Jurnal Teknoif Teknik Informatika Institut Teknologi Padang
type: channel
description: ISSN : 2598-9197 (online), 2338-2724(print) Perihal: Teknik Informatika Frekuensi: 2 kali setahun Bahasa: Indonesia dan Inggris Diindeks di: Crossref, PKP Index, Dimension Sitasi: Google Scholar DOI :10.21063/jtif
publisher: ITP Press
language: id
publication name: Jurnal Teknoif Teknik Informatika Institut Teknologi Padang
issn: 2338-2724
copyright: Jurnal ini dilisensikan berdasarkan Lisensi Internasional Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0). Penulis memegang hak cipta dan memberikan jurnal hak penerbitan pertama. Karya tersebut dapat dibagikan dan diadaptasi, bahkan untuk tujuan komersial, selama penghargaan yang sesuai diberikan dan setiap kreasi baru dilisensikan dengan ketentuan yang sama.
items: Rethinking Graph-Based Approaches: An Empirical Study of Feature Engineering in Network Intrusion Detection
items: Threshold Based Vegetation Classification Using Sentinel-2 and GoogleEarth Engine in Siak-Riau
items: Alzheimer’s Disease Classification using Lightweight Network MobileNet-V3
items: Classification of Daily Rainfall Using XGBoost with SMOTE in The Special Region of Yogyakarta
items: Real-Time IoT-Based Solar Power Monitoring System Using Threshold Decision Algorithm and Mobile Push Notifications
items: WEB-BASED SANTRI MANAGEMENT AND MONITORING SYSTEM INTEGRATED WITH WHATSAPP
items: DESIGN OF SUTI WATER SYSTEM INVENTORY APPLICATION USING THE USER-CENTERED DESIGN (UCD) METHOD
items: IMPLEMENTATION OF FEEDFORWARD NEURAL NETWORK FOR CARDIOVASCULAR DISEASE PREDICTION WITH PERFORMANCE EVALUATION
items: SISTEM INFORMASI GEOGRAFIS PEMETAAN JENIS KEKERASAN TERHADAP PEREMPUAN DI JAWA TENGAH MENGGUNAKAN METODE K-MEANS CLUSTERING
items: COMPARISON OF MACHINE LEARNING CLUSTERING ALGORITHMS FOR ANALYSING ELECTRICITY USAGE PATTERNS IN CAMPUS AREAS
items: DEVELOPMENT OF REAL-TIME MULTI-LOCATION INVENTORY SYSTEM AT PT. AFA KARYALOKA NATA UTAMA USING V-MODEL
items: CLASSIFICATION OF TRAFFIC TICKET CASES AT THE PAGAR ALAM DISTRICT ATTORNEY'S OFFICE USING THE C4.5 ALGORITHM
items: DATA MINING ANALYSIS OF SHELL OIL SALES USING THE C4.5 ALGORITHM AT CV. HARAPAN KARYA MANDIRI
items: IMPLEMENTASI SISTEM KEAMANAN DAN HIGH AVAILABILITY PADA CLOUD SERVER MENGGUNAKAN AMAZON WEB SERVICES (AWS)
items: RANCANG BANGUN SISTEM INFORMASI PENERIMAAN SISWA BARU DENGAN FITUR E-REMINDER BERBASIS WHATSAPP GATEWAY : STUDI KASUS SDIT RABBANI KOTA BENGKULU
items: IDENTIFIKASI KEPADATAN PENDUDUK DI PROVINSI JAWA BARAT MENGGUNAKAN HIERARCHICAL CLUSTERING
items: MODEL REGRESI LOGISTIK DAN JARINGAN SYARAF TIRUAN UNTUK KLASIFIKASI MAHASISWA BERPOTENSI DROPOUT
items: IMPLEMENTASI INCREMENTAL METHOD PADA RANCANG BANGUN WEBSITE PENERBIT PNP PRESS
items: ANALISA LAHAN DAN REKOMENDASI JENIS TANAMAN PADA PERTANIAN CERDAS BERBASIS IOT
items: PENGEMBANGAN WEB SERVICE MENGGUNAKAN FRAMEWORK FASTAPI UNTUK MENINGKATKAN KEMUDAHAN INTEGRASI SISTEM INFORMASI AKADEMIK MULTIPLATFORM
items: SISTEM PENYIRAMAN OTOMATIS PADA PEMBIBITAN PRE-NURSERY KELAPA SAWIT BERBASIS INTERNET OF THINGS
items: PERANCANGAN SISTEM INFORMASI ANALIS BREAK EVEN POINT DAN STOK PADA BUDIDAYA AYAM POTONG BERBASIS WEB
items: INOVASI E-COMMERCE UNTUK OPTIMALISASI PROSES KONSUMEN, PRODUKSI, DAN PEMASARAN BAGI PELAKU UMKM
items: PERANCANGAN APLIKASI PERHITUNGAN BEBAN KERJA DOSEN TERINTEGRASI DENGAN PENDEKATAN WATERFALL
items: PERANCANGAN PROTOTIPE APLIKASI PERUMAHAN TAMAN KENARI SENSOR MONITOR MENGGUNAKAN METODE AGILE
items: IMPLEMENTASI FUZZY TSUKAMOTO DALAM SISTEM PREDIKSI PANEN PADI DI KABUPATEN INDRAMAYU
items: IMPLEMENTASI CHATBOT YANG TERINTEGRASI LAYANAN KEPOLISIAN DALAM PEMBUATAN SIM
items: IMPLEMENTASI QUESTION ANSWERING SYSTEM TAFSIR AL-AZHAR MENGGUNAKAN LANGCHAIN DAN LARGE LANGUAGE MODEL BERBASIS CHATBOT TELEGRAM
items: SIMULASI MONTE CARLO UNTUK ESTIMASI PENGADAAN ATK (STUDI KASUS DI INSTITUT TEKNOLOGI PADANG)
items: Topic Analysis Video Debat Jelang Pemilu Presiden dan Wakil Presiden Tahun 2024

Rethinking Graph-Based Approaches: An Empirical Study of Feature Engineering in Network Intrusion Detection
type: item
description: Although graph-based feature engineering has become widely used in network intrusion detection systems (NIDS), there is a severe lack of empirical research on determining whether the addition of network topology features results in a real positive improvement over the operation of the system or it simply adds complexity to the system. Our paper gets into this gap by critically assessing the performance of graph-based methods as compared to conventional statistical features via systematic comparative analysis across several machine learning paradigms. Using the UNSW-NB15 dataset, we employed a graph-theoretic characteristics that included measures of centrality, the community structure identification and the topological analysis, which were compared to traditional traffic-based characteristics. Results revealed a counterintuitive finding where incorporating graph features consistently degraded detection performance across all algorithms, with statistically significant accuracy reductions observed in multiple classifiers. Random Forest experienced modest performance decline, while Support Vector Machines and RBF Networks showed more substantial degradation. Computational analysis also demonstrated that graph feature extraction imposed substantial overhead compared to traditional feature computation, representing approximately nineteen-fold increase in processing time.
subject: Artikel
  topic: section
subject: Intrusion Detection
  topic: keywords
subject: Cybersecurity
  topic: keywords
subject: Graph Theory
  topic: keywords
subject: Machine Learning
  topic: keywords
subject: Feature Engineering
  topic: keywords
creator: Richard Nwachukwu
rights: Hak Cipta (c) 2026 Richard Nwachukwu https://creativecommons.org/licenses/by-sa/4.0
date: 2026-04-29
publication date: 2026-04-29
starting page: 1
ending page: 10
doi: 10.21063/jtif.2026.V14.1.1-10

Threshold Based Vegetation Classification Using Sentinel-2 and GoogleEarth Engine in Siak-Riau
type: item
description: Land cover change driven by the expansion of oil palm plantations has become a critical environmental issue in Siak Regency, Riau Province, necessitating periodic vegetation monitoring for sustainable land management. This study aimed to integrate Google Earth Engine and Quantum Geographic Information System to analyze vegetation changes in oil palm plantations using Sentinel-2 imagery from the 2022 to 2024 period. The methods involved processing Sentinel-2 Level-2A imagery through cloud masking, generating annual median-based composites, and calculating vegetation indices, including the Normalized Difference Vegetation Index, Enhanced Vegetation Index, and Soil Adjusted Vegetation Index. These indices were classified into several density classes to map land cover conditions, while changes in oil palm and non-oil palm areas were identified annually. All image processing stages were performed on a cloud computing platform, and the results were exported for spatial visualization and further analysis. The findings indicated that Siak Regency remained predominantly characterized by moderate to dense vegetation, particularly in the central and eastern regions. However, annual vegetation dynamics were detected in the western region, which was dominated by residential and industrial activities. In Koto Gasib District, there was a measurable increase in non-oil palm classes and expanding land cover changes over time. Overall, the integration of cloud-based processing and desktop geographic information systems proved effective in producing accurate spatial information for multitemporal analysis to support land use planning and oil palm plantation management in Siak Regency.
subject: Artikel
  topic: section
subject: Google Earth Engine
  topic: keywords
subject: Land Cover Change
  topic: keywords
subject: Multitemporal Classification
  topic: keywords
subject: Oil Palm Monitoring
  topic: keywords
subject: Sentinel-2
  topic: keywords
subject: Vegetation Index
  topic: keywords
creator: Elvira Nurrahma
creator: Faiza Aulia Supriatna
creator: Inggit Lolita Sari
creator: Emilia roza
creator: Harry Ramza
rights: Hak Cipta (c) 2026 Elvira Nurrahma, Faiza Aulia Supriatna, Inggit Lolita Sari, Emilia roza, Harry Ramza https://creativecommons.org/licenses/by-sa/4.0
date: 2026-04-30
publication date: 2026-04-30
starting page: 24
ending page: 46
doi: 10.21063/jtif.2026.V14.1.24-46

Alzheimer’s Disease Classification using Lightweight Network MobileNet-V3
type: item
description: Alzheimer’s disease is a major public health concern characterized by progressive cognitive decline due to irreversible neuronal damage. Alzheimer’s disease represents a major global health concern in the twenty-first century. Although magnetic resonance imaging (MRI) is widely used for early diagnosis, manual interpretation is time-consuming and subject to variability. This study proposes an automated classification system based on the lightweight MobileNetV3 architecture to improve diagnostic efficiency. The model leverages depthwise separable convolutions to reduce computational complexity while maintaining high performance. MobileNetV3 models is then evaluated using appropriate metrics to assess the effectiveness of the proposed classification approach. Data augmentation techniques, including random rotation and flipping, are applied to enhance model generalization. Experimental results demonstrate that the MobileNetV3 Small model achieves superior performance, with an accuracy and F1-score of approximately 0.94, compared to 0.90 for the MobileNetV3 Large model. These findings indicate that the compact architecture provides better efficiency and reliability for Alzheimer’s disease classification. The proposed approach is suitable for deployment in resource-constrained medical environments.
subject: Artikel
  topic: section
subject: Alzheimer’s Disease
  topic: keywords
subject: Classification
  topic: keywords
subject: Deep Learning
  topic: keywords
subject: Convolutional Neural Networks
  topic: keywords
creator: Muhammad Sadewa Wicaksana Wibowo
creator: M Cahyo Kriswantoro
creator: Neni Purwati
rights: Hak Cipta (c) 2026 Muhammad Sadewa Wicaksana Wibowo, M Cahyo Kriswantoro, Neni Purwati https://creativecommons.org/licenses/by-sa/4.0
date: 2026-04-30
publication date: 2026-04-30
starting page: 47
ending page: 58
doi: 10.21063/jtif.2026.V14.1.47-58

Classification of Daily Rainfall Using XGBoost with SMOTE in The Special Region of Yogyakarta
type: item
description: Rainfall is a meteorological parameter that influences various sectors, such as agriculture, water resource management, and disaster mitigation; however, the process of classifying it still faces challenges, particularly due to imbalanced data across categories. This study aims to evaluate the performance of the XGBoost algorithm in classifying daily rainfall in the Special Region of Yogyakarta using NASA POWER data from 2000 to 2025, with input variables including air temperature, relative humidity, wind speed, and surface pressure. The evaluation was conducted using accuracy, precision, recall, and F1-score metrics to provide a more comprehensive overview of the model’s performance. The results indicate that the model achieved an accuracy of 0.82 and performed well in identifying light rain, and began to identify moderate rain, although not yet optimally; however, its performance remains limited for higher-intensity rain classes. This suggests that imbalanced data distribution remains a primary factor affecting model performance, making data quality and balance critical considerations in the development of rainfall classification models.
subject: Artikel
  topic: section
subject: Rainfall
  topic: keywords
subject: XGBoost
  topic: keywords
subject: SMOTE
  topic: keywords
subject: Classification
  topic: keywords
creator: Ayyesa Azzahra Mulia Ramadani
creator: Danur Wijayanto
rights: Hak Cipta (c) 2026 Ayyesa Azzahra Mulia Ramadani, Danur Wijayanto https://creativecommons.org/licenses/by-sa/4.0
date: 2026-04-30
publication date: 2026-04-30
starting page: 59
ending page: 67
doi: 10.21063/jtif.2026.V14.1.59-67

Real-Time IoT-Based Solar Power Monitoring System Using Threshold Decision Algorithm and Mobile Push Notifications
type: item
description: The establishment of solar power installations as a renewable energy option necessitates dependable monitoring systems to ensure peak performance. Nonetheless, current monitoring solutions typically emphasize only data visualization, lacking intelligent early warning features, which results in slower fault detection and faster battery deterioration. This research tackles this gap by creating a mobile monitoring system based on the Internet of Things (IoT), where both the threshold-based decision algorithm and notification logic are fully integrated into the mobile application, rather than the IoT hardware. The system employs an ESP8266 microcontroller exclusively for gathering data from a PZEM-017 DC sensor, transmitting raw readings to Firebase Realtime Database. A mobile application built on Flutter fetches data, checks it against user-defined thresholds (voltage, current, power), and produces immediate push notifications with anti-spam delays, audio alerts, and optional Telegram sending. Experimental outcomes from 30 measurement locations and 50 anomaly simulations indicate that the system reaches a voltage measurement error of 1.22% and a current error of 9.90% in comparison to a calibrated multimeter. The typical notification delay is 3.4 seconds, significantly less than the 10-second goal. In contrast to edge-based thresholding (on microcontroller), the mobile-centric method enables users to modify thresholds flexibly through the app without the need for hardware reprogramming, offers more extensive notification options (local pop-up, sound, Telegram), and streamlines IoT device upkeep. The specialized mobile interface provides enhanced customization and data logging features in comparison to standard platforms like Blynk or Telegram-based options.
subject: Artikel
  topic: section
subject: Firebase
  topic: keywords
subject: Flutter
  topic: keywords
subject: Internet of Things
  topic: keywords
subject: Real-Time Notifications
  topic: keywords
subject: Solar Power Plant
  topic: keywords
subject: Threshold Decision Algorithm
  topic: keywords
creator: Afif Fathur Rachman
creator: Yasdinul Huda
creator: Ika Parma Dewi
creator: Hadi Kurnia Saputra
creator: Asnal Effendi
rights: Hak Cipta (c) 2026 Afif Fathur Rachman, Yasdinul Huda, Ika Parma Dewi, Hadi Kurnia Saputra, Asnal Effendi https://creativecommons.org/licenses/by-sa/4.0
date: 2026-04-30
publication date: 2026-04-30
starting page: 11
ending page: 23
doi: 10.21063/jtif.2026.V14.1.11-23

WEB-BASED SANTRI MANAGEMENT AND MONITORING SYSTEM INTEGRATED WITH WHATSAPP
type: item
description: The increasing number of students in Islamic boarding schools (pesantren) has made administrative tasks such as recording student violations, achievements, permissions, and health records more complex. Many schools still manage these data manually, resulting in duplication, delayed communication, and inefficient supervision. This study addresses this issue by developing a Web-Based Santri Management and Monitoring System integrated with WhatsApp, aiming to streamline data management and enhance real-time communication between administrators, guardians, and health staff. The system was developed using the Waterfall methodology, which includes requirement analysis, system design, implementation, testing, and maintenance stages. Three main user roles were defined: administrators, guardians, and health staff, each with specific responsibilities. A User Acceptance Test (UAT) was conducted with 32 respondents, including one administrator, 30 guardians, and one health staff. The results showed satisfaction levels of 100% for administrators, 87% for guardians, and 100% for health staff, indicating high user acceptance. These findings suggest that the system effectively addresses the challenges of manual data management, improves administrative efficiency, and strengthens communication through real-time WhatsApp notifications, providing a comprehensive solution for student monitoring and supervision in Islamic boarding schools.
subject: Artikel
  topic: section
subject: web-based system
  topic: keywords
subject: santri management
  topic: keywords
subject: monitoring system
  topic: keywords
subject: WhatsApp integration
  topic: keywords
creator: Lucita Aprillia
creator: Yang Agita Rindri
creator: Tri Agusti Farma
rights: Hak Cipta (c) 2025 Lucita Aprillia, Yang Agita Rindri, Tri Agusti Farma https://creativecommons.org/licenses/by-sa/4.0
date: 2025-10-31
publication date: 2025-10-31
starting page: 117
ending page: 126
doi: 10.21063/jtif.2025.V13.2.117-126

DESIGN OF SUTI WATER SYSTEM INVENTORY APPLICATION USING THE USER-CENTERED DESIGN (UCD) METHOD
type: item
description: Inventory management (stock) is an important factor for business operational continuity. The Suti Water bottled water business unit, managed by the Indonesian Islamic Boarding School Cooperation Agency (BKsPPI), was facing serious constraints where the manual recording system often resulted in delays and data inaccuracies, which had a significant impact on operational efficiency. This study aimed to overcome these challenges by designing and developing an inventory application prototype with a focus on optimizing the User Interface (UI) and User Experience (UX). The User-Centered Design (UCD) methodology was adopted to ensure that the application design was centered on the real needs of the Suti Water Main Distributor warehouse staff. Following development, the application's usability was evaluated using the System Usability Scale (SUS). The testing results showed a SUS score of 93.0, which placed the application in the 'Acceptable' category with an "Excellent" rating. These findings demonstrate that the developed prototype is an effective and highly accepted solution by the users. Furthermore, the application proved to reduce transaction recording time and significantly minimize data errors..
subject: Artikel
  topic: section
subject: Pengelolaan Persediaan
  topic: keywords
subject: System Usability Scale
  topic: keywords
subject: User-Centered Design (UCD)
  topic: keywords
subject: Usability
  topic: keywords
creator: Muhammad Farhan
creator: Hersanto Fajri
creator: Berlina Wulandari
creator: Muh. Arbiyansyah Nur
rights: Hak Cipta (c) 2025 Muhammad Farhan, Hersanto Fajri, Berlina Wulandari, Muh. Arbiyansyah Nur https://creativecommons.org/licenses/by-sa/4.0
date: 2025-10-31
publication date: 2025-10-31
starting page: 105
ending page: 116
doi: 10.21063/jtif.2025.V13.2.105-116

IMPLEMENTATION OF FEEDFORWARD NEURAL NETWORK FOR CARDIOVASCULAR DISEASE PREDICTION WITH PERFORMANCE EVALUATION
type: item
description: Disease is crucial to prevent more serious complications. This study implemented a Feedforward Neural Network (FNN) algorithm to build a cardiovascular disease risk prediction model using patient clinical data. The dataset used was sourced from open sources and underwent preprocessing stages such as one-hot encoding and normalization. The model architecture consists of two hidden layers with ReLU and dropout activation functions, and an output layer with a sigmoid function for binary classification. Training was conducted for 100 epochs with a data split ratio of 80:20. Evaluation was carried out using accuracy, precision, recall, F1-score, and confusion matrix metrics. The evaluation results showed that the model achieved a training accuracy of 92% and a testing accuracy of 88%, with an average F1-score of 87.2%. The Confidence Factor value also indicated a high level of confidence in each prediction. These results indicate that the FNN model is effective for cardiovascular disease risk prediction and has the potential to be used as a tool for rapid and accurate medical decision-making.
subject: Artikel
  topic: section
subject: Cardiovascular disease
  topic: keywords
subject: Feedforward neural network
  topic: keywords
subject: risk prediction
  topic: keywords
subject: confidence factor
  topic: keywords
subject: Machine Learning
  topic: keywords
creator: Muhammad Rafli Raflin
creator: Misbahuddin
creator: Bulkis Kanata
rights: Hak Cipta (c) 2025 Muhammad Rafli, Misbahuddin, Bulkis Kanata https://creativecommons.org/licenses/by-sa/4.0
date: 2025-10-31
publication date: 2025-10-31
starting page: 97
ending page: 104
doi: 10.21063/jtif.2025.V13.2.97-104

SISTEM INFORMASI GEOGRAFIS PEMETAAN JENIS KEKERASAN TERHADAP PEREMPUAN DI JAWA TENGAH MENGGUNAKAN METODE K-MEANS CLUSTERING
type: item
description: Violence against women is a social issue with widespread impacts and remains highly prevalent in Indonesia, including in Central Java Province. The forms of violence include physical, psychological, and sexual abuse, exploitation, neglect, and others. Presenting data in a general form without spatial mapping often makes it difficult to identify regions with high levels of vulnerability. This study aims to cluster regencies/municipalities in Central Java based on types of violence against women by integrating the K-Means Clustering method with Geographic Information Systems (GIS). The data used are records of violence against women in 2024 from 35 regencies/municipalities. The K-Means method was applied iteratively until reaching a convergent condition, resulting in three main clusters. The clustering results were visualized using QGIS software in the form of thematic maps, facilitating the interpretation of spatial patterns. The evaluation shows that spatial classification was successfully applied with a spatial match rate of 100%, and a Silhouette Score of 0.577, indicating a moderately good cluster quality. The majority of regions are included in the low cluster, while only one region is in the high cluster. This study concludes that the combination of K-Means and GIS is effective in detecting and visualizing regional vulnerability to violence against women and has the potential to serve as a basis for developing more targeted and evidence-based protection policies. It is recommended that future research expand the dataset, include additional risk variables, and explore alternative clustering methods or advanced spatial analyses to improve the accuracy and understanding of violence patterns.
subject: Artikel
  topic: section
subject: Kekerasan terhadap Perempuan
  topic: keywords
subject: K-Means Clustering
  topic: keywords
subject: Sistem Informasi Geografis
  topic: keywords
subject: Klaster spasial
  topic: keywords
subject: QGIS
  topic: keywords
creator: Novan Maulana
creator: Aris Tri Jaka Harjanta
creator: Mega Novita
rights: Hak Cipta (c) 2025 Novan Maulana, Aris Tri Jaka Harjanta, Mega Novita https://creativecommons.org/licenses/by-sa/4.0
date: 2025-10-31
publication date: 2025-10-31
starting page: 77
ending page: 86
doi: 10.21063/jtif.2025.V13.2.77-86

COMPARISON OF MACHINE LEARNING CLUSTERING ALGORITHMS FOR ANALYSING ELECTRICITY USAGE PATTERNS IN CAMPUS AREAS
type: item
description: Electricity consumption in campus environments varies based on building functions, occupancy patterns, and time-of-day usage. Understanding these variations is essential for efficient energy management. Uncontrolled electricity use often results in high operational costs, highlighting the need for accurate methods to uncover consumption patterns. This study analyzes electricity consumption data from multiple campus buildings at a polytechnic in Jakarta during 2023 and 2024. Each dataset consists of six columns and 365 rows in a year. Since the data is unlabeled, three clustering algorithms: K-Means, Hierarchical Clustering, and DBSCAN are applied to identify usage patterns across campus areas. Pre-processing included imputation and normalization, followed by clustering. Cluster quality was evaluated using the Silhouette Score. A key novelty of this study is the year-to-year comparative analysis, showing that clustering performance can vary significantly depending on data structure and noise. The 2023 dataset (dataset 1) achieved the highest Silhouette Score of 0.48 using DBSCAN, while the 2024 dataset (dataset 2) produced the best result with Hierarchical Clustering at 0.53. These results emphasize the importance of selecting clustering methods based on data characteristics and temporal context. The findings contribute to developing adaptive, data-driven strategies for managing energy use in non-residential settings, particularly in educational institutions like campuses.
subject: Artikel
  topic: section
subject: electricity consumption
  topic: keywords
subject: campus area
  topic: keywords
subject: clustering algorithm
  topic: keywords
subject: machine learning
  topic: keywords
creator: Diya Namira Purba
creator: Muhammad Ridha
creator: Rida Indah Fariani
creator: Harkiapri Yanto
rights: Hak Cipta (c) 2025 Diya Namira Purba, Muhammad Ridha, Rida Indah Fariani, Harkiapri Yanto https://creativecommons.org/licenses/by-sa/4.0
date: 2025-10-31
publication date: 2025-10-31
starting page: 87
ending page: 96
doi: 10.21063/jtif.2025.V13.2.87-96

DEVELOPMENT OF REAL-TIME MULTI-LOCATION INVENTORY SYSTEM AT PT. AFA KARYALOKA NATA UTAMA USING V-MODEL
type: item
description: Inventory management in companies with multiple locations often faces challenges when conventional tools such as spreadsheets are still used, causing inefficiency and difficulties in maintaining accurate records. Previous studies have largely focused on single-location systems without real-time integration, leaving a gap in supporting centralized and synchronized inventory control. This study aims to develop a web-based inventory information system that supports real-time and multi-location operations to improve efficiency and accuracy in stock management. The system was developed using the V-Model methodology, which includes requirements analysis, system design, architectural design, module design, implementation, and testing. Research data were obtained through interviews with company employees and literature review. System testing was conducted using the Black Box Testing method, which focuses on validating functionality based on inputs and outputs without producing quantitative data. Therefore, the evaluation was based on the conformity of the system with the specified requirements. The results show that the developed system is capable of handling core functions such as warehouse and counter stock management, shipping records, return records, and user management, all integrated into a centralized database with real-time synchronization across locations. This ensures that inventory data remains consistent and up to date. In conclusion, the research successfully addresses the identified gap by presenting a web-based, multi-location inventory information system with real-time integration, thereby supporting greater efficiency, accuracy, and control in inventory management.
subject: Artikel
  topic: section
subject: Information System
  topic: keywords
subject: Inventory
  topic: keywords
subject: Multi-Location
  topic: keywords
subject: Real-Time
  topic: keywords
subject: V-Model
  topic: keywords
creator: ARIF SA'BANNA HASIBUAN
creator: Tedi Setiadi
rights: Hak Cipta (c) 2025 Arif Sa’banna Hasibuan; Tedi Setiadi https://creativecommons.org/licenses/by-sa/4.0
date: 2025-10-31
publication date: 2025-10-31
starting page: 66
ending page: 76
doi: 10.21063/jtif.2025.V13.2.66-76

CLASSIFICATION OF TRAFFIC TICKET CASES AT THE PAGAR ALAM DISTRICT ATTORNEY'S OFFICE USING THE C4.5 ALGORITHM
type: item
description: The increasing number of traffic violations in Pagar Alam City has led to a yearly rise in ticketing case data at the Pagar Alam District Attorney’s Office. This accumulation of data creates difficulties in effective data management and hinders the extraction of meaningful insights. The current classification process for ticketing cases remains limited in its accuracy and efficiency, making it difficult to identify patterns or trends. This study aims to address this issue by developing a classification model for traffic ticket cases using data mining techniques, specifically the C4.5 algorithm. The model classifies cases based on attributes such as the relevant article of law, type of vehicle, evidence submitted, and the fine imposed. The CRISP-DM framework is used to guide the process through six phases: business understanding, data understanding, data preparation, modeling, evaluation, and deployment. RapidMiner is used as the primary tool for data processing, and the model is evaluated using the X-Cross Validation technique. The results show that the C4.5 algorithm achieves a high classification accuracy of 99.75%. The “Article” attribute emerged as the most influential factor with the highest gain ratio value. These findings can support law enforcement and policymakers in identifying the most frequent violations and developing more targeted strategies to improve traffic law enforcement and public safety.
subject: Artikel
  topic: section
subject: Classification
  topic: keywords
subject: Data Mining
  topic: keywords
subject: C4.5 Algorithm
  topic: keywords
creator: Sabella Azhari
creator: Muntahanah
rights: Hak Cipta (c) 2025 Sabella Azhari, Muntahanah https://creativecommons.org/licenses/by-sa/4.0
date: 2025-10-31
publication date: 2025-10-31
starting page: 57
ending page: 65
doi: 10.21063/jtif.2025.V13.2.57-65

DATA MINING ANALYSIS OF SHELL OIL SALES USING THE C4.5 ALGORITHM AT CV. HARAPAN KARYA MANDIRI
type: item
description: This study focuses on the analysis of Shell oil sales at CV. Harapan Karya Mandiri (HKM) Bengkulu, which faces challenges in predicting consumer demand and managing stock efficiently. CV. HKM Bengkulu is an official distributor of PT. Shell Indonesia, competing in the vehicle lubricant industry. To address the challenges of competition and demand uncertainty, this study applies data mining methods, particularly the C4.5 algorithm, to analyze historical sales data and uncover significant patterns and trends. Data mining is a technique that helps identify hidden patterns and insights in large datasets to support decision-making. The C4.5 algorithm is employed to build a predictive model through a decision tree, which classifies data based on certain variables such as oil type, sales region, or time period. This model is expected to assist CV. HKM in predicting customer demand, optimizing sales strategies, and improving stock planning efficiency. Additionally, the results from the C4.5 algorithm provide practical benefits by enabling CV. HKM to optimize inventory management, target marketing efforts more effectively, and enhance operational efficiency. The insights derived from the model support data-driven decisions, improve business performance, and maximize profits by aligning stock levels with demand trends, thereby reducing wastage and improving profitability.
subject: Artikel
  topic: section
subject: Analysis
  topic: keywords
subject: Data Mining
  topic: keywords
subject: Sales
  topic: keywords
subject: C4.5 Algorithm
  topic: keywords
creator: Seci Monika
creator: Muhammad Husni Rifqo
rights: Hak Cipta (c) 2025 Seci Monika, Muhammad Husni Rifqo https://creativecommons.org/licenses/by-sa/4.0
date: 2025-10-31
publication date: 2025-10-31
starting page: 48
ending page: 56
doi: 10.21063/jtif.2025.V13.2.48-56

IMPLEMENTASI SISTEM KEAMANAN DAN HIGH AVAILABILITY PADA CLOUD SERVER MENGGUNAKAN AMAZON WEB SERVICES (AWS)
type: item
description: Ketersediaan layanan dan keamanan merupakan aspek krusial dalam pengelolaan server web, terutama pada institusi pendidikan yang memanfaatkan teknologi berbasis cloud. Penelitian ini bertujuan untuk mengimplementasikan sistem high availability dan keamanan pada server web SMKN 5 Padang menggunakan Amazon Web Services (AWS). Metode yang digunakan meliputi penerapan load balancing (Elastic Load Balancing) dengan tujuan efektivitas distribusi beban menggunakan layanan untuk mendistribusikan beban server secara merata, Auto Scaling berguna menyesuaikan jumlah instance secara dinamis berdasarkan beban lalu lintas, serta Wazuh sebagai sistem pemantauan keamanan untuk mendeteksi dan merespons ancaman siber seperti serangan DoS (Denial of Service). Evaluasi kinerja sistem dilakukan melalui uji beban (stress test) pada web server dan analisis log keamanan. Hasil implementasi menunjukkan bahwa load balancing efektif dalam mengoptimalkan distribusi lalu lintas jaringan, Auto Scaling mampu menjaga ketersediaan layanan secara otomatis saat terjadi lonjakan akses, serta Wazuh berhasil mendeteksi dan memitigasi ancaman keamanan secara real-time. Kontribusi utama penelitian ini adalah penguatan arsitektur server web berbasis cloud dengan pendekatan high availability dan keamanan adaptif yang dapat diadopsi oleh institusi pendidikan lainnya.
subject: Artikel
  topic: section
subject: AWS
  topic: keywords
subject: high availability
  topic: keywords
subject: load balancing
  topic: keywords
subject: Auto Scaling
  topic: keywords
subject: Wazuh
  topic: keywords
subject: keamanan siber
  topic: keywords
creator: Andre Febrian Kasmar
creator: Wahyuna Wahyuna
creator: Fanni Sukma
creator: Sitti Amalia
rights: Hak Cipta (c) 2025 Andre Febrian Kasmar; Wahyuna Wahyuna, Fanni Sukma, Sitti Amalia https://creativecommons.org/licenses/by-sa/4.0
date: 2025-04-30
publication date: 2025-04-30
starting page: 40
ending page: 47
doi: 10.21063/jtif.2025.V13.1.40-47

RANCANG BANGUN SISTEM INFORMASI PENERIMAAN SISWA BARU DENGAN FITUR E-REMINDER BERBASIS WHATSAPP GATEWAY : STUDI KASUS SDIT RABBANI KOTA BENGKULU
type: item
description: Dalam era digital yang terus berkembang, pengelolaan data dan informasi di lingkungan pendidikan menjadi aspek yang sangat penting. Proses penerimaan siswa baru di SDIT Rabbani Kota Bengkulu masih menghadapi berbagai kendala, seperti penumpukan berkas, kesulitan dalam manajemen data, dan keterlambatan proses administrasi. Hal tersebut berdampak pada kurang optimalnya kelancaran dan efisiensi proses penerimaan siswa. Untuk mengatasi permasalahan tersebut, penelitian ini bertujuan untuk merancang dan membangun sistem informasi penerimaan siswa baru berbasis web dengan fitur e-Reminder melalui WhatsApp Gateway. Penelitian ini menggunakan metode pengembangan perangkat lunak Waterfall, dengan tahapan analisis, desain, implementasi, pengujian, dan pemeliharaan. Sistem dikembangkan menggunakan framework Laravel dan Vue.js, serta diintegrasikan dengan layanan WhatsApp untuk mengirimkan notifikasi otomatis terkait tahapan dan jadwal penting dalam proses penerimaan. Hasil dari implementasi sistem menunjukkan bahwa proses penerimaan menjadi lebih terstruktur, waktu penyelesaian administrasi lebih cepat, dan komunikasi antara sekolah dan calon wali siswa menjadi lebih efektif. Dengan demikian, sistem ini mampu meningkatkan kinerja administrasi penerimaan siswa serta memberikan pengalaman layanan yang lebih modern dan informatif.
subject: Artikel
  topic: section
subject: Information System
  topic: keywords
subject: E-reminder
  topic: keywords
subject: WhatsApp Gateway
  topic: keywords
subject: Laravel
  topic: keywords
subject: Vue.js
  topic: keywords
creator: Haris Suryamen
creator: Ullya Mega Wahyuni
creator: Muhammad Fairuzi Iszam Aziz
rights: Hak Cipta (c) 2025 Haris Suryamen, Ullya Mega Wahyuni, Muhammad Fairuzi Iszam Aziz https://creativecommons.org/licenses/by-sa/4.0
date: 2025-04-30
publication date: 2025-04-30
starting page: 17
ending page: 27
doi: 10.21063/jtif.2025.V13.1.17-27

IDENTIFIKASI KEPADATAN PENDUDUK DI PROVINSI JAWA BARAT MENGGUNAKAN HIERARCHICAL CLUSTERING
type: item
description: Penelitian ini menerapkan algoritma hierarchical clustering untuk mengidentifikasi pola kepadatan penduduk di Jawa Barat (18 kabupaten, 9 kota) sebagai dasar penanggulangan bencana alam. Data kepadatan penduduk 2020-2022 dari Dinas Kependudukan Jawa Barat dianalisis untuk mengelompokkan wilayah menjadi tiga kategori: terpadat, sedang, dan terendah. Metode hierarchical clustering digunakan untuk mengelompokkan wilayah berdasarkan kepadatan penduduk dan potensi banjir, dengan atribut tambahan yaitu keberadaan sungai. Hasil pengelompokan dievaluasi menggunakan Davies-Bouldin index. Hasilnya menunjukkan bahwa algoritma berhasil diterapkan, mengelompokkan 20 kabupaten/kota dengan kepadatan penduduk terendah (Cluster 0), 3 kabupaten/kota dengan kepadatan sedang (Cluster 1), dan 4 kabupaten/kota dengan kepadatan terpadat (Cluster 2).Penelitian ini diharapkan dapat memberikan wawasan kepada pemerintah dan lembaga terkait dalam merencanakan mitigasi bencana berdasarkan pola kepadatan penduduk, sehingga dapat mengurangi risiko bencana alam di masa depan. Penelitian ini mengambil data dari sumber resmi https://jabar.bps.go.id/indicator/12/245/1/kepadatan-penduduk-menurut-kabupaten-kota.html. Tujuan utama penelitian ini adalah untuk memahami pola kepadatan penduduk yang dapat memberikan indikasi tingkat risiko terhadap bencana alam tertentu di wilayah Jawa Barat. Informasi ini diharapkan dapat digunakan sebagai dasar untuk strategi penanggulangan bencana yang lebih efektif dan efisien di masa depan. Implikasi dari penelitian ini menunjukkan bahwa dengan memahami pola kepadatan penduduk dan distribusi sungai melalui metode hierarchical clustering, pemerintah dan lembaga terkait dapat merumuskan strategi penanggulangan bencana yang lebih tepat sasaran.
subject: Artikel
  topic: section
subject: Hierarchical Clustering
  topic: keywords
subject: Kepadatan penduduk
  topic: keywords
subject: Penanggulangan bencana
  topic: keywords
subject: Sungai
  topic: keywords
creator: Wahyu Iskandar Simanjuntak
creator: Yusran Timur Samuel
rights: Hak Cipta (c) 2025 Wahyu Iskandar Simanjuntak, Yusran Timur Samuel https://creativecommons.org/licenses/by-sa/4.0
date: 2025-04-30
publication date: 2025-04-30
starting page: 28
ending page: 39
doi: 10.21063/jtif.2025.V13.1.28-39

MODEL REGRESI LOGISTIK DAN JARINGAN SYARAF TIRUAN UNTUK KLASIFIKASI MAHASISWA BERPOTENSI DROPOUT
type: item
description: Setiap perguruan tinggi memiliki mahasiswa yang keluar tanpa keterangan, termasuk mahasiswa yang gagal hingga akhir masa studinya dan dinyatakan drop out (DO). Langkah awal penyelesaian permasalahan mahasiswa DO dapat dilakukan melalui teknik klasifikasi. Penelitian ini bertujuan untuk mengklasifikasi mahasiswa DO menggunakan metode regresi logistik yang dikomparasi dengan metode Jaringan Syaraf Tiruan (JST) untuk membagi data dalam 5 klasifikasi: Aktif, Lulus, Potensi Lulus, Potensi DO, dan DO. Data yang digunakan adalah data akademik mahasiswa Program Studi Ilmu Komputer yang diperoleh dari PUSTIPADA UIN Sumatera Utara yang berupa: tahun masuk, lama studi, IPS, IPK, SKS per semester, total SKS, dan UKT. Sebanyak 1337 data mahasiswa yang dibagi dalam 80% pelatihan, dan 20% pengujian. Hasil pengujian model regresi logistik terhadap data uji memperoleh akurasi 93%, sementara model JST lebih unggul dengan akurasi 96%. Hal ini menunjukkan bahwa JST lebih efektif dalam menangkap pola kompleks dan variatif pada data mahasiswa. Hasil penelitian ini dapat memberikan kontribusi kepada lembaga akademik dan pengambil kebijakan pendidikan khususnya Program Studi Ilmu Komputer untuk membuat keputusan atau program pencegahan potensi drop out terhadap mahasiswa yang memiliki karakteristik serupa dengan data yang digunakan dalam penelitian ini.
subject: Artikel
  topic: section
subject: Drop out
  topic: keywords
subject: Mahasiswa
  topic: keywords
subject: Regresi Logistik
  topic: keywords
subject: Jaringan Syaraf Tiruan
  topic: keywords
creator: Armansyah Armansyah
creator: Suhardi Suhardi
rights: Hak Cipta (c) 2025 Armansyah Armansyah, Suhardi Suhardi https://creativecommons.org/licenses/by-sa/4.0
date: 2025-04-30
publication date: 2025-04-30
starting page: 8
ending page: 16
doi: 10.21063/jtif.2025.V13.1.8-16

IMPLEMENTASI INCREMENTAL METHOD PADA RANCANG BANGUN WEBSITE PENERBIT PNP PRESS
type: item
description: Penerbit PNP Press merupakan salah satu penerbit di Indonesia yang berada di bawah naungan perguruan tinggi negeri Politeknik Negeri Padang, penerbit ini menerbitkan dua model penerbitan, yakni Majalah dan buku. Jenis buku yang diterbitkan di PNP Press adalah buku ilmiah, teks, dan referensi. Sedangkan jenis artikel yang di terbitkan di majalah adalah artikel populer dan artikel dari beberapa rubrik. Meningkatnya permintaan akan publikasi buku dan majalah pada penerbit ini, diperlukan sebuah sistem yang dapat mengelola proses publikasi secara efektif dan efisien. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sebuah website yang dapat memfasilitasi proses publikasi dan distribusi majalah dan buku di PNP Press menggunakan metode Incremental. Metode ini dipilih karena dapat mengakomodir berbagai macam kebutuhan selama proses pengembangan sistem. Penggunaan Incremental Method dalam membangun website penerbit terbukti mampu menghasilkan website penerbit PNP Press yang sesuai dengan kebutuhan pengguna dan memastikan sistem dapat diimplementasikan secara efektif, yakni berupa buku yang terbit menggunakan open open monograph press (OMP) dan majalah menggunakan open journal system (OJS).
subject: Artikel
  topic: section
subject: Penerbit
  topic: keywords
subject: PNP Press
  topic: keywords
subject: OJS
  topic: keywords
subject: OMP
  topic: keywords
subject: Website
  topic: keywords
subject: Metode Incremental
  topic: keywords
creator: Riyan Ikhbal Salam
creator: Ikhsan
creator: Rayendra
creator: Ismael
creator: Dian Eka Putra
creator: Ramadhani
rights: Hak Cipta (c) 2025 Ikhsan https://creativecommons.org/licenses/by-sa/4.0
date: 2025-04-30
publication date: 2025-04-30
starting page: 1
ending page: 7
doi: 10.21063/jtif.2025.V13.1.1-7

ANALISA LAHAN DAN REKOMENDASI JENIS TANAMAN PADA PERTANIAN CERDAS BERBASIS IOT
type: item
description: Pertanian berbasis teknologi merupakan pendekatan modern yang memanfaatkan Internet of Things (IoT) untuk mendukung proses produksi secara efisien. Di Kampung Durian Tarung, Pasar Ambacang, Kuranji, Padang, Sumatera Barat, kelompok petani hortikultura menghadapi tantangan dalam menentukan jenis tanaman yang sesuai dengan kualitas tanah di lahan mereka. Penelitian ini mengembangkan sistem berbasis IoT untuk analisis lahan yang dapat merekomendasikan jenis tanaman optimal sesuai kondisi tanah. Teknologi IoT diimplementasikan untuk mengumpulkan data tanah, seperti pH, kelembaban, dan suhu tanah, melalui sensor-sensor nirkabel. Data tersebut dianalisis dengan metode fuzzy, yang memungkinkan pengambilan keputusan berdasarkan sejumlah parameter kualitas tanah untuk memberikan rekomendasi yang lebih tepat dan real-time. Hasil uji coba menunjukkan bahwa sistem mampu mengukur kondisi tanah secara akurat dan memberikan rekomendasi tanaman yang sesuai berdasarkan data kualitas tanah yang diperoleh. Penggunaan metode fuzzy terbukti efektif dalam menyaring data dari sensor dan menyesuaikan rekomendasi tanaman berdasarkan nilai ambang pada pH, kelembaban, dan suhu tanah. Penelitian ini berkontribusi pada bidang pertanian cerdas dengan menghadirkan solusi berbasis IoT yang spesifik untuk kebutuhan petani hortikultura lokal. Menggabungkan teknologi sensor nirkabel dan metode fuzzy memungkinkan analisis yang lebih adaptif dan relevan dengan kondisi tanah di lahan pertanian. Keberhasilan penelitian ini memberikan arah bagi pengembangan sistem serupa yang dapat diterapkan di wilayah lain, serta menggarisbawahi peran teknologi IoT dalam mendukung keberlanjutan pertanian melalui pemanfaatan data secara optimal.
subject: Artikel
  topic: section
subject: Analisis Lahan
  topic: keywords
subject: Rekomendasi Tanaman
  topic: keywords
subject: sensor nirkabel (WSN)
  topic: keywords
subject: Internet of Thisngs (IoT)
  topic: keywords
creator: Busran Busran
creator: Anna Syahrani
creator: Eko Kurniawanto Putra
creator: Eva Yulianti
creator: Muhammad Vajri Djauhari
rights: Hak Cipta (c) 2024 Muhammad Vajri Djauhari, Busran Busran, Eva Yulianti, Eko Kurniawanto Putra, Anna Syahrani https://creativecommons.org/licenses/by-sa/4.0
date: 2024-10-30
publication date: 2024-10-30
starting page: 92
ending page: 99
doi: 10.21063/jtif.2024.V12.2.92-99

PENGEMBANGAN WEB SERVICE MENGGUNAKAN FRAMEWORK FASTAPI UNTUK MENINGKATKAN KEMUDAHAN INTEGRASI SISTEM INFORMASI AKADEMIK MULTIPLATFORM
type: item
description: Kegiatan akademik yang ada pada Universitas Dian Nuswantoro dikelola menggunakan sistem informasi akademik mahasiswa, dosen, tenaga pendidik, dan orang tua (wali) mahasiswa berbasis web dan berbasis mobile (Android dan IOS). Proses pengambilan data yang digunakan oleh sistem informasi akademik saat ini berada pada masing-masing sistem itu sendiri sehingga rawan terjadi kesalahan. Maka, diperlukan sebuah layanan back-end berupa web service yang bertindak sebagai portal proses pengambilan data yang bisa digunakan oleh sistem informasi akademik multiplatform tersebut. Selain membantu untuk terhindar dari kesalahan pengambilan data, web service yang dibangun juga menyediakan dokumentasi penggunaan web service yang lengkap dan mudah dipahami. Waktu rata-rata yang dibutuhkan web service untuk memberikan response ketika diakses 1000 user adalah 6198ms (minimal 17ms dan maksimal 10017ms), artinya web service memiliki peforma yang baik pada beban yang tinggi. Metode Extreme Programming dipilih untuk pengembangan web service pada penelitian ini. Metode ini terdiri dari empat tahapan, yaitu planning (analisa apa saja yang dibutuhkan sistem), design (visualisasi dengan Use Case diagram), pengkodingan (menggunakan FastAPI Framework), dan yang terakhir adalah pengujian (menggunakan BlackBox dan JMeter untuk pengujian fungsi dan keamanan). Kesederhanaan dari metode ini dapat mendukung tercapainya hasil yang diinginkan yaitu sebuah layanan back-end berupa web service, yang bisa digunakan oleh sistem informasi akademik multipaltform untuk bertukar data dengan mudah dan tepat sehingga dapat terhindar dari kesalahan terutama ketidakkonsistenan dalam menyajikan data akademik.
subject: Artikel
  topic: section
subject: Sistem Akademik
  topic: keywords
subject: Multiplatform
  topic: keywords
subject: Web Service
  topic: keywords
subject: FastAPI
  topic: keywords
creator: Aprilyani Nur Safitri
creator: Imanuel Harkespan
rights: Hak Cipta (c) 2024 Aprilyani Nur Safitri, Imanuel Harkespan https://creativecommons.org/licenses/by-sa/4.0
date: 2024-10-30
publication date: 2024-10-30
starting page: 149
ending page: 157
doi: 10.21063/jtif.2024.V12.2.149-157

SISTEM PENYIRAMAN OTOMATIS PADA PEMBIBITAN PRE-NURSERY KELAPA SAWIT BERBASIS INTERNET OF THINGS
type: item
description: Penerapan teknologi otomatisasi pada sektor pertanian merupakan solusi yang sangat efektif untuk meningkatkan efisiensi dan produktivita pembibitan, terutama pada pembibitan kelapa sawit. CV Pangean Raya TBS merupakan sebuah usaha pembibitan kelapa sawit di Kabupaten Solok Selatan. CV Pangean Raya TBS sedang menghadapi tantangan dalam proses penyiraman bibit kelapa sawit. Metode penyiraman yang dilakukan masih secara manual. Metode manual tersebut menyebabkan pemborosan waktu, tenaga, dan air. Penyiraman manual sering mengakibatkan ketidakmerataan asupan air yang dapat mempengaruhi kualitas bibit kelapa sawit. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem penyiraman otomatis berbasis Internet of Things (IoT) yang efisien menggunakan sensor kelembaban tanah, modul ESP32, dan RTC. Sistem ini dirancang untuk memantau kondisi kelembaban tanah secara real-time dan mengatur penyiraman secara otomatis. Penyiraman otomatis dilakukan berdasarkan nilai dari kelembaban yang didapatkan oleh sensor. Penyiraman juga dapat diatur secara manual melalui smartphone ketika dibutuhkan pada saat hujan turun, sehingga tidak terjadi pemborosan air dan kelebihan air pada bibit kelapa sawit. Sistem ini dapat membantu pemilik kebun dalam mengoptimalkan penggunaan air, meningkatkan produktivitas bibit kelapa sawit, dan mengurangi ketergantungan pada tenaga kerja manual. Hasil penelitian menunjukkan bahwa sistem penyiraman ini dapat berjalan secara otomatis berdasarkan data kelembaban yang diterima, sehingga efektif dalam menghemat sumber daya, meningkatkan produktivitas, dan memberikan kontrol yang lebih baik terhadap kondisi tanaman.
subject: Artikel
  topic: section
subject: Automatic
  topic: keywords
subject: Palm Oil
  topic: keywords
subject: IoT
  topic: keywords
subject: Humidity
  topic: keywords
creator: Dian Eka Putra
creator: Edwar Rosman
creator: Katrina Flomina G
creator: Miftahul Hasanah
creator: Riyan Ikhbal Salam
rights: Hak Cipta (c) 2024 Dian Eka Putra, Edwar Rosman, Katrina Flomina G, Miftahul Hasanah, Riyan Ikhbal Salam https://creativecommons.org/licenses/by-sa/4.0
date: 2024-10-30
publication date: 2024-10-30
starting page: 131
ending page: 138
doi: 10.21063/jtif.2024.V12.2.131-138

PERANCANGAN SISTEM INFORMASI ANALIS BREAK EVEN POINT DAN STOK PADA BUDIDAYA AYAM POTONG BERBASIS WEB
type: item
description: Although broiler chicken farming offers many benefits, there are also risks of losses, especially when production costs are not accurately recorded, leading to inaccurate per-unit pricing that can harm farmers. To assist farmers in accurately determining the Break Even Point (BEP) price for each chicken, a web-based cost and stock management information system for broiler farming has been developed. To provide a clear and sequential software lifecycle approach, this system was built using the waterfall method, which includes the stages of requirements analysis, design specifications, coding, testing, and maintenance. Each stage produces measurable outcomes before proceeding to the next. The development results indicate that the system successfully records the total production costs, including detailed costs for feed, medicine, operational expenses, and chicken stock. By using the formula BEP = total production cost/number of live chickens, the system achieves accurate pricing for broiler chickens. Based on these findings, future research is suggested to improve the user interface for greater appeal, optimize system accessibility on mobile devices, and integrate this system with other systems.
subject: Artikel
  topic: section
subject: Ayam Potong
  topic: keywords
subject: BEP
  topic: keywords
subject: Biaya
  topic: keywords
subject: Budidaya
  topic: keywords
subject: Sistem Informasi
  topic: keywords
subject: Stok
  topic: keywords
creator: Khoiril Afif
creator: Yudi Kristyawan
creator: Slamet Kacung
rights: Hak Cipta (c) 2024 khoiril afif, Yudi Kristyawan, Slamet Kacung https://creativecommons.org/licenses/by-sa/4.0
date: 2024-11-11
publication date: 2024-11-11
starting page: 111
ending page: 119
doi: 10.21063/jtif.2024.V12.2.111-119

INOVASI E-COMMERCE UNTUK OPTIMALISASI PROSES KONSUMEN, PRODUKSI, DAN PEMASARAN BAGI PELAKU UMKM
type: item
description: Teknologi e-commerce memungkinkan transaksi online yang efisien, memberikan konsumen pengalaman pembelian yang nyaman dan efisien. Dalam hal produksi, sistem informasi e-commerce dapat diintegrasikan dengan manajemen produksi, memungkinkan pemantauan proses produksi sehingga mengoptimalkan efisiensi produksi dan mengurangi risiko kekurangan stok. Teknologi e-commerce juga membuka peluang strategi pemasaran yang lebih canggih, karena pelaku UMKM dapat memanfaatkan analisis data konsumen, meningkatkan daya tarik konsumen dan pemesanan serta penjualan. Teknologi e-commerce memfasilitasi interaksi langsung antara konsumen, membina hubungan yang lebih dekat dan meningkatkan pengalaman konsumen. Perkembangan teknologi e-commerce secara signifikan meningkatkan efektivitas dan efisiensi pelaku UMKM khusus di sektor ayam goreng, memungkinkan untuk bersaing di era bisnis digital. Tujuan penelitian ini adalah mengembangkan sistem informasi E-Commerce di sentra industri ayam goreng “Maju Makmur” Kalasan yang mengelola pelaku UMKM ayam goreng. Metode penelitian ini adalah model prototype. Model ini dimulai dari pengumpulan data, desain sistem dan pengujian. Tahapan model pengembangan prototyping terdiri atas: komunikasi, perencanaan cepat, pemodelan cepat, kontruksi, dan penyerahan. Hasil penelitian ini adalah sebuah sistem berbasis web untuk mengoptimalkan proses konsumen, produksi, dan pemasaran agar terjadi peningkatan efisiensi operasional dan akses pasar melalui platform online.
subject: Artikel
  topic: section
subject: E-commerce
  topic: keywords
subject: Business Optimization
  topic: keywords
subject: Consumer Management
  topic: keywords
subject: Production Efficiency
  topic: keywords
subject: Digital Marketing
  topic: keywords
creator: Zaidir Zaidir
creator: V Wiratna Sujarweni
creator: Erizal Erizal
rights: Hak Cipta (c) 2024 Zaidir Zaidir, V Wiratna Sujarweni, Erizal Erizal https://creativecommons.org/licenses/by-sa/4.0
date: 2024-10-30
publication date: 2024-10-30
starting page: 120
ending page: 130
doi: 10.21063/jtif.2024.V12.2.120-130

PERANCANGAN APLIKASI PERHITUNGAN BEBAN KERJA DOSEN TERINTEGRASI DENGAN PENDEKATAN WATERFALL
type: item
description: Digital transformation in higher education emphasizes the importance of information technology in enhancing management efficiency, including the management of lecturers' workloads. This study aims to design a Full-Time Equivalent Teaching Load (EWMP) calculation system integrated with the Integrated Resource Information System (SISTER), implemented by the Ministry of Education, Culture, Research, and Technology (KEMDIKBUDRISTEK). The application was developed using the Waterfall methodology and leverages the SISTER Application Programming Interface (API) to automate the collection of lecturer activity data at Universitas Dian Nuswantoro Semarang (UDINUS). By integrating the workload calculation application into the internal management system, this solution streamlines data recording, reduces manual errors, and enhances accuracy in the evaluation of lecturer performance. The test results indicate that the application successfully synchronizes data with SISTER in an accurate and real-time manner, supporting more effective workload management for lecturers. Additionally, the system provides reports and analyses of lecturer workloads, facilitating resource planning and allocation. This application is expected to contribute to a more transparent, accurate, and quality-driven human resource management process in higher education.
subject: Artikel
  topic: section
subject: Academic
  topic: keywords
subject: API
  topic: keywords
subject: Integration
  topic: keywords
subject: SISTER-API
  topic: keywords
subject: Waterfall
  topic: keywords
creator: Danny Oka Ratmana
creator: Muhammad Syaifur Rohman
creator: Fahri Firdausillah
creator: Galuh Wilujeng Saraswati
rights: Hak Cipta (c) 2024 Danny Oka Ratmana, Muhammad Syaifur Rohman, Fahri Firdausillah, Galuh Wilujeng Saraswati https://creativecommons.org/licenses/by-sa/4.0
date: 2024-10-30
publication date: 2024-10-30
starting page: 139
ending page: 148
doi: 10.21063/jtif.2024.V12.2.139-148

PERANCANGAN PROTOTIPE APLIKASI PERUMAHAN TAMAN KENARI SENSOR MONITOR MENGGUNAKAN METODE AGILE
type: item
description: Perumahan Taman Kenari merupakan komplek perumahan yang terletak di Kabupaten Bogor, Jawa Barat. Perumahan ini relatif sepi pada siang hari, sore hari, dan malam hari yang dapat menyebabkan masalah pada segi keamanan rumah. Salah satu permasalahan yang dihadapi oleh penghuni rumah di Perumahan Taman Kenari adalah kurangnya pemantauan dan pengawasan yang efektif terhadap keamanan rumah mereka. Untuk mengatasi masalah ini, penulis merancang sebuah prototipe aplikasi bernama Taman Kenari Sensor Monitor menggunakan metode Agile. Tujuan penelitian ini adalah untuk merancang prototipe aplikasi Taman Kenari Sensor Monitor sebagai solusi yang efektif dalam meningkatkan keamanan dan efisiensi pengawasan rumah di Perumahan Taman Kenari. Melalui pendekatan prototipe ini, aplikasi Taman Kenari Sensor Monitor dapat direpresentasikan secara visual dalam bentuk mockup yang sesuai dengan kebutuhan pengguna, serta efisien dalam hal fungsionalitas dan estetika. Prototipe ini dirancang menggunakan pemodelan UML (Unified Modeling Language) dan diimplementasikan dalam bentuk mockup yang dibuat di aplikasi Figma. Pengujian aplikasi dilakukan dengan metode Blackbox untuk menguji fungsionalitas aplikasi secara keseluruhan. Penelitian ini memberikan solusi untuk mengatasi permasalahan keamanan rumah di Perumahan Taman Kenari
subject: Artikel
  topic: section
subject: metode agile
  topic: keywords
subject: metode blackbox
  topic: keywords
subject: keamanan rumah
  topic: keywords
subject: prototipe
  topic: keywords
subject: UML (Unified Modeling Language)
  topic: keywords
creator: Ichramsyah Abdurrachman
creator: Diki Gita Purnama
rights: Hak Cipta (c) 2024 Ichramsyah Abdurrachman Universitas Paramadina, Diki https://creativecommons.org/licenses/by-sa/4.0
date: 2024-10-30
publication date: 2024-10-30
starting page: 84
ending page: 91
doi: 10.21063/jtif.2024.V12.2.84-91

IMPLEMENTASI FUZZY TSUKAMOTO DALAM SISTEM PREDIKSI PANEN PADI DI KABUPATEN INDRAMAYU
type: item
description: Upaya strategis untuk menjaga produksi beras yang merupakan makanan pokok masyarakat Indonesia harus terus dilakukan, salah satunya menjaga produksi pada daerah penghasil beras seperti Kabupaten Indramayu adalah langkah yang harus diutamakan. Mengetahui prediksi hasil panen padi yang akan datang dijadikan usaha yang tepat dilakukan. Logika fuzzy tsukamoto merupakan metode yang dapat dijadikan perhitungan untuk melakukan prediksi, pemilihan fuzzy tsukamoto dikarenakan kemampuannya dalam memprediksi dengan faktor-faktor yang memiliki ketidakpastian seperti curah hujan, selain itu luas lahan dan hasil panen juga dapat dijadikan variabel untuk mendapatkan prediksi melalui fuzzy tsukamoto. Penelitian ini dilakukan untuk melakukan implementasi fuzzy tsukamoto untuk prediksi hasil panen padi, dimana hasil proses logika fuzzy tsukamoto yang telah dilakukan menghasilkan enam rules pada tahap inferensi pada kategori panen bertambah atau berkurang, yang dijadikan dasar proses defuzzifikasi untuk mencari nilai output hasil panen. Hasil perhitungan kemudian diterapkan dalam sebuah sistem berbasis website menggunakan framework laravel dan DBMS MySql sehingga dapat digunakan untuk melakukan prediksi hasil panen padi. Berdasarkan proses prediksi yang dilakukan melalui sistem berbasis metode fuzzy tsukamoto, dari 31 Kecamatan terdapat 16 Kecamatan yang berpotensi mengalami penurunan, dan 15 Kecamatan mengalami peningkatan produksi panen padi di Kabupaten Indramayu.
subject: Artikel
  topic: section
subject: Fuzzy Tsukamoto
  topic: keywords
subject: Prediksi
  topic: keywords
subject: Panen
  topic: keywords
subject: Padi
  topic: keywords
subject: Indramayu
  topic: keywords
creator: Riyan Farismana
creator: Debi Nabilah Sholihah
creator: Dian Pramadhana
creator: Sonty Lena
rights: Hak Cipta (c) 2024 riyan farismana, Debi Nabilah Sholihah, Dian Pramadhana, Sonty Lena https://creativecommons.org/licenses/by-sa/4.0
date: 2024-10-30
publication date: 2024-10-30
starting page: 100
ending page: 110
doi: 10.21063/jtif.2024.V12.2.100-110

IMPLEMENTASI CHATBOT YANG TERINTEGRASI LAYANAN KEPOLISIAN DALAM PEMBUATAN SIM
type: item
description: Studi ini menyarankan penggunaan pemrosesan bahasa alami (NLP) untuk mengintegrasikan chatbot dengan layanan kepolisian selama pengiriman izin pengemudi (SIM). Layanan polisi sekarang dapat memberikan informasi kepada publik lebih cepat berkat penggunaan teknologi chatbot, termasuk rencana perjalanan untuk kartu SIM dan instruksi perpanjangan SIM. Studi ini menggunakan metodologi penelitian pengembangan, menggunakan teknik kuantitatif dan kualitatif untuk mengumpulkan data melalui pengamatan, wawancara, dan dokumentasi. Dengan potensi untuk berdampak signifikan pada penggunaan teknologi untuk meningkatkan layanan publik, integrasi chatbot dengan layanan kepolisian dalam proses pengiriman kartu SIM adalah langkah penting menuju peningkatan efektivitas dan aksesibilitas layanan publik.
subject: Artikel
  topic: section
subject: pemrosesan bahasa alami
  topic: keywords
subject: (NLP)
  topic: keywords
subject: izin mengemudi
  topic: keywords
subject: (SIM)
  topic: keywords
subject: chatbot
  topic: keywords
subject: layanan polisi
  topic: keywords
subject: efisiensi layanan
  topic: keywords
creator: Ekananda Naufal Allaam
creator: Eri Zuliarso
rights: Hak Cipta (c) 2024 Ekananda Naufal Allaam Eka, Eri Zuliarso https://creativecommons.org/licenses/by-sa/4.0
date: 2024-10-30
publication date: 2024-10-30
starting page: 77
ending page: 83
doi: 10.21063/jtif.2024.V12.2.77-83

IMPLEMENTASI QUESTION ANSWERING SYSTEM TAFSIR AL-AZHAR MENGGUNAKAN LANGCHAIN DAN LARGE LANGUAGE MODEL BERBASIS CHATBOT TELEGRAM
type: item
description: Tafsir merupakan sebuah gerbang utama bagi seorang muslim untuk mempelajari dan memahami isi kandungan dari ayat-ayat yang terdapat di dalam Al-Quran, salah satu contohnya adalah Tafsir Al-Azhar. Tafsir Al-Azhar merupakan tafsir karya Profesor Dr.Hamka yang memperlihatkan bagaimana cara Dr. Hamka menghubungkan antara sejarah islam modern dengan studi Al-Quran. Tafsir Al-Azhar mempunyai halaman yang sangat banyak, sehingga membutuhkan kerja yang lebih ketika kita ingin mencari suatu informasi dari tafsir tersebut. Penelitian ini bertujuan untuk membuat sebuah sistem yang mampu menerima pertanyaan seputar Tafsir Al-Azhar dalam bentuk bahasa alami, serta menjawab pertanyaan tersebut dengan kata-kata yang mudah dipahami oleh pengguna. Adapun teknologi yang akan digunakan pada penelitian ini seperti Langchain dan Large Language Model, untuk pengimplementasiannya menggunakan chatbot telegram, karena telegram merupakan aplikasi yang sudah terkenal dan sudah banyak digunakan oleh banyak orang, dan juga telegram mempunyai interface yang ramah, sehingga tidak membuat pengguna kebingungan ketika menggunakannya. Sistem Question Answering ini diuji menggunakan UAT dan framework DeepEval, hasil dari pengujian UAT berupa skor akurasi sebesar 83.71%, sedangkan hasil dari pengujian menggunakan framework DeepEval, berupa skor hallucination sebesar 41 %, contextual precision sebesar 90 %, contextual recall sebesar 81 %, dan contextual relevancy 79 %.
subject: Artikel
  topic: section
subject: Question Answering System
  topic: keywords
subject: Langchain
  topic: keywords
subject: Large Language Model
  topic: keywords
subject: Tafsir Al-Quran
  topic: keywords
subject: Chatbot
  topic: keywords
creator: Aji Bayu Permadi
creator: Nazruddin Safaat H
creator: Lestari Handayani
creator: Yusra
rights: Hak Cipta (c) 2024 Aji Bayu Permadi, Nazruddin Safaat H, Lestari Handayani, Yusra https://creativecommons.org/licenses/by-sa/4.0
date: 2024-04-29
publication date: 2024-04-29
starting page: 62
ending page: 69
doi: 10.21063/jtif.2024.V12.1.62-69

SIMULASI MONTE CARLO UNTUK ESTIMASI PENGADAAN ATK (STUDI KASUS DI INSTITUT TEKNOLOGI PADANG)
type: item
description: Alat Tulis Kantor (ATK) merupakan salah satu kebutuhan operasional di Institut Teknologi Padang (ITP). Pengadaan ATK dilakukan dan 2 kali dalam satu tahun dengan pengajuan anggaran per tahunnya. Pengelolaan ATK dilakukan secara manual mulai dari permintaan hingga sistem transaksi. Kondisi saat ini mengakibatkan perencanaan pengadaan tidak terukur, sehingga terjadi kekurangan beberapa item barang tertentu ditengah periode atau penumpukan beberapa item barang tententu di akhir tahun. Bagaimana membantu bagian pengadaan untuk menentukan estimasi pengadaan, sehingga dapat menyediakan barang secara optimal serta penggunaan anggaran yang lebih efektif dan efisien untuk periode yang akan datang. Pengolahan dilakukan terhadap data transaksi ATK dengan menggunakan metode simulasi Monte Carlo. Tahapan simulasi dengan menentukan probabilitas, menghitung distribusi kumulatif, menetapkan interval dari angka acak, bentuk bilangan acak dan membuat simulasi. Hasil simulasi yang dilakukan dapat menentukan estimasi jumlah pengadaan barang serta dapat menekan biaya pengadaan sebesar 25,6% jika dibandingkan dengan pengadaan pada periode semester genap sebelumnya.
subject: Artikel
  topic: section
subject: Simulation
  topic: keywords
subject: Monte Carlo
  topic: keywords
subject: ATK
  topic: keywords
subject: ITP
  topic: keywords
creator: Hamdi Habdillah
creator: Jufriadif Na’am
rights: Hak Cipta (c) 2024 Hamdi Habdillah, Jufriadif Na’am https://creativecommons.org/licenses/by-sa/4.0
date: 2024-04-29
publication date: 2024-04-29
starting page: 56
ending page: 61
doi: 10.21063/jtif.2024.V12.1.56-61

Topic Analysis Video Debat Jelang Pemilu Presiden dan Wakil Presiden Tahun 2024
type: item
description: Mendekati pemilihan umum presiden (PEMILU) pada tahun 2024 banyak diadakan debat calon presiden dan wakil presiden sebagai sarana menyampaikan gagasan-gagasan. Untuk dapat menemukan topik dari gagasan-gagasan yang ada dalam debat bakal calon presiden dan wakil presiden yang ditayangkan dalam video debat, penelitian ini melakukan topic analisis terhadap video debat calon presiden dan wakil presiden dengan menggunakan metode Latent Dirichlet Allocation (LDA) dan K-means Clustering, untuk masing-masing pasangan calon: A (Anies-Muhaimin), B (Prabowo-Gibran)), dan C (Ganjar-Mahfud). Hasilnya dengan menggunakan K-Means Clustering topik yang didapatkan lebih banyak, beragam, dan lebih merata topiknya untuk setiap paslon. Sedangkan topik LDA mendapatkan topik lebih sedikit dan lebih berhasil mendapatkan topik untuk paslon A. Berdasarkan standar yang telah dibuat, efektivitas pencarian topik berbeda-beda keberhasilannya disetiap dataset. Pada dataset 1 dengan model LDA didapati gagasan pasangan calon untuk paslon A 60%, B 25%, dan C 0%. Pada dataset 2 dengan model K-Means didapati gagasan pasangan calon untuk paslon A 37.04%, B 25%, dan C 17.24%. Pada dataset 2 dengan model LDA didapati gagasan pasangan calon untuk paslon A 100%, B 40%, dan C 0%. Pada dataset 2 dengan model K-Means didapati gagasan pasangan calon untuk paslon A 35.71%, B 14.29%, dan C 28.57%.
subject: Artikel
  topic: section
subject: Topic Modelling
  topic: keywords
subject: Latent Dirichlet Allocation
  topic: keywords
subject: K-Means
  topic: keywords
creator: Ivana Valentina
creator: Aziz Mu’min
creator: Devion Tanrico
creator: Oscar Karnalim
rights: Hak Cipta (c) 2024 Ivana Valentina, Aziz Mu’min, Devion Tanrico, Oscar Karnalim https://creativecommons.org/licenses/by-sa/4.0
date: 2024-04-29
publication date: 2024-04-29
starting page: 29
ending page: 35
doi: 10.21063/jtif.2024.V12.1.29-35