TINJAUAN PUSTAKA SISTEMATIS: PENERAPAN DATA MINING TEKNIK CLUSTERING ALGORITMA K-MEANS
DOI:
https://doi.org/10.21063/jtif.2022.V10.2.52-61Kata Kunci:
data mining, clustering, K-Means, systematic literature reviewAbstrak
Data Mining adalah metode untuk menganalisis pola dan karakteristik di masa depan serta untuk mengumpulkan informasi tak terduga yang belum pernah terlihat sebelumnya dari database yang besar. Dalam data mining, clustering adalah salah satu teknik yang berguna untuk analisis data. Salah satu algoritma data mining adalah algoritma K-Means yang merupakan teknik clustering berdasarkan pembagian jarak. Tujuan yang ingin dicapai dalam paper ini yakni menganalisis teknik clustering menggunakan algoritma K-Means dalam data mining dengan melakukan review secara mendalam dan mengevaluasi penelusuran melalui literatur terpilih berdasarkan kriteria tertentu dan studi yang dipilih akan diproses untuk menjawab pertanyaan penelitian. Tinjauan Pustaka Sistematis (Systematic Literature Review/SLR) merupakan sebuah metode penelitian yang bertujuan untuk mengidentifikasi dan mengevaluasi hasil penelitian dengan teknik terbaik berdasarkan prosedur yang spesifik dari hasil perbandingan. Berdasarkan pemilihan literatur publikasi jurnal, Pattern Recognition, Knowledge-Based System, Applied Soft Computing dan IEEE Access dapat menjadi rujukan utama terkait algoritma K-Means. Metode atau teori perhitungan jarak yang sering digunakan terkait algoritma K-Means yakni Euclidean Distance, Elbow Criterion, dan Lloyd Algorithm. Hasil perbandingan metode menunjukkan bahwa Euclidean Distance memiliki keunggulan perhitungan jarak yang lebih baik.
Kata Kunci—data mining, clustering, K-Means, tinjauan pustaka sistematis.
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