Analisis Data Mining Menggunakan Algoritma K-Means Clustering Untuk Menentukan Strategi Marketing
DOI:
https://doi.org/10.22441/incomtech.v8i3.4174Kata Kunci:
Data Mining, strategi marketing, klustering, Metode K- Means, Rapid Miner, Online ShopAbstrak
Penelitian ini mencari strategi marketing yang mampu bersaing dengan kompetitor lain, karena pada era saat ini setiap perusahaan saling belomba dalam menjual produknya dengan ujung tombaknya adalah strategi marketing, masalah yang diangkat pada penelitian ini adalah menumpuknya stok sepatu yang belum terjual dan kurang diperhatikanya reseller yang memiliki potensial dalam penjualan. penelitian ini menggunakan metode K-Means, adalah metode clustering yang membagi data kedalam satu atau lebih kluster, data yang karakteristik sama dikelompokkan satu kluster yang sama dan karakteristik yang berbeda dikelompokkan kedalam kelompok yang lain. K-Means adalah metode yang cocok digunakan dengan satu tipe data dan ditunjang dengan validitas kluster yang menggunakan Davies-Bouldin Index untuk mengetahui seberapa baik proses kinerja pengklusteran. Hasil pengklusteran data untuk mendapatkan informasi reseller yang potensial, dengan menggunakan dua kluster, sedangkan untuk mendapatkan informasi tipe sepatu yang laris adalah dengan menggunakan tiga cluster. Dan pengklusteran ini menghasilkan 1 reseller yang potensial yaitu reseller Hoy, sedangkan proses mencari tipe sepatu yang laris mendaptkan 3 tipe sepatu yang terlaris yaitu Neo Adventage, Cloudfoam Swiftt, dan Bennasi. Hasil dari nilai Davies Bouldin Index yang diperoleh pada clustering pencarian reseller yang potensial adalah 0.271 dan 0.196 pada klustering pencarian tipe sepatu yang laris.
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