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Journal : Jurnal Transformatika

Analisis Loyalitas Customer Perusahaan Konveksi dengan Model RFM dan Algoritma k-Means Gerian, Matthew; Nataliani, Yessica
Jurnal Transformatika Vol 21, No 1 (2023): July 2023
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v21i2.7248

Abstract

Strategi yang baik diperlukan suatu perusahaan dalam menjalankan usahanya. CV. Karunia Jaya merupakan salah satu perusahaan yang bergerak dalam bidang konveksi yanag menjual pakaian bayi. Dalam pelayanan terhadap customer CV. Karunia Jaya belum menerapkan strategi Customer Relationship Management (CRM). Untuk mengetahui loyalitas customer maka perlu dilakukan segmentasi pelanggan terhadap customer. Penelitian ini menggunakan data transaksi dari tahun 2021-2022. Algoritma k-means digunakan dalam penentuan cluster berdasarkan model Recency, Frequency, dan Moneetary (RFM), dibantu dengan tools Weka 3.8.6. Metode elbow digunakan untuk mencari jumlah cluster terbaik dari sekelompok data. Hasil dari penelitian ini yaitu terdapat 27 customer yang terbagi dalam tiga cluster, 21 customer potensi rendah, tiga customer potensi sedang, dan tiga customer potensi tinggi. Perusahaan dapat memberikan layanan yang berbeda terhadap setiap kelompok customer, sehingga hal tersebut dapat menguntungkan perusahaan.
Clustering Performa Pemain Basket Berdasarkan Posisi dan Statistik Pemain Menggunakan Metode Fuzzy c-Means Gregorry, Febrianus; Nataliani, Yessica
Jurnal Transformatika Vol. 20 No. 1 (2022): July 2022
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v20i1.5137

Abstract

Satya Wacana Saints Salatiga is one of the professional teams that compete in Indonesian Basketball League (IBL). Player evaluation has been done as an effort to maintain the quality and performance of all players which can be used as team records. They can also make a couple of improvements within the team for the next season. Classifying the players performance by using the fuzzy c-means algorithm is the aim of this research. Player performance is determined based on five kinds of player statistical criteria, namely points, assists, blocks, rebounds, and steals from each position. The assessment carried out in this study is using weighting criteria for each position. The grouping by weighting aims to get the highest to the lowest scores from each player so that they can be grouped into three performance groups; good, moderate, and poor performance. The results of the fuzzy c-means grouping of 15 players of the Satya Wacana Saints Salatiga team with weighting obtained three players with good performance, five players with moderate performance, and seven players with poor performance. Meanwhile, the results of the fuzzy c-means grouping without weighting obtained five players with good performance, three players with moderate performance, and seven players with poor performance. Both grouping results are compared with the actual performance data. The result of the comparison was found that the grouping with weighting resulted in an accuracy rate of 100% and the grouping without weighting resulted in an accuracy rate of 86.67%. Grouping with weighting on different statistical values for each player position has an effect on player performance. Each player position has different strengths in scoring points, assists, rebounds, steals, block shoots, and field goals.