Perbandingan Algoritma Decision Tree dan K-Means Clustering Untuk Menentukan Penghargaan Terhadap Loyaltas Customer

Mahardika, Bagus Tri
Prastowo, Donnie Varyasetya

Journal Technology Information and Data Analytic
Vol 2 No 1 (2025): Journal Technology Information and Data Analytic (TIFDA)

PT Tangguh Buana Roda Indonesia has difficulty in retaining loyal customers due to less than optimal customer management. This research proposes the use of a data mining-based system to categorize loyal customers using the K-Means and Decision Tree methods. The evaluation shows that the combination of K-Means and Decision Tree algorithms provides a higher average accuracy of 93.7175%. Compared to using Decision Tree alone which reached 92.8525% and K-Means which was only 91.667%. With the combination of these two algorithms, it is expected to support the awarding of loyal customers and strengthen the relationship between customers and companies. The system that has been created is web-based which will facilitate strategic planning to increase customer loyalty.