Prediksi Kepuasan Pelanggan dengan Algoritma Rough Set

Engla Breinda(1*), Sarjon Defit(2), Gunadi Widi Nurcahyo(3),

(1) Universitas Putra Indonesia “YPTK” Padang, Indonesia
(2) Universitas Putra Indonesia “YPTK” Padang, Indonesia
(3) Universitas Putra Indonesia “YPTK” Padang, Indonesia
(*) Corresponding Author


Bukittinggi, located in West Sumatra Province, hosts approximately 25 computer shops scattered across its various areas. Statistics reveal a proportional distribution of one computer shop per square kilometer within the city limits, intensifying the competition among these establishments. The primary objective of this study is to assess customer satisfaction using the Rough Set Method. Maintaining high levels of customer satisfaction is crucial as it often leads to repeat purchases. The Rough Set Method, renowned for its effectiveness in Knowledge Discovery in Databases (KDD), comprises five key stages: Decision System, Equivalence Class, Discernibility Matrix, Discernibility Matrix Modulo D, Reduction, and General Rule. The dataset utilized in this research originates from HBC Computer Shop in Bukittinggi, comprising records of 96 customers. Through the analysis, a total of 257 rules were generated, facilitating the identification of customer satisfaction levels. Consequently, the findings of this study can serve as valuable insights for HBC Computer Store management in devising marketing strategies to uphold customer satisfaction and effectively compete with similar businesses.

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