Implementasi data mining menggunakan algoritma C4.5 untuk prediksi kepuasan pelanggan Restoran Kwetiau Ateng Cabang S.Parman

Robby, Robby (2020) Implementasi data mining menggunakan algoritma C4.5 untuk prediksi kepuasan pelanggan Restoran Kwetiau Ateng Cabang S.Parman. Bachelor thesis, Universitas Pelita Harapan.

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Abstract

Bagi kegiatan usaha restoran hidangan makanan maupun minuman perlu melakukan evaluasi terhadap feedback yang diberikan pembeli agar dapat bersaing dengan kompetitor. Penelitian akan dilakukan terhadap data yang dikumpulkan pada restoran Kwetiau Ateng Cabang S.parman agar dapat mengetahui dan menganalisis faktor - faktor yang dapat meningkatkan kepuasan pelanggan dan juga mempertahankan loyalitas pembeli di industri bisnis makanan. Atrribut - atrribut atau variabel yang akan diuji pada penelitian ini berupa harga, fasilitas, pelayanan, loyalitas, dan kualitas. Nantinya hasil penelitian akan menujukkan keakuratan data dan membantu memberikan bantuan dalam mengambil keputusan agar dapat memperoleh keuntungan dalam bisnis. Setelah dilakukan pengujian terhadap data kuisioner dengan menggunakan algoritma C4.5 dan dengan menggunakan pengujian K-fold validation sebanyak 3 kali didapatkan bahwa pada K-Fold Validation 10 mempunyai nilai akurasi paling tinggi yakni 96, 50%, presisi 97. 84%, serta recall 98. 37%. Hal ini menujukkan bahwa algoritma C4.5 tepat digunakan untuk mengukur kepuasan pelanggan restoran./For food and beverages industry, it is necessary to evaluate the feedback of their customers in order to survive and win from other competitors. Research will be conducted based on data from Kwetiau Ateng Cabang S.Parman to find out and analyze factors that can be used to improve customer's satisfaction and maintain loyalty in food and beverages industry. Attributes or variables that will be tested in this research are price, facility, service, loyalty, and quality. This research results will be shown in the form of data's accuration and information that can be used by organization to get competitive advantage. After testing the questionnaire data using the C4.5 algorithm and by using the K-fold validation test 3 times. It was found that the K-Fold Validation 10 had the highest accuracy value of 96, 50%, precision 97.84%, and recall 98. 37%. This shows that the C4.5 algorithm is appropriate to measure restaurant customer satisfaction.

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