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All Journal Journal of Artificial Intelligence and Innovative Applications (JOAIIA) Abdi Masya FADZAT Jurnal Ekonomi Syariah Biner : Jurnal Ilmu Komputer, Teknik dan Multimedia OKTAL : Jurnal Ilmu Komputer dan Sains SURAKARTA ABDIMAS JOURNAL WISDOM : Jurnal Pengabdian Kepada Masyarakat Wisdom Jurnal Sains Materi Indonesia
Savitri
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Perancangan Aplikasi Data Mining Berbasis Web Menggunakan Algoritma C4.5 untuk Memprediksi Tingkat Kepuasan Pelanggan Muhamad Fathan; Savitri
Journal of Artificial Intelligence and Innovative Applications (JOAIIA) Vol. 7 No. 1 (2026): February
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/joaiia.v7i1.56622

Abstract

The rapid development of information technology encourages various industries to utilize the data they possess as a basis for strategic decision-making. CV. Triqua Global Mandiri is a company engaged in the sale of bottled water, where customer satisfaction is a key indicator in assessing service quality and business success. However, the company has not yet had a system capable of automatically analyzing customer data to predict satisfaction levels. Therefore, this study aims to design a web-based data mining application using the C4.5 algorithm to predict customer satisfaction levels based on several parameters such as service, communication, price, and quality. The method used in this study is the C4.5 algorithm, a classification method in data mining that forms a decision tree based on entropy values and information gain from each attribute. The research process includes data collection, data cleaning, decision model formation using training data, and model testing using testing data to measure the system's accuracy. Based on the testing conducted, the system was able to provide predictions with an accuracy rate of 80%, making it a valuable tool for the management of CV. Triqua Global Mandiri in improving service quality and marketing strategies. By using this application, the company can gain objective predictive information to improve services and maximize customer satisfaction more efficiently and effectively.
Co-Authors Abdul Malik Adil Azrial Akbar Amin Astuti Bahfie Birawidha Dapot TH Sianturi Dwi Gunawan Dwi Yanti Elvrida Rosa Fairuz Dzulfiqar, Muhammad Faris Akbar Giyono Hifi Rini Puspita IRWANTO Juni Trisnowati2 Karo Karo Kristiawan , Y Yulianto Muhamad Fathan Muhammad Kamal Muda Mukti, Bayu Mutiarawati, Raihana Puput Isnani singgih Prabowo Wijoyo