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All Journal Syntax Jurnal Informatika Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Pilar Nusa Mandiri Informatics for Educators and Professional : Journal of Informatics Information Management For Educators And Professionals (IMBI) Jurnal Teknik Informatika STMIK Antar Bangsa JITK (Jurnal Ilmu Pengetahuan dan Komputer) INTI Nusa Mandiri Systematics JATI (Jurnal Mahasiswa Teknik Informatika) Reputasi: Jurnal Rekayasa Perangkat Lunak JUSTIN (Jurnal Sistem dan Teknologi Informasi) Journal of Artificial Intelligence and Engineering Applications (JAIEA)
Esty Purwaningsih
Universitas Bina Sarana Informatika
Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Library & Information Science Other

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Penerapan Algoritma C4.5 Dalam Pengukuran Tingkat Kepuasan Pelanggan Terhadap Layanan Resto Cepat Saji Esty Purwaningsih; Ela Nurelasari
Reputasi: Jurnal Rekayasa Perangkat Lunak Vol. 3 No. 1 (2022): Mei 2022
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/reputasi.v3i1.1199

Abstract

Tingkat kepuasan pelanggan terdapat tingkat kepentingan, kinerja dan hasil yang dirasakan memberikan hasil yang sama atau bahkan melampaui dari harapan pelanggan. Sedangkan ketidakpuasan terjadi apabila hasil yang diperoleh tidak memenuhi harapan yang diinginkan pelanggan. Tantangan tersulit bagi setiap pelaku industri kuliner agar para pelanggannya tetap setia. Sehingga untuk memenangkan persaingan maka perlu meningkatkan kepuasan pelanggan. Ada 5 (lima) dimensi dalam mengukur kualitas pelayanan berdasarkan pada nilai harapan dengan nilai kinerja, diantaranya tangible, reliability, responsiveness assurance, dan emphaty. Penilaian kepuasan pelanggan yang diambil berdasarkan kuesioner yang telah diisi oleh pelanggan. Kemudian diolah kedalam algoritma C4.5, dimana algoritma tersebut merupakan model klasifikasi yang menghasilkan pohon keputusan yang sangat mudah dimengerti, mudah untuk dibangun, serta membutuhkan data percobaan yang lebih sedikit dibandingkan algoritma klasifikasi lainnya. Penelitian ini bertujuan untuk mengetahui seberapa tinggi tingkat kepuasan pelanggan dan membantu pihak resto dalam meningkatkan pelayanan. Dari hasil pengolahan data dengan menggunakan algoritma C4.5 didapatkan akurasi sebesar 95,36%.
Analysis of JKN Mobile User Satisfaction using SVM and KNN Methods Through PSO Optimization Esty Purwaningsih; Ela Nurelasari
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2345

Abstract

This study was conducted to evaluate the service quality of the JKN Mobile application developed by the Health Social Security Administering Agency (BPJS Kesehatan) as a means of facilitating participants in accessing health services. Although the application provides convenience for users, there are still various complaints indicating that the service is not running optimally. Therefore, this study aims to analyze the positive and negative sentiments of JKN Mobile application users by comparing the Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) algorithms based on Particle Swarm Optimization (PSO). The research method was carried out by processing user review data using sentiment classification techniques. The test results showed that the SVM algorithm obtained an accuracy of 85.02% with an AUC value of 0.815, while the PSO-based SVM increased to 86.71% with an AUC of 0.831. The KNN algorithm obtained an accuracy of 39.54% with an AUC of 0.500, while the PSO-based KNN increased to 87.05% with an AUC of 0.736. The results of the study prove that the implementation of PSO is able to improve the accuracy performance of both algorithms.
Co-Authors Aditia Darmawan Algani, Ahmad Diah Ayu Maulida Wati Diah Puspitasari Ela Nurela Sari Ela Nurela Sari Ela Nurelasari Ela Nurelasari Junian Tamba, Hiskia Magdalena Gire Namang Ridwansyah Ridwansyah Santoso Setiawan