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All Journal PROSIDING SEMINAR NASIONAL Jurnal Keperawatan Anak Jurnal Pengabdian Masyarakat Kesehatan Jurnal Perawat Indonesia Indonesian Journal of Nursing Research (IJNR) Journal of Information Systems and Informatics Healthcare Nursing Journal Jurnal Pengabdian kepada Masyarakat Nusantara Journal of Holistics and Health Sciences (JHHS) Joong-Ki : Jurnal Pengabdian Masyarakat Indonesian Journal of Midwifery (IJM) Indonesian Journal of Community Empowerment (IJCE) Pro Health Jurnal Ilmiah Kesehatan Jurnal Pengabdian Perawat Jurnal Anestesi: Jurnal Ilmu Kesehatan dan Kedokteran Jurnal Keperawatan Berbudaya Sehat Joong-Ki Joong-Ki
Fiktina Vifri Ismiriyam
Universitas Ngudi Waluyo
Religion Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Health Professions Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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Journal : Journal of Information Systems and Informatics

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Expert System for The Diagnosis of Depression in Students Using Certainty Factor Method: A Case Study of Ngudi Waluyo University Purnamasari, Yessy Sabilla; Mujiyono, Sri; Ismiriyam, Fiktina Vifri
Journal of Information System and Informatics Vol 7 No 1 (2025): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i1.950

Abstract

Depression is a growing mental health concern among university students, often fueled by academic pressure, social demands, and personal stress. This study presents the development of an expert system using the Certainty Factor (CF) method to diagnose depression specifically among students at Ngudi Waluyo University. The system categorizes depression into mild, moderate, and severe levels based on 12 validated symptom statements and expert-defined diagnostic rules. Implemented with PHP, JavaScript, and CSS, the system offers a user-friendly, accessible, and anonymous platform for self-assessment. Testing yielded an accuracy rate of up to 79% in diagnosing depression severity and a 71.7% user satisfaction rate based on a User Acceptance Test (UAT) involving 32 students. Results demonstrate that the system can effectively support early detection and mental health awareness within academic environments. Despite some limitations in UI and feedback depth, the expert system shows strong potential for broader application and further enhancement.
Co-Authors Ade Isnaini Ade Isnaini Fadillah Alivia Desi Rahmawati Ana Pujiastuti, Ana Anggun Trisnasari Desti Endang Kartikasari Dinda Hapsari Ela Suryani Endang Susilowati Joyo Minardo Kartika Dian Pertiwi Kartika Yuni Purwanti Khilvy Salsabila Az-Zahra Luluk Sri Nurhaliza Maksum Maksum Moneca Diah Listiyaningsih MUKHAMAD MUSTA'IN Mukhamad Mustain Mukhamad Musta’in Mukhamad Musta’in Novelia Rahmaningtyas Puji Purwaningsih Purnamasari, Yessy Sabilla Putri, Risma Aliviani Siti Haryani SRI LESTARI Sri Lestari Sri Mujiyono Suwanti Tina Mawar Dika Tina Mawardika Ulvi Nabila Azzahra Umi Aniroh, Umi Ummu Muntamah Veftisia, Vistra wulansari Wulansari