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All Journal Techno.Com: Jurnal Teknologi Informasi Pixel : Jurnal Ilmiah Komputer Grafis Jurnal Informatika Upgris Sistemasi: Jurnal Sistem Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA ILKOM Jurnal Ilmiah The IJICS (International Journal of Informatics and Computer Science) JURIKOM (Jurnal Riset Komputer) Jurnal Onoma: Pendidikan, Bahasa, dan Sastra JSAI (Journal Scientific and Applied Informatics) KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer (BALOK) Jurnal Teknologi Informasi Indonesia Nomos : Jurnal Penelitian Ilmu Hukum Jurnal Gemilang Informatika (GIT)
Citra Yustitya Gobel
Universitas Ichsan Gorontalo
Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice

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Klasifikasi Citra Penyakit Gigi Menggunakan Metode Gabor Filter Dan K-Nearest Neighbor Yulianty Lasena; Citra Yustitya Gobel; Fitria Anggraini
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 4 No 2 (2025)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37195/balok.v4i2.1194

Abstract

Penelitian ini bertujuan untuk mengklasifikasikan citra penyakit gigi menggunakan metode K-Nearest Neighbor(K-NN), dengan fokus pada peningkatan akurasi klasifikasi. Hasil menunjukan bahwa meskipun penerapanK-NN menghasilkan akurasi yang meningkat dengan nilai recall tertinggi , nilai precision belum tercapai tingkat optimal. Meskipun model mencapai akurasi tertinggi pada k=3 dengan 60%, nilai precision hnya 55%, menyoroti kebutuhan untuk meningktkan kinerja keseluruhan metode. Penelitian ini memberikan dasar untuk penelitian lebih lanjut dalam pengembangan teknik klasifikasi citra untuk diagnosis penyakit gigi dengan lebih akurat Kata Kunci: Klasifikasi citra, Penyakit gigi, Gabor filter, K-Nearest Neighbor, Akurasi
Expert System for Mental Health Disordes in Women and Children based on Android using the Certainty Factor Method Lasena, Marlin; Gobel, Citra Yustitya; Puspa, Misrawati Aprilyana
Sistemasi: Jurnal Sistem Informasi Vol 15, No 1 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i1.5739

Abstract

This study focuses on the limited access to mental health services in Gorontalo and the social stigma surrounding mental health disorders, which discourages women and children from seeking help. The main problem addressed in this research is the management of mental health disorders, particularly the complexity of the initial diagnostic process. The study aims to develop an expert system using the Certainty Factor method to assist in the early diagnosis of mental health disorders in women and children, specifically Depression, Anxiety, and Stress disorders. The research employs a Research and Development (R&D) approach with qualitative methods, including interviews with experts such as psychologists to obtain a knowledge base comprising symptoms, Measure of Belief, and Measure of Disbelief values. The expert system is implemented on the Android platform, facilitating user access to early diagnostic services. Results from the Certainty Factor calculations on user data indicate that the early diagnosis confidence levels are 97.04% for Depression, 63.11% for Anxiety, and 59.72% for Stress. The highest value is observed for Depression, suggesting that the symptoms selected by users most strongly indicate this disorder, with the highest confidence level across all Depression symptoms. Both manual calculations by experts within the system and Black Box testing confirm that the Certainty Factor method can effectively support early diagnosis of mental health disorders. The study concludes that the expert system using the Certainty Factor method is effective and can be implemented as an early mental health detection tool. The strength of this research lies in the integration of qualitative expert knowledge with mobile technology implementation, providing a practical and easily accessible solution for the community.
Co-Authors Abdul Malik Buna Adam, Novita Adrian Djafar Ali, Satriadi D Deya Riski Haluti Dunggio, Zufriato K. Fitria Anggraini Hariati Husain Ifriandi Labolo Ifriandi Labolo Isla, Muhammad Kamase, Hamka Witri La Ardi Achmad Basir Marlin Lasena Mayang, Dewi Cahyani Misrawati Aprilyana Puspa Muhammad Isla Muhammad Isla Rahmawati, Rahmawati Ridwan Y Kulu Salma P Nua Salma P. Nua Santawal, Santawal Santawali Santawali Santawali Santawali Santawali Santawali, Santawali Satiadi D Ali Satriadi Ali Sennung, Bahtiar Utiarahman, Siti Andini Wahab, Rahmawalta Yulianty Lasena Zahrannisa, Adea Zufrianto Dunggio Zufriato K. Dunggio