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All Journal Jurnal Ilmiah Teknologi dan Rekayasa Informatics for Educators and Professional : Journal of Informatics
Yoseph Pius Kurniawan Kelen
University of Timor
Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Other

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Pengembangan sistem pakar diagnosis tingkat depresi mahasiswa semester akhir berbasis android menggunakan metode certainty factor Maximilianus Amasanan; Yoseph Pius Kurniawan Kelen
Jurnal Ilmiah Teknologi dan Rekayasa Vol. 31 No. 1 (2026)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/tr.2026.v31i1.143

Abstract

Depression is increasingly experienced by final-year university students due to academic pressure, with symptoms such as prolonged sadness, loss of motivation, sleep disturbances, and difficulty concentrating. Early detection remains limited because of restricted access to mental health professionals and the high cost of consultations. This study aims to develop an Android-based expert system for diagnosing depression levels using the Certainty Factor (CF) method. The research employed the Research and Development (R&D) method with the Rapid Application Development (RAD) model, which consists of requirements planning, design, construction, and implementation stages. The system utilizes 15 symptoms and classifies four levels of depression: mood disorder, mild depression, moderate depression, and severe depression. The evaluation was conducted on 20 respondents by comparing the system’s diagnostic results with expert analysis. The evaluation results showed that 17 out of 20 system diagnoses were consistent with the expert’s analysis, resulting in an accuracy rate of 85%. An example of the calculation process using the CF method produced a diagnostic value of 0.95 (95%), which falls into the severe depression category. The developed system is capable of supporting early detection of depression in a faster, more practical, and easily accessible manner through Android devices, and it can serve as an initial consultation tool for final-year students. The system can assist early detection more efficiently and with greater accessibility.
Sistem pakar diagnosis stadium rabies pada manusia menggunakan metode certainty factor berbasis web: studi kasus Puskesmas Oelolok Maria Gradiana Misa; Yoseph Pius Kurniawan Kelen; Krisantus Tey J Seran
Jurnal Ilmiah Teknologi dan Rekayasa Vol. 31 No. 1 (2026)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/tr.2026.v31i1.167

Abstract

Delays in the early diagnosis of rabies remains a significant issue due to the limited of public knowledge in recognizing the symptoms of the disease, resulting in delayed medical treatment. This study aims to develop a web-based expert system designed to assist in the early diagnosis of rabies in humans using the Certainty Factor (CF) method. This method is used to calculate the confidence level of the diagnosis based on the symptoms selected by the user. The system knowledge base was obtained through expert interviews and literature studies, which were represented in the form of diagnostic rules. The system is capable of providing rabies diagnosis results along with their corresponding confidence values based on the symptoms entered by users. Functional testing using the Black Box Testing method showed that all system features functioned properly. In addition, system validation was carried out by comparing the system diagnosis results with expert diagnoses through 30 testing scenarios using different symptom combinations. The test results showed 27 matching data and 3 non-matching data, resulting in a system accuracy rate of 90%. This research contributes to the implementation of the CF method in a web-based expert system to support early rabies diagnosis in a fast and measurable manner.
Sistem Pendukung Keputusan Penentuan Budidaya Tanaman Buah Buahan Terhadap Jenis Lahan Pertanian Di Eban Menggunakan Metode Fuzzy Tahani Maria Ermalinda Usboko; Yoseph Pius Kurniawan Kelen; Dian Grace Ludji
INFORMATICS FOR EDUCATORS AND PROFESSIONAL : Journal of Informatics Vol. 11 No. 1 (2026): INFORMATICS FOR EDUCATORS AND PROFESSIONAL : JOURNAL OF INFORMATICS (Juni 2026
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat Universitas Bina Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51211/itbi.v11i1.3890

Abstract

Budidaya tanaman buah memerlukan kesesuaian kondisi lahan agar tanaman dapat tumbuh optimal dan menghasilkan produktivitas yang baik. Permasalahan yang sering terjadi adalah penentuan lahan pertanian masih dilakukan secara subjektif berdasarkan pengalaman petani sehingga menyebabkan ketidaksesuaian antara kondisi lahan dan kebutuhan tanaman buah. Penelitian ini bertujuan membangun Sistem Pendukung Keputusan penentuan budidaya tanaman buah-buahan terhadap jenis lahan pertanian di Eban menggunakan metode Fuzzy Tahani. Metode ini digunakan karena mampu menangani data yang bersifat tidak pasti melalui pendekatan logika fuzzy dan basis data relasional. Kriteria yang digunakan meliputi pH tanah, temperatur, ketinggian tempat, ketebalan tanah, curah hujan, dan tekstur tanah. Sistem dibangun berbasis web menggunakan PHP, CodeIgniter, dan MySQL. Proses penelitian meliputi analisis kebutuhan, perancangan sistem, implementasi metode Fuzzy Tahani, dan pengujian sistem menggunakan Black Box Testing serta pengujian akurasi. Hasil penelitian menunjukkan bahwa sistem mampu menghasilkan rekomendasi tanaman buah sesuai kondisi lahan pertanian. Berdasarkan hasil perhitungan, tanaman pisang menjadi alternatif terbaik dengan nilai fire strength tertinggi sebesar 0,260745. Pengujian akurasi dilakukan terhadap 20 pengguna dengan data kondisi lahan yang berbeda dan menghasilkan tingkat akurasi sebesar 100%. Dengan demikian, sistem yang dibangun dapat membantu proses pengambilan keputusan dalam menentukan budidaya tanaman buah secara lebih objektif dan efektif.
Co-Authors Dian Grace Ludji Maria Ermalinda Usboko Maria Gradiana Misa Maximilianus Amasanan Tey Seran, Krisantus Jumarto