RANCANG BANGUN SISTEM PAKAR DIAGNOSA GANGGUAN SUASANA PERASAAN (AFEKTIF) MENGGUNAKAN METODE TEOREMA BAYES BERBASIS ANDROID
Indonesia
DOI:
https://doi.org/10.31949/jensitec.v8i01.1905Abstract
Feeling disorder a group of clinical features characterized by reduced or lost emotional control and self-control. Affective disorders can be depression, manic or a mixture of both (bipolar). Someone who has mood disorders needs treatment as early as possible through early detection and an accurate assessment is carried out in consultation with a psychologist. So a system is needed that can detect the possible disturbance of the mood. Expert systems are part of artificial intelligence that mimics the slow pace of an expert. Bayes' Theorem is a way of knowing conditional probabilities. Conditional probability is the probability of an event occurring, given that it has some relationship with one or more other events. The probability value of symptoms and disease is obtained based on the experience of an expert. This expert system can produce a process of diagnosing mood disorders with some data about mood disorders in the form of symptom data, disease data and its probability value. The accuracy rate is 100% using 10 test data. An expert system for diagnosing mood disorders which is designed to be an Android-based application of JavaScript and PHP as a programming language, Cordova as a framework for creating mobile applications, PHP 7.2.1 as a web server, MySQL 5.0.21 as a database.
Keywords:
Mood disorders, expert system, teorema bayes, android, cordova, PHPDownloads
References
Depkes RI. R., 2019. Riset Kesehatan Dasar 2018.
Hardyan, D. S. & S., 2019. RANCANG BANGUN APLIKASI E-COMMERCE DAN FORUM BUDIDAYA TANAMAN KEBUN BERBASIS ANDROID. p. 25.
Harijanto, B. & Latif, R. A., 2016. Sistem Pakar Diagnosa Penyakit Pada Kucing Dengan Metode Teorema Bayes Berbasis Android. Teknologi Informasi, pp. 172-180.
Khotimah, N. & Kusumadewi, S., 2019. Sistem Pendukung Keputusan Untuk Diagnosis Banding Gangguan Afektif.
Kusumadewi, S., 2003. Artificial intelligence (teknik dan aplikasinya). Yogyakarta: Graha Ilmu.
Nofriansyah, D., Gunawan, R. & Elfitriani, 2020. Sistem Pakar Untuk Mendiagnosa Penyakit Pertussis (Batuk Rejan) Dengan Menggunakan Metode Teorema Bayes. J-SISKO TECH Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD, Volume vol.3, No.1, pp. 41-54.
Pravitasari, N., 2017. SISTEM PAKAR UNTUK MENENTUKAN GANGGUAN AFEKTIF. Faktor Exacta, Volume 3, pp. 237-246.
Proboyekti, U., 2011. Extreme Programing.. Yogyakarta: s.n.
Sujadi, H. & Suhaeni, E., 2016. Sistem Pakar Penyakit Dengan Gejala Demam Menggunakan Perangkat Mobile Berbasis Android.
Wahyuni, T., Sopiandi, i. & Raharjo, S., 2020. Sistem Informasi Geografis Wisata Kuliner Berbasis Android. INFOTECH journal, pp. 36-43.
Published
How to Cite
Issue
Section
License
An author who publishes in the J-ENSITEC (Journal of Engineering and Sustainable Technology) agrees to the following terms:
- Author retains the copyright and grants the journal the right of first publication of the work simultaneously licensed under the Creative Commons Attribution-ShareAlike 4.0 License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal
- The author is able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book) with the acknowledgment of its initial publication in this journal.
- The author is permitted and encouraged to post his/her work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of the published work