Main Article Content

Emanuel Fahik
Derwin R Sina
Arfan Y Mauko


Case Based Reasoning (CBR) method is one method to build a system with new case decision based on solution from previous cases by calculating similarity level. In this study, the authors apply CBR to diagnose dental and mouth disease in humans. Sources of system knowledge are obtained by collecting cases that have occurred before. The calculation of similarity values ​​using the Block City Gower method with threshold 60%. This system can diagnose 5 diseases based on 26 existing symptoms. The output of the system in the form of the illness experienced by the patient based on the symptoms entered by non-physician medical personnel, as well as the treatment solution which accompanied the presentation of similarities with the previous case to show the truth level of possible diagnosis. Based on the results of the test case obtained the results: the system can take back the old case is appropriate and has used the formulation of Block City method correctly indicated with 100% accuracy, and use 122 cases is optimal enough to diagnose 5 diseases indicated by the average similarity to 20 cases for milk teeth growth phase of 80% and 30 cases for adult tooth growth phase of 90%.


Download data is not yet available.

Article Details

How to Cite
Fahik, E., Sina, D., & Mauko, A. (2017). CASE BASED REASONING UNTUK MENDIAGNOSA PENYAKIT GIGI DAN MULUT MENGGUNAKAN METODE BLOCK CITY. Jurnal Komputer Dan Informatika, 5(2), 28-33.


J-ICON, Vol. 5 No. 2, Oktober 2017 : 28~33
3. Setiap gejala dapat ditambahkan dengan bobot untuk meminimalisir perbedaan diagnosa antara sistem dengan pakar.
4. Metode-metode yang lain untuk mengasilkan penelitian-penelitian lain yang bermanfaat.
[1] Riset Kesehatan Dasar., 2013, Badan Penelitian dan Pengembangan Kesehatan Kementerian Kesehatan RI, Jakarta.
[2] Kementerian Kesehatan Republik Indonesia., 2013, Profil Kesehatan Indonesia, Jakarta.
[3] Nur dan Abdul Fadlil, 2013, Sistem Identifikasi Citra Jenis Cabai (Capsicum Annum L.) Menggunakan Metode Klasifikasi City Block Distance, Jurnal Sarjana Teknik Informatika, e-ISSN 2338-5197, Volume 1 Nomor 2, Universitas Ahmad Dahlan.
[4] Faizal, E., 2012, Case Based Reasoning Diagnosis Penyakit Mata, Jurnal Teknologi Informasi dan Ilmu Komputer, STMIK El Rahma Surabaya.
[5] Swari, M., 2014, Sistem Diagnosis Penyakit Gigi Dan Mulut Menggunakan Kombinasi Case Based Reasoning Dan Rule Based Reasoning, Universitas Gadja Mada, Yogyakarta.
[6] Aamodt, A., dan Plaza, E., 1994, Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches. AI Communications, Vol. 7, 39- 59.
[7] Sung dan Hyuk Cha, 2007, Comprehensive Survey on Distance/Similarity Measure Between Probability Density Function, International Journal Of Mathematical And Methods In Applied Scmiences, Issue 4 Volume 1, Pace University.

Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.