Published: 2022-03-04
Sistem Pakar untuk Mendeteksi Gejala Awal Penyakit Apendisitis dengan Metode Case Based Reasoning (CBR) Berbasis Mobile Android
DOI: 10.35870/jtik.v6i4.553
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Abstract
Appendicitis is caused by inflammation of the intestines (appenditis). The patient will feel pain in the lower right abdomen. This study explores this with several references, by designing an expert system an application is produced that is used to detect appendicitis. This process can help detect early symptoms starting from the user answering questions in the form of symptoms suffered by the user. The research applies the Case Base Reasoning method in the expert system by detecting the early symptoms of appendicitis using this android-based device. The research aims to add experience to users in finding out the disease they feel by entering the initial symptoms and providing solutions or it can be without consulting the nearest hospital or clinic. The results of the research. This android-based appendicitis expert system aims to help diagnose Appendicitis Inflammatory Disease for children under five and adults based on Android Mobile, and the Appendicitis Disease Diagnosis Expert System that was built to provide information easily starting from understanding, dangers, causal factors, symptoms of the disease and solution only by consulting the system and objectives can help provide a good solution.
Keywords
Expert System ; Appendicitis ; Blackbox Testing ; Case Based Reasoning
Article Information
This article has been peer-reviewed and published in the Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi). The content is available under the terms of the Creative Commons Attribution 4.0 International License.
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Issue: Vol. 6 No. 4 (2022)
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Section: Computer & Communication Science
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Published: %750 %e, %2022
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License: CC BY 4.0
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Copyright: © 2022 Authors
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DOI: 10.35870/jtik.v6i4.553
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Catur Nugroho
Universitas Siber Asia
Ade Davy Wiranata
Universitas Muhammadiyah Prof. Dr. HAMKA
Rima Tamara Aldisa
Universitas Nasional
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Admin. 2021. Penyakit Usus Buntu, Alodokter.https://www.alodokter.com/penyakit-usus-buntu
-
Toba, H. and Tanadi, S., 2008. Pengembangan Case-Based Reasoning Pada Aplikasi Pemesanan Kain Berdasarkan Studi Kasus Pada CV. Mitra KH Bandung. Jurnal informatika, 4(2), pp.135-148.
-
Putri, T.E., Andreswari, D. and Efendi, R., 2016. Implementasi Metode CBR (Case Based Reasoning) dalam Pemilihan Pestisida terhadap Hama Padi Sawah Menggunakan Algoritma K-Nearest Neighbor (KNN)(Studi Kasus Kabupaten Seluma). Rekursif: Jurnal Informatika, 4(1).
-
Warsidi. 2017. pengertian-sistem-pakar. 2017https://students.warsidi.com/2017/06/pengertian-sistem-pakar-adalah.html.
-
Asif, M. and Ahmed, J., 2020. A novel case base reasoning and frequent pattern-based decision support system for mitigating software risk factors. IEEE Access, 8, pp.102278-102291.
-
Asim, Y., Malik, A.K., Raza, B., Shahid, A.R. and Qamar, N., 2020. Predicting influential blogger’s by a novel, hybrid and optimized case based reasoning approach with balanced random forest using imbalanced data. IEEE Access, 9, pp.6836-6854.
-
Putra, S.E., Munir, Z. and Masriadi, M., 2021. Sistem Pakar Penyakit Ikan Bawal Bintang Dengan Metode Case Based Reasoning. JURSIMA (Jurnal Sistem Informasi dan Manajemen), 9(2), pp.30-39.
-
Kristiana, T., 2018. Sistem pakar untuk mendiagnosa penyakit saluran pencernaan dengan metode forward chaining. Informatik: Jurnal Ilmu Komputer, 14(2), pp.65-80.
-
Nasution, S.W., Hasibuan, N.A. and Ramadhani, P., 2017. Sistem Pakar Diagnosa Anoreksia Nervosa Menerapkan Metode Case Based Reasoning. KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer), 1(1).
-
Yuliati, N., 2012. Perancangan Dan Implementasi Sistem Pakar Untuk Memprediksi Penyakit Apendisitis Dengan Metode Dempster-Shafer. Jurnal Manajemen Informatika, 1(1).
-
Marifat, I.S. and Kesuma, C., 2018. Pengembangan sistem pakar mendeteksi penyakit pencernaan menggunakan metode naive bayes berbasis web.
-
Rahman, A. and Qosim, A., 2021. Sistem Cerdas Pengelompokan Mahasiswa Berdasarkan Prediksi Performa Belajar Dengan Metode Case Based Reasoning. Jurnal Edik Informatika Penelitian Bidang Komputer Sains dan Pendidikan Informatika, 8(1), pp.13-26.
-
Sulistiani, H., Darwanto, I. and Ahmad, I., 2020. Penerapan Metode Case Based Reasoning dan K-Nearest Neighbor untuk Diagnosa Penyakit dan Hama pada Tanaman Karet. JEPIN (Jurnal Edukasi Dan Penelitian Informatika), 6(1), pp.23-28.
-
Nurhayatmi, E., Muttaqin, Z., Sugiyarta, A. and Hay’s, R.N., 2019. Expert System for Diagnosing Types of Diseases in Human Intestine Organs Using the Certainty Factor Method. Journal of Machine Learning and Soft Computing, 1(2), pp.21-28.
-
Utami, A., Suyanto, Y. and Sihabuddin, A., 2021. Reccomendations on Selecting The Topic of Student Thesis Concentration using Case Based Reasoning. IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 15(1), pp.1-10.
-
Gupita, G., Harijanto, B. and Ariyanto, Y., 2017. Pengembangan Sistem Pakar Pendeteksi Penyakit Pada Kucing Dengan Metode Case Based Reasoning Dan Certainty Factor Berbasis Android. Jurnal Informatika Polinema, 3(2), pp.8-8.
-
Utomo, D.P. and Nasution, S.D., 2016. Sistem Pakar Mendeteksi Kerusakan Toner Dengan Menggunakan Metode Case Based-Reasoning. JURIKOM (Jurnal Riset Komputer), 3(5).
-
Hastings, J.D., Latchininsky, A.V., Adelung, T.J. and Schell, S.P., 2014, January. Early Assessment of an Approach to Determining the Predictive Coverage of Case-Based Reasoning with Adaptation through CARMA. In 2014 47th Hawaii International Conference on System Sciences (pp. 857-864). IEEE.
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