Sistem Pakar Deteksi Dini Gejala Poliycystic Kidney Disease (PKD) Menggunakan Metode Forward Chaining Berbasis Android
Article Sidebar
Main Article Content
Abstract
The purpose of this study is to build an application with the forward chaining method used to diagnose Polycystic Kidney Disease based on Android. The research method consists of analysis and design, while the use case diagram is used as a model of the system to be built, Forward Chaining is implemented in the system to diagnose Polycystic Kidney Disease and the application is built based on Android. The conclusion from the results of this study is to show the application features that are made to run. An expert system application designed to be able to help Polycystic Kidney Disease based on the symptoms entered by the user using the Forward Chaining method.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
The Authors submitting a manuscript do so on the understanding that if accepted for publication, copyright of the article shall be assigned to JTIK journal and Research Division, KITA Institute as the publisher of the journal. Copyright encompasses rights to reproduce and deliver the article in all form and media, including reprints, photographs, microfilms, and any other similar reproductions, as well as translations.
JTIK journal and Research Division, KITA Institute and the Editors make every effort to ensure that no wrong or misleading data, opinions or statements be published in the journal. In any way, the contents of the articles and advertisements published in JTIK journal are the sole and exclusive responsibility of their respective authors and advertisers.
The Copyright Transfer Form can be downloaded here: [Copyright Transfer Form JTIK]. The copyright form should be signed originally and send to the Editorial Office in the form of original mail, scanned document or fax :
Muhammad Wali (Editor-in-Chief)
Editorial Office of Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi)
Research Division, KITA Institute
Teuku Nyak Arief Street Nomor : 7b, Lamnyong, Lamgugop, Kota Banda Aceh
Telp./Fax: 0651-8070141
Email: jtik@lembagakita.org - journal@lembagakita.org
References
Bergmann, C., Guay-Woodford, L.M., Harris, P.C., Horie, S., Peters, D.J. and Torres, V.E., 2018. Polycystic kidney disease. Nature reviews Disease primers, 4(1), pp.1-24.
Cornec-Le Gall, E., Alam, A. and Perrone, R.D., 2019. Autosomal dominant polycystic kidney disease. The Lancet, 393(10174), pp.919-935.
Cornec-Le Gall, E., Alam, A. and Perrone, R.D., 2019. Autosomal dominant polycystic kidney disease. The Lancet, 393(10174), pp.919-935.
Cornec-Le Gall, E., Alam, A. and Perrone, R.D., 2019. Autosomal dominant polycystic kidney disease. The Lancet, 393(10174), pp.919-935.
Serra, G., Corsello, G., Antona, V., D’Alessandro, M.M., Cassata, N., Cimador, M., Giuffrè, M., Schierz, I.A.M. and Piro, E., 2020. Autosomal recessive polycystic kidney disease: case report of a newborn with rare PKHD1 mutation, rapid renal enlargement and early fatal outcome. Italian journal of pediatrics, 46(1), pp.1-6.
Al-Qumboz, M.N.A., Elsharif, A.A., Samy, I.M.D. and Abu-Naser, S.S., 2019. Kidney Expert System Diseases and Symptoms. International Journal of Academic Engineering Research (IJAER), 3(5).
Singla, J., Kaur, B., Prashar, D., Jha, S., Joshi, G.P., Park, K., Tariq, U. and Seo, C., 2020. A Novel Fuzzy Logic-Based Medical Expert System for Diagnosis of Chronic Kidney Disease. Mobile Information Systems, 2020.
Soroka, S., Alam, A., Bevilacqua, M., Girard, L.P., Komenda, P., Loertscher, R., McFarlane, P., Pandeya, S., Tam, P. and Bichet, D.G., 2018. Updated Canadian expert consensus on assessing risk of disease progression and pharmacological management of autosomal dominant polycystic kidney disease. Canadian journal of kidney health and disease, 5, p.2054358118801589.
Kaur, B., Sadawarti, H. and Singla, J., 2019, November. A Comprehensive Review of Medical Expert Systems for Diagnosis of Chronic Kidney Diseases. In 2019 International Conference on Smart Systems and Inventive Technology (ICSSIT) (pp. 1008-1013). IEEE.
Abu Al-qumboz, M.N., Elsharif, A.A., Dheir, I.M. and Abu-Naser, S.S., 2019. Kidney Expert System Diseases and Symptoms.
Azhar, S., Sari, H.L. and Zulita, L.N., 2014. Sistem Pakar Penyakit Ginjal Pada Manusia Menggunakan Metode Forward Chaining. Jurnal Media Infotama, 10(1).
Jepri, J., 2019. Pengembangan Sistem Pakar Diagnosis Penyakit Ginjal Kronik Menggunakan Metode FIS-Sugeno. STRING (Satuan Tulisan Riset dan Inovasi Teknologi), 3(3), pp.258-266.
Rosmawanti, N. and Kusumawardhani, G.P., 2021. Model Sistem Pakar Diagnosa Penyakit Gagal Ginjal Menggunakan Metode Teorema Bayes. Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi, 9(3), pp.205-216.
Suryadibrata, A., 2014. Sistem pakar untuk memprediksi penyakit ginjal kronis menggunakan neural network (Doctoral dissertation, Universitas Multimedia Nusantara).