Sistem Pakar dengan Menggunakan Metode Naive Bayes dalam Mengidentifikasi Penyakit Karies pada Gigi Manusia
DOI:
https://doi.org/10.37034/jsisfotek.v3i4.71Keywords:
Expert System, Dental Caries, Naive Bayes, Codeigniter Framework, MySQLAbstract
Caries disease in human teeth is a disease that permanently destroys the inner walls of teeth and forms small holes in the teeth. The Indonesian people lack the knowledge to find information and identify tooth decay, which makes many people unaware of the consequences and dangers of this disease. Tooth decay disease is usually caused by three factors. The first factor is teeth and saliva, which are the hosts of microorganisms in the oral cavity. Bacteria and food are the second and third factors. The purpose of this research is to help the public find information about tooth decay, thus forming a branch of artificial intelligence, the expert system. Artificial intelligence is a science that allows you to build computer systems that display intelligence in different ways. An expert system is a computer program or information system that uses some knowledge of an expert. The methods used in this study are the Naive Bayes method and the model's view controller, which are implemented as a database in the PHP Codeigniter framework and MySQL. The data processed in this study is knowledge about the symptoms of dental caries obtained from experts. The test results of this method provide patients with the knowledge necessary to prevent tooth decay, with an accuracy rate of 83.61%. This expert system helps the public to recognize and obtain information about tooth decay. The Expert System can also be used to take the first step in preventing tooth decay
References
Arysespajayadi, A., Sutoyo, M. N., & Qammaddin, Q. (2019). Implementasi Metode Certainty Factor pada Sistem Pakar Diagnosa Penyakit Karies Gigi. Jurnal Sains Dan Informatika, 5(2), 167–176. DOI: https://doi.org/10.34128/jsi.v5i2.188
Kurniawan, A., Sumijan, & Jufriadif Na’am. (2019). Sistem Pakar Identifikasi Modalitas Belajar Siswa Menggunakan Metode Forward Chaining. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 3(3), 518–523. DOI: https://doi.org/10.29207/resti.v3i3.1166
Wahyuni, W. C., & Sitio, A. S. (2020). Pest Detection Expert System And Method Using Bayes Rice Diseases. Journal Of Computer Networks, Architecture and High Performance Computing, 2(2), 313–319. DOI: https://doi.org/10.47709/cnapc.v2i2.411
Setyaputri, K. E., Fadlil, A., & Sunardi, S. (2018). Comparative Analysis of Certainty Factor Method and Bayes Probability Method on ENT Disease Expert System. Scientific Journal of Informatics, 5(2), 205–212. DOI: https://doi.org/10.15294/sji.v5i2.16151
Ilham Insani, M., Alamsyah, A., & Putra, A. T. (2018). Implementation of Expert System for Diabetes Diseases using Naïve Bayes and Certainty Factor Methods. Scientific Journal of Informatics, 5(2), 185–193. DOI: https://doi.org/10.15294/sji.v5i2.16143
Sihotang, H. T., Riandari, F., Simanjorang, R. M., Simangunsong, A., & Hasugian, P. S. (2019). Expert System for Diagnosis Chicken Disease using Bayes Theorem. Journal of Physics: Conference Series, 1230(1). DOI: https://doi.org/10.1088/1742-6596/1230/1/012066
Windarto, Y. E., & Marfuah, M. (2020). Implementasi Naives Bayes-Certainty Factor untuk Diagnosa Penyakit Menular. Jurnal Sisfokom (Sistem Informasi Dan Komputer), 9(2), 208–214. DOI: https://doi.org/10.32736/sisfokom.v9i2.823
Nur, R. M., Na’am, J., Nurcahyo, G. W., & Arlis, S. (2019). Peningkatan Keamanan Website Menggunakan Metode XML dengan Framework Codeigniter. Indonesian Journal of Computer Science, 8(2), 156–163. DOI: https://doi.org/10.33022/ijcs.v8i2.188
Rahman, F., & Ratna, S. (2018). Perancangan E-Learning Berbasis Web Menggunakan Framework Codeigniter. Technologia: Jurnal Ilmiah, 9(2), 95. DOI: https://doi.org/10.31602/tji.v9i2.1370
Cahaya Khairani, Y., & Nurcahyo, G. W. (2020). Sistem Pakar dalam Mengidentifikasi Tingkat Keparahan Penyakit pada Tanaman Kelapa Sawit Menggunakan Framework Codeigniter. Jurnal Informasi Dan Teknologi, 3, 53–57. DOI: https://doi.org/10.37034/jidt.v3i1.113
Yendrizal. (2021). Sistem Pakar Dalam Diagnosa Penyakit Kanker Rahim Menggunakan Metode Naïve Bayes dan Certainty Factor. Jurnal Media Informatika Budidarma, 5, 251–257. DOI: https://doi.org/10.30865/mib.v5i1.2669
Purnamawati, A., Nugroho, W., Putri, D., & Hidayat, W. (2020). Deteksi Penyakit Daun Pada Tanaman Padi Menggunakan Algoritma Decision Tree , Random Forest , Naïve Bayes , Svm Dan Knn. Info Tekjar : Jurnal Nasional Informatika Dan Teknologi Jaringan, 5(1), 212–215. DOI: https://doi.org/https://doi.org/10.30743/infotekjar.v5i1.2934
Sukarsih, S., Silfia, A., & Muliadi, M. (2019). Perilaku dan Keterampilan Menyikat Gigi terhadap Timbulnya Karies Gigi pada Anak di Kota Jambi. Jurnal Kesehatan Gigi, 6(2), 80–86. DOI: https://doi.org/10.31983/jkg.v6i2.5479
Abdussalaam, F., & Mardiansyah Ramadhan, M. (2019). Perancangan Sistem Informasi Work Order Dengan Metode Iteratif Menggunakan Framework Codeigniter (Studi Kasus :Cv Sirna Miskin Bandung). Jurnal E-Komtek (Elektro-Komputer-Teknik), 3(1), 35–48. DOI: https://doi.org/10.37339/e-komtek.v3i1.129
Yanto, M., Khairiazaz, Y., & Kunci, K. (2020). Komparasi Metode Naive Bayes dan Certainty Factor untuk Mendiagnosa Penyakit Anemia Pendahuluan Metode Penelitian. Jurnal Ilmiah KOMPUTASI, 19, 1–8.
Kurniawan, A., Sumijan, & Jufriadif Na’am. (2019). Sistem Pakar Identifikasi Modalitas Belajar Siswa Menggunakan Metode Forward Chaining. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 3(3), 518–523. DOI: https://doi.org/10.29207/resti.v3i3.1166
Minarni, M., & Irawan, P. (2019). Implementasi Metode Naive Bayes Untuk Diagnosa Penyakit Lambung. Jurnal TeknoIf, 7(2), 115. DOI: https://doi.org/10.21063/jtif.2019.v7.2.115-123
Nababan, M., Laia, Y., Sitanggang, D., Sihombing, O., Indra, E., Siregar, S., Purba, W., & Mancur, R. (2018). The diagnose of oil palm disease using Naive Bayes Method based on Expert System Technology. Journal of Physics: Conference Series, 17(1). DOI: https://doi.org/10.1088/1742-6596/17/1/012015
Puspa, M. A. (2018). Sistem Pakar Diagnosa Penyakit Hipertensi Menggunakan Metode Naive Bayes Pada Rsud Aloe Saboe Kota Gorontalo. ILKOM Jurnal Ilmiah, 10(2), 166–174. DOI: https://doi.org/10.33096/ilkom.v10i2.304.166-174
Perbawawati, A. A., Sugiharti, E., & Muslim, M. A. (2019). Bayes Theorem and Forward Chaining Method On Expert System for Determine Hypercholesterolemia Drugs. Scientific Journal of Informatics, 6(1), 116–124. DOI: https://doi.org/10.15294/sji.v6i1.14149
Silahudin, D., Henderi, & Holidin, A. (2020). Model expert system for diagnosis of COVID-19 using naïve bayes classifier. IOP Conference Series: Materials Science and Engineering, 17(1). DOI: https://doi.org/10.1088/1757-899X/17/1/012067
Widodo, Y. B., Anggraeini, S. A., & Sutabri, T. (2021). Perancangan Sistem Pakar Diagnosis Penyakit Diabetes Berbasis Web Menggunakan Algoritma Naive Bayes. Jurnal Teknologi Informatika Dan Komputer MH. Thamrin, 7(1), 112–123. DOI: https://doi.org/https://doi.org/10.37012/jtik.v7i1.507
Putra, D. W. T., Utami, A. O., Minarni, M., & Swara, G. Y. (2019). Accuracy Level of Diagnosis of ENT Diseases in Expert System. Jurnal KomtekInfo, 6(2), 127–134. DOI: https://doi.org/10.35134/komtekinfo.v6i2.829
Widiyawati, C., Imron, M., Informatika, T., & Kucing, P. (2018). Sistem Pakar Diagnosa Penyakit Pada Kucing Menggunakan Metode Naive Bayes Classifier. Jurnal Teknologi Informasi Techno.Com, 17(2), 134–144. DOI: https://doi.org/10.33633/tc.v17i2.1625