Jaringan Saraf Tiruan (JST) Memprediksi Penyakit Rubella Menggunakan Metode Backpropagation
DOI:
https://doi.org/10.62951/bridge.v2i4.219Keywords:
Data Mining, Rubella, BackpropagationAbstract
The development of Information Technology is now entering various sectors, including health, and is implemented in Bidadari Binjai Hospital. As a health institution that is committed to excellent service and quality, Bidadari Binjai Hospital needs to innovate technology. One health issue that requires attention is rubella, an airborne infectious disease that has the potential to cause serious disorders such as hearing loss, cataracts, speech delay, and heart failure in toddlers and children. The initial symptoms of rubella are often similar to other common diseases, so public understanding of these symptoms is very important for quick treatment. This research aims to develop an information technology-based system that is able to predict rubella using the backpropagation method. This method is expected to improve the accuracy of diagnosis and make it easier for people to recognize rubella symptoms early on. The proposed system aims to provide better diagnosis support at Bidadari Binjai Hospital, as well as increase public awareness and knowledge about rubella disease. From the research conducted, the results of the accuracy rate obtained when conducting a test program were selected according to the symptoms and the results obtained were rubella disease with a 100% accuracy rate.
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Agus Perdana Windarto, Darmeli Nasution, Anjar Wanto, Frinto Tambunan, Muhammad Said Hasibuan, Muhammad Noor Hasan Siregar, Muhammad Ridwan Lubis, Solikhun, Yusra Fadhillah, & Dicky Nofriansyah. (2020). Jaringan Saraf Tiruan (J. Simarmata (ed.); Janner Simarmata). Tim Kreatif Kita Menulis.
Agushybana, F., Nuryanto, & Margawati, A. (2018). Imunisasi Campak dan Rubella. In S. P. Jati & Martini (Eds.), FKM UNDIP Press. FKM UNDIP Press.
Amna, S, W., Putra, T. A., Wahidin, A. J., Syukrilla, W. A., Wardhani, A. K., Heryana, N., Indriyani, T., & Santoso, L. W. (2023). Data Mining Data mining. In D. Ediana (Ed.), PT Global Eksekutif Teknologi (1st ed., Vol. 1, Issue 1).
Aziz Muslim Much, P. B. L. H. M. E. J. H. A. M. H. R. S. N. A. (2019). Data Mining.
Hartanto, D., & Hansum, S. (2013). Pengertian dan Konsep Data Mining – GSB-IPB. Gamma Sigma Beta.
Ismanto, E., & Cynthia, E. P. (2017). Jaringan Syaraf Tiruan Algoritma Backpropagation Dalam Memprediksi Ketersediaan Komoditi Pangan Provinsi Riau. Rabit : Jurnal Teknologi Dan Sistem Informasi Univrab, 2(2), 196–209. https://doi.org/10.36341/rabit.v2i2.152
Marwati, F., & Fauzi, R. (2024). Prediksi Penyakit Diabetes Melitus Menggunakan Jaringan Syaraf Tiruan Dengan Metode Backpropagation. Jitu: Jurnal Informatika Utama, 2(1), 26–34.
Muhajir, A., & Artanimgsih, E. Y. (2023). Artificial Neural Network Untuk Diagnosa Penyakit Kulit Kusta Dengan Backpropagation (Studi Kasus RSK DR. Sitanala Tangerang). JORAPI : Journal of Research and Publication Innovation, 1(3), 694–702.
Munazilin, A., & Santoso, F. (2021). Logika dan Algoritma Pemrograman (1st ed., Vol. 1). CV. AA. RIZKY.
Naufal, T., Arnes, S., & Hermansyah, S., (2024). Jaringan Syaraf Tiruan Memprediksi Tingkat Penggunaan Sosial Media DiMasa Pandemi Menggunakan Metode Backpropagation. Jurnal Teknik,Komputer, Agroteknologi dan Sains, 1(1), 94–102.
Nurhayati. 2008. Analisis Statistik Deskriptif MengguNakan Matlab. Yogyakarta: Graha Ilmu.
Relita Buaton, Zarlis, M., Efendi, S., & Yasin, V. (2019). DATA MINING TIME SERIES (1st ed., Vol. 1). Wade Group.
Widodo, W., Rachman, A., & Amelia, R. (2014). Jaringan Syaraf Tiruan Prediksi Penyakit Demam Berdarah Dengan Menggunakan Metode Backpropagation. Jurnal IPTEK.
Yulia, Rendy, & Arnomo, S. A. (2023). Jaringan Syaraf Tiruan Mendeteksi Penyakit Pneumonia Infeksi Saluran Pernafasan Akut Dengan Algoritma Back Propagation. Indonesian Journal of Computer Science, 12(2), 284–301. http://ijcs.stmikindonesia.ac.id/ijcs/index.php/ijcs/article/view/3135
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