Web-Based Expert System Application for Early Diagnosis of HIV/AIDS Using the Naive Bayes Method

Sri Purwani Aisah; Rizal Tjut Adek; Zara Yunizar

doi:10.29103/jacka.v1i4.17809

Web-Based Expert System Application for Early Diagnosis of HIV/AIDS Using the Naive Bayes Method

Sri Purwani Aisah, Rizal Tjut Adek, Zara Yunizar

Abstract

AIDS is a progressive decrease in the immune system so that opportunistic infections can appear and end in death, therefore the author created an early diagnosis system for HIV/AIDS using the website-based Naïve Bayes algorithm. Naïve Bayes is a simple probability classification that can calculate all possibilities by combining a number of combinations and frequencies of a value from the database obtained.the results of the research obtainedThe naïve Bayes algorithm can be implemented for early diagnosis of HIV/AIDS by means that the existing HIV/AIDS symptom data is adjusted to the patient's symptom data processed using the naïve Bayes algorithm and then it is concluded what the symptoms are and What is the solution.

Keywords

Application; Expert System; HIV/AIDS; Naive Bayes; Website

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References

Sapti ayubbana,2022, remaja yang terinfeksi hiv/aids di indonesia (analisis data publikasi sdki 2017), holistik jurnal kesehatan, volume 16, no.2

Nurma yuliyanasari, 2017, global burden desease – human immunodeficiency virus – acquired immune deficiency syndrome (hiv-aids), dosen fakultas kedokteran universitas muhammadiyah surabaya – indonesia

Rizal rachman, 2021, klasifikasi algoritma naive bayes dalam memprediksi tingkat kelancaran pembayaran sewa teras umkm, jurnal informatika, vol.8 no.2

Wahyu hidayatullah,2023, sistem pakar diagnosis penyakit ispa menggunakan metode naïve bayes berbasis web pada puskesmas teratak, jurnal kecerdasan buatan dan teknologi informasi (jkbti), vol. 2, no. 1,

Fitrokh nur ikhromr,2023, implementasi data mining untuk memprediksi penyakit diabetes menggunakan algoritma naives bayes dan k-nearest neighbor, journal of information technology and computer science (intecoms) volume 6 nomor 1

D. Abdullah, Merancang Aplikasi Perpustakaan Menggunakan SDLC, Medan: Sefa Bumi Persada, 2017

Hasibuan, M. S. (2024). Jurnal Teknologi Informasi Magister Darmajaya PREDIKSI PENYAKIT PARU-PARU MENGGUNAKAN ALGORITMA. 1(1).

Riadi, I., Umar, R., Anggara, R., Dahlan, U. A., Korespondensi, P., Mining, D., & Neighbor, K. (2024). Prediksi kelulusan tepat waktu berdasarkan riwayat akademik menggunakan metode k-nearest neighbor. Jurnal Teknologi Informasi Dan Ilmu Komputer (JTIIK), 11(2), 249–256.

Yuswinda, E. H., Zufria, I., & Husein, I. (2024). Penerapan Metode Naïve Bayes Untuk Mendiagnosis Penyakit Pohon Karet Di PT. Bridgestone Aek Tarum. Journal of Information Technology, 4(1), 157–165. https://doi.org/10.46229/jifotech.v4i1.876

UNICEF. (2020). Reimagining a resilient HIV response for children, adolescents and pregnant women living with HIV

UNICEF. (2020). Reimagining a resilient HIV response for children, adolescents and pregnant women living with HIV Chen,W.K. (1993). Linear Networks and Systems.Wadsworth, Belmont, 123-135.

Costa, T., Zarante, P., Sodré, J. (2013).Simulation of aldehyde formation in ethanol fuelled spark ignition engines. In: Sens, M., Baar, R. (eds) Engine Processes. Expert Verlag, Berlin.

Bentley, R.E. (1998). Handbook of Temperature Measurement Vol. 3: The Theory and Practice of Thermoelectric Thermometry. Springer Science & Business Media.

Hasan. (2017). Prediksi Tingkat Kelancaran Pembayaran Kredit Bank Menggunakan Algoritma Naive Bayes Berbasis Forward Selection. Ilkom Jurnal Ilmiah. Indomaret.Co.Id. (2018)..

Puridewi, Nugraha. (2018). Perbandingan Metode Naive Bayes, Support Vector Machine Dan Id3 Dalam Penetapan Status Penanganan Kecelakaan Kerja.

DOI: https://doi.org/10.29103/jacka.v1i4.17809