Analisis dan Penerapan Algoritma Naïve Bayes Untuk Klasifikasi Penyakit Diabetes Melitus

M Daffa Adrian ; Pareza Alam Jusia ; Rudolf Sinaga ; Azzahra Raihana Adriansyah ; Mutammimah Mutammimah
Prosiding Seminar Nasional Ilmu Teknik 📅 2025 Vol 2, No 2 🔗 DOI: 10.61132/prosemnasproit.v2i2.114
Abstract
Diabetes Mellitus is a group of metabolic diseases characterized by hyperglycemia resulting from defects in insulin secretion, insulin action or both. Hyperglycemia is a medical condition in the form of an increase in glucose levels beyond normal limits which is a characteristic of several diseases, especially Diabetes Mellitus, in addition to various other conditions. Diabetes Mellitus is currently a global health threat. Classification is one of the techniques of data mining that can be used to help predict the results of the classification of types of diabetes using the naïve Bayes algorithm. Testing was carried out using 5 evaluation models including rapid miner with 3 options, namely use training set, 5 Fold Cross-Validation, 10 Fold Cross-Validation, and 2 other evaluation models, namely Microsoft Excel and Python. Testing data regarding Diabetes Mellitus has high accuracy in the excel evaluation model, which is 89.00% compared to other evaluation models. Meanwhile, the lowest accuracy is the Python evaluation model which obtains an accuracy of 86.36%. The Naïve Bayes algorithm can be said to be one of the most effective algorithms, both in terms of calculations and the final results, where the test can be used as a basis for diabetes mellitus considering the accuracy results are above 85%.
Keywords
Data Mining; Naïve Bayes Algorithm; Diabetes Mellitus
How to Cite

M Daffa Adrian, et al. (2025). Analisis dan Penerapan Algoritma Naïve Bayes Untuk Klasifikasi Penyakit Diabetes Melitus. Prosiding Seminar Nasional Ilmu Teknik, 2(2). https://doi.org/10.61132/prosemnasproit.v2i2.114

M Daffa Adrian; Pareza Alam Jusia; Rudolf Sinaga; Azzahra Raihana Adriansyah; Mutammimah Mutammimah, "Analisis dan Penerapan Algoritma Naïve Bayes Untuk Klasifikasi Penyakit Diabetes Melitus," Prosiding Seminar Nasional Ilmu Teknik, vol. 2, no. 2, 2025.

M Daffa Adrian; Pareza Alam Jusia; Rudolf Sinaga; Azzahra Raihana Adriansyah; Mutammimah Mutammimah. "Analisis dan Penerapan Algoritma Naïve Bayes Untuk Klasifikasi Penyakit Diabetes Melitus." Prosiding Seminar Nasional Ilmu Teknik, vol. 2, no. 2, 2025.

M Daffa Adrian; Pareza Alam Jusia; Rudolf Sinaga; Azzahra Raihana Adriansyah; Mutammimah Mutammimah. "Analisis dan Penerapan Algoritma Naïve Bayes Untuk Klasifikasi Penyakit Diabetes Melitus." Prosiding Seminar Nasional Ilmu Teknik 2, no. 2 (2025).

M Daffa Adrian, et al. (2025) 'Analisis dan Penerapan Algoritma Naïve Bayes Untuk Klasifikasi Penyakit Diabetes Melitus', Prosiding Seminar Nasional Ilmu Teknik, 2(2). doi: 10.61132/prosemnasproit.v2i2.114.

M Daffa Adrian; Pareza Alam Jusia; Rudolf Sinaga; Azzahra Raihana Adriansyah; Mutammimah Mutammimah. Analisis dan Penerapan Algoritma Naïve Bayes Untuk Klasifikasi Penyakit Diabetes Melitus. Prosiding Seminar Nasional Ilmu Teknik. 2025;2(2).

Artikel Terkait

Pengolahan Citra Digital Kamera Multispektral Berbasis Drone dengan Artificial Neural Network (ANN) untuk Identifikasi Cekaman Air pada Tanaman Padi

Shahiban Muzaki

Analisis Tingkat Kepuasan Pengguna Pada Website Smp Negeri 5 Kota Jambi Menggunakan Model Webqual 4.0 Dan Importance Performance Analisis (Ipa)

Usi Nofriana; Nurhadi Nurhadi; Joni Devitra

Implementasi Simple Additive Weighting Untuk Rekomendasi Karir Mahasiswa Berdasarkan Hasil Tes Psikologi

Moh Nur Iman Siyus Setyowati; Dihin Muriyatmoko; Eko Prasetio Widhi

Analisis Performa Convolutional Neural Network untuk Klasifikasi Aktivitas Pengemudi Terganggu

Zufar Abdullah Rabbani; Wahyu Syaifullah J S; Alfan Rizaldy Pratama

Analisis Korelasi Faktor Gaya Hidup Terhadap Indikator Kesehatan Menggunakan Metode Shapiro-Wilk dan Spearman

Mohd Fadli Ariansyah; Eka Pandu Cynthia

Pengukuran Tingkat Kesiapan Pasien RSUD Abdul Manap Terhadap Mobile JKN Menggunakan Metode HOT-Fit

Titania Arida Nandini; Setiawan Assegaff; Nurhadi Nurhadi
Tren Sitasi Jurnal