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All Journal Ulul Albab: Jurnal Studi Islam MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Jurnal Teknologi dan Manajemen Informatika OPSI SMATIKA Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Indonesian Journal of Artificial Intelligence and Data Mining JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Riset Informatika JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Review Pendidikan dan Pengajaran (JRPP) Jurnal Mantik ILKOMNIKA: Journal of Computer Science and Applied Informatics Jurnal Mnemonic G-Tech : Jurnal Teknologi Terapan International Journal of Advances in Data and Information Systems Journal of Computer Networks, Architecture and High Performance Computing Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences Jurnal Computer Science and Information Technology (CoSciTech) J-Intech (Journal of Information and Technology) Didaktika Religia Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Journal of Information Technology
Ririen Kusumawati
Universitas Islam Negeri Maulana Malik Ibrahim Malang
Religion Aerospace Engineering Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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Journal : Jurnal Computer Science and Information Technology (CoSciTech)

 1 
Analisis Data Mining Untuk Deteksi Diabetes Mellitus Menggunakan Naïve Bayes Yusril Haza Mahendra; Ririen Kusumawati; Imamudin
Computer Science and Information Technology Vol 6 No 1 (2025): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v6i1.7954

Abstract

Diabetes mellitus is a chronic disease with a continuously increasing global prevalence. it is characterized by high blood glucose levels due to the body's inability to produce or effectively use insulin. the widespread impact on individuals and communities underscores the importance of early detection and proper management. In the digital era, data mining analysis has become a crucial tool in healthcare, enabling the exploration and analysis of health data on a large scale to identify patterns and trends that are difficult to detect manually. in the context of detecting diabetes mellitus, data mining holds great potential for predictive model development. one of the algorithms used is naïve bayes. This study analyzes naïve bayes classification for early symptoms of diabetes mellitus, with the aim of enhancing understanding of risk factors and developing early detection tools. The research findings indicate that naïve bayes has the highest accuracy of 78% with the application of missing value imputation mean. It is hoped that this research will enhance efforts in preventing and managing diabetes mellitus, as well as reducing the burden on individuals and communities as a whole.
Co-Authors A, Miftahul Hikmah Putri Samudera Aang Subiyakto Abd. Rahman Ahlan Abdurrozzaaq Ashshiddiqi Zuhri Achmad Fahreza Alif Pahlevi Agung Teguh Wibowo Almais Agus Sofiyan Anwar, Agus Sofiyan Ahmad Fahmi Karami Ainul Yaqin Aldian Faizzul Anwar Anwar, Aldian Faizzul Arief, Yunifa Miftachul Asrul Sani Azmi, Agus N Balogun, Naeem A Cahyo Crysdian Dita Aisha Dwi Purbo Yuwono Dwi Yuniarto Eko Agus Moh. Iqbal Erfan Ainul Yakin Fachrul Kurniawan Fathurrahman Fathurrahman Fithriani Matondang, Fithriani Fresy Nugroho Fresy Nugroho Hariyadi, Muhammad Amin Hartawan, Muhammad S Hidayah, Ika Arofatul Hidayah Hidayah, Imalatul Huda, Muhammad Q Ida Ayu Putu Sri Widnyani imamudin Imamudin, M Imamudin, Muhammad Irwan Budi Santoso Kunaefi, Aang Kurniawati Kurniawati Lia Wahyuliningtyas MARIA BINTANG Marudin, Marudin Maulidifa, Renisa Mokhamad Amin Hariyadi Muchammad Mustaqhfiri, Muchammad Muhammad Andryan Muhammad Andryan Wahyu Saputra Muhammad Faisal Muhammad Isa Ansori Muji, Muji Nashrul Hakiem Novardy, Novardy Nur Fitriyah Ayu Tunjung Sari Pahlevi, Achmad Fahreza Alif Prima Astuti Handayani Puspa Miladin Nuraida Safitri A. Silfiyah, Chilmiatus Sri Harini Subarkah, Aan Fuad Sulika Sulika Suryatno, Agung Suseno, Hendra B Syawab, Moh Husnus Totok Chamidy Usman Pagalay Viva Arifin Wahyuliningtyas, Lia Wibowo, Firmansyah Rekso Wiwik Handayani Yuliawan, Audi Bayu Yuniar Setyo Marandy Yunifa Miftachul Arif Yunifa Mittachul Arif Yusril Haza Mahendra Zainal Abidin Zainal Abidin Zuhri, Abdurrozaq Ashshiddiqi Zuhri, Abdurrozzaaq Ashshiddiqi