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All Journal Jurnal Simetris Jurnal Informatika Jurnal Informatika Telematika : Jurnal Informatika dan Teknologi Informasi JITK (Jurnal Ilmu Pengetahuan dan Komputer) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI J I M P - Jurnal Informatika Merdeka Pasuruan DoubleClick : Journal of Computer and Information Technology JurTI (JURNAL TEKNOLOGI INFORMASI) Jurnal Teknologi Sistem Informasi dan Aplikasi JSiI (Jurnal Sistem Informasi) METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi KOMPUTA : Jurnal Ilmiah Komputer dan Informatika Infoman's: Jurnal Ilmu-Ilmu Manajeman dan Informatika Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Journal of Information Systems and Informatics Community Engagement and Emergence Journal (CEEJ) JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) JTIKOM: Jurnal Teknik dan Sistem Komputer Jurnal Teknologi dan Sistem Tertanam Journal of Soft Computing Exploration BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Jurnal Pengabdian Kepada Masyarakat Abdi Nusa Jurnal Ilmiah IT CIDA : Diseminasi Teknologi Informasi Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Jurnal Pengabdian Mitra Masyarakat (JPMM) J-ABDIPAMAS (Jurnal Pengabdian Kepada Masyarakat) Teknikom: Teknologi Informasi, Ilmu Komputer dan Manajemen Jurnal Informatika: Jurnal Pengembangan IT
Hendra Marcos
Universitas Amikom Purwokerto
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Library & Information Science Mathematics Medicine & Pharmacology Public Health Social Sciences Other

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Journal : Jurnal Informatika

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PERBANDINGAN KINERJA ALGORITME C.45 DAN NAIVE BAYES MENGKLASIFIKASI PENYAKIT DIABETE Marcos, Hendra; Utomo, Hengky Setiawan
Jurnal Informatika Vol 15, No 2 (2015): Jurnal Informatika
Publisher : IIB Darmajaya

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Abstract

Diabetes or can be called with diabetes or blood sugar disease is a disease that is hard to cure but can be controlled blood sugar levels. This causes people with diabetes is increasing every year. This study aims to determine which algorithm that has the best classification accuracy, so that it can be used to assist in classifying whether a person has diabetes or not. The data used is the Pima Indians Diabetes dataset obtained from the UCI machine learning. Processing of data mining is divided into two stages, namely stage of data preprocessing and feature selection. Results of the research that has been done, C4.5 algorithm has an accuracy of 73.82% and increased to 74.87%, subsequent to the selection of attributes. While naïve Bayes has an accuracy rate of 76.30% and increased to 77.47%. The end result of this research is naïve bayes algorithm is better than C4.5 algorithms because it has a better accuracy rateKeyword: C4.5, Naïve Bayes, Diabetes
Co-Authors Aan Supandhi Akhmad Yusuf Fauzi Ali Nur Ikhsan Amira Aida Rashifa Amrulloh, Nur Azmi Arbi Restandi Ardu Darugutni Arsi, Primandani Atmaja Jalu Narendra Kisma Bagus Adhi Kusuma Berlilana Berlilana Desty Rakhmawati Didit Suhartono Dimas Marsus Pandega Dita Ferdian Bayu Kusuma Dwijayanto, Adi Prayogo Dwiki Febriyanto Eka Tripustikasari Fadila Darojatu Sidqi Fanesa Dwiana Hengky Setiawan Utomo Hero Galuh Pyawai Husni Muzaki Ika Romadoni Yunita Indah, Ulya Intan Surya Saputra, Dhanar Irza Dwi Niesviantika Isti Nurhafiyah Jaka Wijaya Kusuma jordy, Roy Jordy Kinanthi Putri Siwilopo Mahardika, Fajar Prasetyo Kartika, Nur Kholifah Dwi Pungkas Subarkah Purnawati , Ely Purwadi Purwadi Rahman Rosyidi Rakhmawati, Desty Restiana Tri Oktavia Riyanto Riyanto Riyanto Rofiqoh, Dayana Saputri, Deva Risma SITI ALVI SHOLIKHATIN Subarkah, Pungkas Utomo, Hengky Setiawan Wenti Risma Damayanti Wiga Maulana Baihaqi Wildan Abdillah Wildan Razzaq Pratama Yusida Munsa Idah