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All Journal International Journal of Electrical and Computer Engineering Riau Journal of Computer Science InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Jurnal Informatika Upgris Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Teknik Komputer AMIK BSI JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Penelitian Pendidikan IPA (JPPIPA) IT JOURNAL RESEARCH AND DEVELOPMENT Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Teknik Informatika UNIKA Santo Thomas Minda Baharu Building of Informatics, Technology and Science Jurnal Mantik Informatika Jurnal Pendidikan Teknologi Informasi dan Vokasional Jurnal Tekinkom (Teknik Informasi dan Komputer) JIIP (Jurnal Ilmiah Ilmu Pendidikan) MEANS (Media Informasi Analisa dan Sistem) International Journal Of Science, Technology & Management (IJSTM) JPM: JURNAL PENGABDIAN MASYARAKAT SECONDARY : Jurnal Inovasi Pendidikan Menengah (JIPM) Journal La Edusci Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) TEACHING : Jurnal Inovasi Keguruan dan Ilmu Pendidikan EDUTECH : Jurnal Inovasi Pendidikan Berbantuan Teknologi Bulletin of Information Technology (BIT) EXPLORER Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Journal of Computer Science and Information Systems (JCoInS) IKA BINA EN PABOLO : PENGABDIAN KEPADA MASYARAKAT Jurnal Pengabdian Masyarakat Gemilang (JPMG) Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Zadama: Jurnal Pengabdian Masyarakat Jurnal Arsitektur Jurnal Informatika: Jurnal Pengembangan IT Jurnal Pengabdian Masyarakat dan Riset Pendidikan Jurnal Gemilang Informatika (GIT) EDUCATIONAL: Jurnal Inovasi Pendidikan dan Pengajaran Jurnal Ilmu Komputer Ruru
Iwan Purnama
Universitas Labuhanbatu
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

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Journal : building of informatics technology and science

 1 
Sistem Pendukung Keputusan Pemilihan Sales Supervisor Menerapkan Metode EDAS berdasarkan Pembobotan ROC Purnama, Iwan; Zulkifli, Zulkifli; Nasution, Muhammad Bobbi Kurniawan; Karim, Abdul; Trianovie, Sri
Building of Informatics, Technology and Science (BITS) Vol 5 No 1 (2023): June 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i1.3558

Abstract

Sales is a job that aims to sell a product in the form of goods, services and others and provide the best service to consumers or buyers. Sales will work optimally if managed properly. The person who works to manage sales work is a sales supervisor. Sales Supervisor is someone who is responsible for managing the work procedures of each sales person under his control. A supervisor is required to be able to control every task implementation of a salesperson. If the company hires someone who is not qualified to be a sales supervisor, it will cause losses. So to determine the sales supervisor, a system is needed that will help select good and quality sales supervisor candidates according to the criteria set by the company. The right system to assist companies in making elections is SPK. Decision support system (DSS) is a system that is deliberately created to assist certain parties in making decisions with quality and objective results. SPK requires a method. In this study the method used is the EDAS method. The EDAS method has a function, namely to produce a ranking value by implementing mathematical formulations correctly according to the rules. The mathematical formulation is systematically arranged by experts and produces a ranking value which will eventually be assembled into an accurate decision. From the results of this study, a value of 0.5348 was obtained by Mandala as an alternative to B7, which is the best sales supervisor candidate
Komparasi Perbandingan Algoritma C4.5, Naive Bayes, K-Nearest Neighbor, Random Forest Untuk Prediksi Faktor Penyebab Penyakit Diabetes Muhammad Bagus Fadli; Iwan Purnama; Rohani Rohani
Building of Informatics, Technology and Science (BITS) Vol 7 No 3 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i3.8683

Abstract

Diabetes is a chronic metabolic disease characterized by elevated blood glucose levels and can cause various serious complications and contribute to high mortality rates worldwide. The main problem in managing diabetes is the need for accurate patient status classification based on laboratory test data so that appropriate treatment can be carried out. This study aims to compare the performance of the C4.5 algorithm, Naive Bayes, K-Nearest Neighbor (KNN), and Random Forest in classifying diabetes patient data. The dataset used was sourced from Electronic Health Records (EHRs) with research subjects from Rantauprapat Regional General Hospital, totaling 10,000 data consisting of eight attributes and one class attribute, with 859 diabetes patient data and 9,141 non-diabetes patient data. The research method was carried out by dividing the data into training data and testing data using a ratio of 90:10, 80:20, and 70:30. Evaluation of model performance used accuracy parameters and Receiver Operating Characteristic (ROC) with Area Under Curve (AUC) values. The results showed that the C4.5 and Random Forest algorithms produced higher accuracy values ​​than Naive Bayes and KNN, especially at training data ratios of 90%:10% and 70%:30%. Based on the ROC evaluation, the Random Forest algorithm obtained the highest AUC values ​​at the 70%:30% ratio of 0.972 and 80%:20% of 0.970. Based on these test results, it can be concluded that the C4.5 and Random Forest algorithms have relatively better performance and are almost equivalent in classifying diabetes based on accuracy and AUC values.
Co-Authors Abdul Karim Agus Perdana Windarto Agustina Sidabutar Agustina, Asri Widya Aini, Putri Al Amri Al Maahi, Muhammad Zuhri Ali Akbar Ritonga Ali Akbar Ritonga Alvionita, Icha Ambiyar, Ambiyar Andi Ernawati Andre Ardian Ardansyah, Muhammad Ardansyah, Muhmmad Arie Pramana Ashari, Suci Asyahri Hadi Nasyuha Aysyah Rengganis AZIDDIN HARAHAP Aziddin Harahap Balqi, Siti Fadillah Bangun, Budianto D.Leo Surya Duha Dahrul Aman Harahap Danil Polanda Dar Hasibuan, Halmi Deby Lorensyah Rambe Dudes Manalu Elysa Rohayani Hasibuan Elysa Rohayani Hasibuan Fahmi Rizal Faisal Efendi Siregar Fauzan Azim Febriani, Lisa Feri, Jonny Firman Edi Firman Edi Fitri Indina Dongoran Gomal Juni Yarnis Guna Dharma, Aditya Gunawan, Yogi Harahap, Aziddin Harahap, Nur Salimah Hasibuan, Elysa Rohanayani Hasibuan, Linda Suhela Hasibuan, Mila Nirmala Sari Heni Pujiastuti Ibnu Rasyid Munthe Ibnu Rasyid Munthe Ibnu Rasyid Munthe ibnu Rasyid Munthe Ibu Rasyid Munthe Indah Lestari, Indah Ira Purnama Sari Irmayani, Deci Jufri Khairul Khairul Hadi Listia, Bella Ayu Lubis, Khoirunnisaiyah Lubis, Rizky Ramadhan Hasan M. Rafi Mahadi Kesuma Rambe Marha As, Pawa Niassa Marlina Siregar Masrizal Masrizal Menrisal Mesran, Mesran Mohamad Fakih Firdaus Monica, Nelly Muhammad Ardansyah Muhammad Bagus Fadli Muhammad Halmi Dar Muhammad Hamka Muslim N, M Rizqi Nasution, Muhammad Bobbi Kurniawan Nathania Putri1, Nathania Nelly Monica Nurhayati Nuridin Widya Pranoto Nurintan Asyiah Siregar Nurwijayanti Nur’ainun Gulo Pane, Rahmadani Puput Indrayani Rahel Marianti Ritonga Raja Inganta Sinulingga Ramzi Saputra Rasyid Munthe, Ibnu Reni Kartikaningsih Rian Farta Wijaya Rian Farta Wijaya Rio Septian Hardinata Risnawati Agustin Rizki Hariandi Rohani Rohani Rohani Rohani Rohani Ronal Watrianthos Rosnah Ritonga Ruth Rize Paas Megahati S Ruth Rize Paas Megahati S Ruth Rize Paas Megahati.S Ryan Utama Tambunan Safaridah Rambe Sakinah Sakinah Sandhi, Bagus Hari Sapriyani Sapriyani Saputra, Haris Tri Saputra, Ramzi Saragih, Reagan Surbakti Sempurna, Teguh Silestian, Selvi Siregar, Julmahdi Siregar, Marlina Siregar, Sakinah Ubudiyah Solikhun Solikhun, Solikhun Sulis Sumitro Sarkum Sumitro Sarkum Sumitro Sarkum Sumitro Sumitro Surya Ramadhan Suryadi, Sudi Susi Susanti Sutrino Dwi Raharjo Sutrisno Dwi Raharjo Suwarti Syahputra Harahap, Hasmi Syahrul Syaiful Zuhri Harahap Syaiful Zuhri Harapan Tambak, Riski Romadhon Tiok Wijanarko Trianovie, Sri Ummy Hairani Unung Verawardina Volante, Kevin Volvo Sihombing Windo Yandri Lesmana Yandri Lesmana Yanris, Gomal Juni Zulfahmi Syahputra Zulkifli Zulkifli Zulkifli