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All Journal Jurnal Sains dan Teknologi TELKOMNIKA (Telecommunication Computing Electronics and Control) Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Jurnal Teknologi Informasi dan Ilmu Komputer Sistemasi: Jurnal Sistem Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Pilar Nusa Mandiri Jurnal Ekobistek Sebatik MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Teknologi Informasi dan Pendidikan Indonesian Journal of Electrical Engineering and Computer Science Community Development Journal: Jurnal Pengabdian Masyarakat Majalah Ilmiah UPI YPTK Jurnal Informatika Terpadu Journal of Computer Scine and Information Technology Jurnal Ipteks Terapan : research of applied science and education COMSERVA: Jurnal Penelitian dan Pengabdian Masyarakat Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence Jurnal Media Computer Science Jurnal Komtekinfo SATIN - Sains dan Teknologi Informasi Jurnal Teknik dan teknologi tepat guna The Indonesian Journal of Computer Science TECHNOMEDIA : Informatics and Computer Science Jurnal TAM (Technology Acceptance Model) Jurnal Komputer, Informasi dan Teknologi
Syafri Arlis
Universitas Putra Indonesia YPTK
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Journal : sebatik

 1 
POLA PENENTUAN STATUS PEMINJAMAN DENGAN ALGORITMA PERCEPTRON Syafri Arlis; Darma Syahrullah Ekajaya; Musli Yanto
Sebatik Vol 23 No 2 (2019): Desember 2019
Publisher : STMIK Widya Cipta Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (338.482 KB)

Abstract

Pada setiap penentuan pemberian dana pinjaman koperasi yang dilakukan, pada umumnya memiliki sistem yang sama dengan melihat data-data yang diajukan oleh pihak peminjam sebelumnya. Penelitian ini memiliki tujuan untuk mampu mengenali pola pemberian status peminjaman yang akan diberikan oleh pihak koperasi dengan mengkobinasikan konsep ilmu pada jaringan saraf tiruan algoritma perceptron. Algoritma ini sangat cocok dalam mengenali pola yang berkerja dengan melakukan pelatihan jaringan berdasarkan variabel-variabel dari data yang digunakan pada jaringan. Dalam proses pelatihan yang dilakukan jaringan, penulis menggunakan alat bantu software matlab. Hasil penelitian yang didapat akan mampu memberikan masukan pada pihak pengelola koperasi dalam memberikan status pemberian dana pinjaman yang lebih terkonsepdan tersistem agar proses pemberian status peminjaman lebih cepat dan efisien.
Intelligent System for Diagnosing Infectious Diseases in  Children Using the Certainty Factor and Naive Bayes Methods Based on Android Ahmad Khomsi; Syafri Arlis; S Sumijan
Sebatik Vol. 30 No. 1 (2026): June 2026
Publisher : STMIK Widya Cipta Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46984/sebatik.v30i1.2743

Abstract

Infectious diseases in children remain a serious health problem due to their high vulnerability resulting from an immune system that is not yet fully developed. Limited access to medical personnel and delays in early detection often result in ineffective treatment. Therefore, this study aims to design and implement an Android-based intelligent system application capable of detecting infectious diseases in children early on by utilizing the Certainty Factor and Naïve Bayes methods. This system is designed as an expert system that mimics the way pediatricians analyze symptoms and determine preliminary diagnoses. The research methods used include collecting disease and symptom data based on the knowledge of pediatric health experts, data analysis, rule base formation, and the design and implementation of an Android-based system. The Certainty Factor method is used to handle the uncertainty of the level of confidence in the symptoms selected by the user, while the Naïve Bayes method is used to calculate the probability of disease based on historical data. The combination of these two methods aims to improve the accuracy and reliability of diagnostic results. The results of the study show that the developed expert system application is capable of providing initial diagnostic information on infectious diseases in children quickly and easily accessible to parents and health workers. This system is expected to be an effective early detection tool, support initial medical decision-making, and contribute to the development of artificial intelligence-based health technology in Indonesia.
Teacher Performance Evaluation Analysis Using K-Means Clustering Algorithm and Random Forest Classification Dito Jurinaldo; Musli Yanto; Syafri Arlis
Sebatik Vol. 30 No. 1 (2026): June 2026
Publisher : STMIK Widya Cipta Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46984/sebatik.v30i1.2744

Abstract

Teacher performance assessment is a primary parameter in determining the quality of educational institutions. Evaluation systems in many elementary schools still rely on descriptive qualitative approaches. Abundant school administrative data often remain as unprocessed archival records without further analytical utilization. This condition results in school management decision-making that lacks a strong empirical foundation. This study applies data mining technology to transform administrative data into strategic information. The research focuses on SD Negeri 12 Padang Besi and involves all active teaching staff during the current academic year. The research dataset is entirely derived from internal school records. This study excludes the use of questionnaire instruments, and in-depth interview methods are not employed in the data collection process. The analysis is strictly limited to administrative aspects, without including assessments of in-class pedagogical competence. The technical implementation utilizes the K-Means Clustering algorithm to automatically identify patterns in teacher performance grouping. This process is followed by the application of the Random Forest algorithm to measure classification accuracy based on the available administrative features. The combination of these methods produces a performance mapping that is free from human subjectivity. The analytical results provide clear performance labels for each individual teacher. This study contributes to the development of a data-driven digital evaluation model. School management can use the outputs of this research as a basis for reward allocation or targeted professional development programs. This approach ensures transparency in human resource governance within the educational environment.
Co-Authors Agung Ramadhanu Ahmad Khomsi Andrian, Reski Aprilian Gevindo Ariza Ikhlas Aswandi, Nopan Bambang Supperianto Billy Hendrik Candra Putra Darma Syahrullah Ekajaya Deri Marse Putra Dito Jurinaldo Dodi Guswandi Doli Raharjo, Tio Eggy Febyanti Edwar Fachriqi Naldes Fadhila Putri Sani Fadhila Putri Sani Fajrul Islami Febri Hadi Febri Hadi Feri Pratama Gunadi Widi Nurcahyo Gunadi Widi Nurcahyo, Gunadi Guslendra Hanum, Luthfia Harkamsyah Andrianof Ilsa hidayat Imam Fakhri Muhammad Iskandar Fitri Johan Harlan Jufriadif Na`am, Jufriadif Larissa Navia Rani, Larissa Larissa Naviarani M.Iqbal, M.Iqbal Mardison Mardison Marfalino, Hari Muhammad Reza Putra Muhammad, Abulwafa Nabila Frisca Oktavia Nabilah Putri Permana Olivia, Ladyka Febby Permana, Nabilah Putri Purnama, Ayu Widya Putra, Muhammad Reza Rahma Yanti Ridwan, Ridwan Rofil M. Nur Rusydi, Rezki Sahari Sahari Sahari Sahari Sahari Saputra, Randy Sarjon Defit SIGIT SANJAYA, SIGIT Sofika Enggari Sovia, Rini Sukardi Sukardi Sumijan Sumijan Sumijan, Sumijan Sumijan Supperianto, Bambang Syahputra, Afriadi Wahyu, Fungki Waruwu, Kalfinus Winda Sutra Amanda Winda Sutra Amanda Yanto, Musli Yanto, Musli Yesri Elva Yuhandri Yuhandri, Yuhandri Yulasmi