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All Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Timuris : Journal of Computational and Information Research
Rabiah Adawiyah
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Computer Science & IT

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Implementasi Analytical Hierarchy Process Dan Metode Perbandingan Eksponensial Untuk Pemberian Reward Karyawan Suharsono Bantun; Rabiah Adawiyah; Kharis Syaban; Dimas Febriyan Priambodo; Nirsal Nirsal; Suci Pricilia Lestari; Jayanti Yusmah Sari
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 10 No 1 (2023): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v10i1.3082

Abstract

Giving employee rewards for a company is one of the agendas that must be considered carefully. This is because the provision of rewards can be an indicator to encourage employees to work harder for more optimal company performance, but in reality it is difficult to determine employees who deserve to receive rewards because many employees are entitled to receive rewards but the quota is limited. This is the difficulty faced by PT. YZZ especially in providing annual rewards, because in the calculation process it has 5 assessment criteria so that in this case a decision support system is needed to assist managers in providing recommendations for employees who are entitled to receive rewards using the Analytical Hierarchy Process (AHP) and Metode Perbandingan Eksponensial (MPES). Based on the results of the study, there are several alternatives that are recommended to receive rewards so that it can be suggested in giving employee rewards.
Classifying Family Economic Status Using the K-Nearest Neighbor Algorithm in Popalia Village Istrikah Istrikah; Rabiah Adawiyah; Yuwanda Purnamasari Pasrun
Timuris: Journal of Computational and Information Research Vol. 1 No. 1 (2026): Timuris: Journal of Computational and Information Research
Publisher : Kiswah Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Access to accurate family economic data is essential for the equitable distribution of village social assistance. At the Popalia Village Office, Tanggetada Sub-district, Kolaka Regency, identification of eligible recipients previously relied on manual, page-by-page verification of Statistics Indonesia (BPS) census documents, a process that was slow and often produced recipients that did not match the intended criteria. This study develops a web-based classification system using the K-Nearest Neighbor (KNN) algorithm to categorize 160 household heads into “Mampu” (financially capable) and “Tidak Mampu” (financially incapable) classes based on twelve socio-economic criteria, including occupation, monthly income, education, number of dependents, and asset ownership. The system was built following the Waterfall development model using PHP and MySQL with a use-case-driven UML design. Model performance was evaluated using Euclidean-distance-based KNN with 10-fold cross validation and confusion matrix analysis. The system achieved an average classification accuracy of 99.38% (minimum 93.75%, maximum 100%), a precision of 98.21%, a recall of 100%, and an F1-score of 99.10%. Black-box testing further confirmed that all functional modules operated as intended. These findings indicate that KNN is an accurate and practical method for supporting village-level social assistance targeting.
Co-Authors Dimas Febriyan Priambodo Istrikah Istrikah Jayanti Yusmah Sari Nirsal Nirsal Suci Pricilia Lestari Suharsono Bantun Syaban, Kharis Yuwanda Purnamasari Pasrun