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All Journal Jurnal Informatika Progres
Dikwan Moeis
Ilmu Komputer, STMIK Profesional Makassar
Computer Science & IT

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IMPLEMENTASI SISTEM PENDAFTARAN SISWA BARU BERBASIS WEB MENGGUNAKAN ALGORITMA SAW DI SANGGAR KEGIATAN BELAJAR UJUNG PANDANG Calvin Bonar Sarumpaet; Hidayatul Fajri; Suardi Hi Baharuddin; Dikwan Moeis
PROGRESS Vol 17 No 1 (2025): April
Publisher : P3M STMIK Profesional Makassar

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The new student registration process at Sanggar Kegiatan Belajar (SKB) Ujung Pandang was previously conducted manually, resulting in several issues such as data processing delays, file accumulation, and lack of transparency in selection. This study aims to develop a web-based registration information system integrated with the Simple Additive Weighting (SAW) algorithm to enhance the efficiency and objectivity of the selection process. The system was developed using the Waterfall model and implemented using PHP and MySQL-based web technology. The implementation results show that the system can automate registration and selection in real-time. The SAW algorithm effectively produces objective participant rankings based on criteria such as exam scores, age, and domicile. Evaluation indicates that the system improves selection speed, result accuracy, and facilitates data management for users. It can be concluded that this system provides significant benefits for both SKB administrators and applicants and is relevant in supporting the digital transformation of non-formal education.
IMPLEMENTASI ALGORITMA APRIORI UNTUK ANALISIS PERSEDIAAN MATERIAL DI WAREHOUSE PT. TELKOM AKSES MAKASSAR Dzul Jalali Wal Ikram; Ahmad Rifai Sadrin; Dikwan Moeis; Rosnani
PROGRESS Vol 17 No 1 (2025): April
Publisher : P3M STMIK Profesional Makassar

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This research aims to implement Apriori algorithm for data mining in material inventory management at PT. Telkom Akses Makassar. Apriori algorithm identifies frequent itemsets and generates association rules from transaction data to optimize warehouse stock management. The methodology includes data collection through observation, interviews, and historical transaction datasets. Data processing uses Apriori to calculate support, confidence, and lift metrics. The results indicate that frequent item combinations can improve planning accuracy and reduce stockouts. A web-based application, Material Analyzer, was developed for analysis and visualization, featuring dashboard, analysis, history, and visualization modules. This study contributes practically by supporting logistics decision-making and theoretically by expanding data mining applications in inventory systems.
Co-Authors Ahmad Rifai Sadrin Calvin Bonar Sarumpaet Dzul Jalali Wal Ikram Hidayatul Fajri Rosnani Suardi Hi Baharuddin