Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Journal Of Artificial Intelligence And Software Engineering

Goods Management System Using Always Better Control (ABC) Method Prasetyo, Adi Tri; Hasanah, Herliyani; Oktaviani, Intan
Journal of Artificial Intelligence and Software Engineering Vol 5, No 3 (2025): September
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i3.7351

Abstract

This study aims to design and develop a web-based inventory management system utilizing the Always Better Control (ABC) method to assist Toko Didik in managing stock more efficiently. Until now, the inventory process in the store has been carried out manually using conventional record-keeping, which is prone to data entry errors, delays in stock monitoring, and the absence of a classification system to prioritize items based on their sales contribution.To address this problem,  the system was designed using the Waterfall development methodology, involving stages of requirements analysis, system design, implementation, and testing. Data were collected through observation, interviews, and documentation conducted at the store site. The system was built using the Laravel framework and MySQL database, and includes key features such as item recording, automatic item classification using the ABC method, real-time stock monitoring, purchase recommendations, sales transactions, and sales reporting. The results of black-box testing indicate that all system functions operate as expected without errors. The ABC classification method successfully groups items into three categories based on their contribution to total sales, allowing the store owner to prioritize procurement effectively. With this system, inventory management becomes more organized, accurate, and supports data-driven decision-making. This study serve as an alternative solution for small or medium-sized stores in addressing inventory management challenges through the use of information systems.
Geographic Information System (GIS) For Road Repair Planning Prioritization Using Naive Bayes Alamsyah, Bintang; Hasanah, Herliyani; Oktaviani, Intan
Journal of Artificial Intelligence and Software Engineering Vol 5, No 3 (2025): September
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i3.7396

Abstract

Prioritizing road infrastructure repair in rural areas often faces challenges, particularly due to budget limitations and subjective evaluation processes. This study aims to design and develop a web-based Geographic Information System (GIS) integrated with the Naive Bayes classification algorithm to support objective road repair prioritization. The system was developed using the Rapid Application Development (RAD) approach, involving active user participation in iterative development cycles. The application was built using Laravel as the backend framework, Leaflet.js for interactive map visualization, and PostgreSQL with the PostGIS extension for spatial data management. The system is capable of managing regional and road data, receiving road damage reports, and classifying repair priorities into high, medium, or low categories based on parameters such as damage level, traffic volume, and road length. The classification results are visualized on an interactive map to assist village officials in monitoring infrastructure and making informed decisions. System evaluation using black box testing confirmed that all functionalities operate validly in accordance with user requirements. This system offers an accurate and transparent data-driven solution for managing road infrastructure in Jelobo Village and has the potential to be replicated in other regions with similar conditions.