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All Journal Journal of Artificial Intelligence and Engineering Applications (JAIEA)
Lina Nur Afifah
Universitas Amikom Purwokerto
Automotive Engineering Computer Science & IT Control & Systems Engineering

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Design of a Warehouse Inventory Management System Using FEFO Method in NUSA Niaga Multi-Tenant Lina Nur Afifah; Aulia Hamdi; Sri Rahayu; Intan Nur Sifa; Rizki Cahya Putri; Purnia Setiawati; Aulia Suryaning Tyas; Mayza Nurul Khasanatun Nisa
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2343

Abstract

Most village-based businesses still manage their inventory manually, from monitoring warehouse stock and generating reports and checking items based on expiration dates. This process is considered inefficient and carries the risk of errors in data recording and reporting. In the process of transferring inventory to the display on the web-based NUSA Niaga platform, the FEFO method is applied. Needs analysis, system design, design implementation, and system documentation were conducted. Literature review on management systems, the FEFO method, multi-tenant architecture, and RBAC were used for data collection. The system was designed to monitor inventory, manage products nearing expiration, record goods transfers, and implement multi-tenant functionality using flowcharts, ERDs, and DFDs. This system is expected to help manage BUMDes warehouse in a more connected and structured manner.
Sentiment Analysis of TikTok User Comments on The Free Nutritious Meal Program Using Support Vector Machine Lina Nur Afifah; Sri Rahayu; Purwadi
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 2 (2026): February 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i2.1879

Abstract

This study aims to analyze user sentiment when leaving comments on TikTok about the Free Nutritious Food Program (MBG) to understand how the public views the program. Comment data was obtained through online collection and then divided into three groups: positive, negative, and neutral. Before further processing, the data went through a text cleaning and stemming stage to reduce word variation. The data was then represented using the TF-IDF method before being classified with a Support Vector Machine algorithm. The evaluation results showed that using stemming provided more accurate results than without using stemming, thereby improving the model's ability to recognize sentiments contained in comments using informal language. Additional analysis using word clouds, n-grams, and topic modeling provided an overview of words and issues frequently appearing in public discussions regarding the program.
Design of a Multi-Tenant Waste Management System with Volume Estimation and Vehicle Trip Optimazation Intan Nur Sifa; Aulia Hamdi; Purnia Setiawati; Aulia Suryaning Tyas; Rizki Cahya Putri; Mayza Nurul Khasanatun Nisa; Sri Rahayu; Lina Nur Afifah
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2327

Abstract

Waste management at the village level still faces a number of challenges, such as unstructured waste volume recording, suboptimal collection scheduling, and a lack of transparency in cost management. This study aims to design a multi-user waste management system equipped with a volume estimation model and vehicle route optimization. The approach applied includes a literature review to analyze system requirements, followed by design using flowcharts, Data Flow Diagrams (DFDs), and Entity-Relationship Diagrams (ERDs). The research findings indicate that the developed system successfully integrates the management of waste source data, transportation processes, and cost calculations in a structured manner. The volume estimation model is used to estimate the amount of waste in the field, while route optimization determines the number of vehicle trips based on their carrying capacity. Additionally, the multi-tenant concept allows this system to be used by various regions simultaneously while ensuring data separation. Therefore, this system is expected to improve operational efficiency, management transparency, and the quality of waste transportation services.
Co-Authors Aulia Hamdi Aulia Hamdi Aulia Suryaning Tyas Aulia Suryaning Tyas Intan Nur Sifa Intan Nur Sifa Mayza Nurul Khasanatun Nisa Mayza Nurul Khasanatun Nisa Purnia Setiawati Purnia Setiawati Purwadi Purwadi Rizki Cahya Putri Rizki Cahya Putri Sri Rahayu Sri Rahayu