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Achmad Muchayan
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achmad.muchayan@narotama.ac.id
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ijeeit@narotama.ac.id
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NAROTAMA UNIVERSITY, Indonesia AR HAKIM 51 SURABAYA JAWA TIMUR www.narotama.ac.id
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IJEEIT : International Journal of Electrical Engineering and Information Technology
Published by Universitas Narotama Surabaya
ISSN : 26152088     EISSN : 26152096     DOI : https://doi.org/10.29138/ijeeit.v3i2
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
is an open-access journal publishing original research from across all areas of the Electrical Engineering and Information Technology We offer our authors a highly respected home for their research. Partnering with our extensive network of expert peer reviewers, our editorial team provides rigorous, objective and constructive peer review, and will support you throughout the publication process. We led by the same ethical and editorial policy guidelines to ensure that all the research we publish is scientifically robust, original, and of the highest quality. We help your research reach more people and maximize its impact. As an open-access journal, we ensure that your work is immediately accessible and highly discoverable across a range of channels Focus and Scope IJEEIT publishes original research from all areas of the Electrical Engineering and Information Technology
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 62 Documents
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Exploration of the Evolution of SISGANIS: Analytical Intelligence Approach in Raw Material Inventory Management and Interactive Visual Analysis Cafe Rengganis Wiranto, Ferry; Rohim, Muhamat Abdul; Rachmawati, Lia
IJEEIT : International Journal of Electrical Engineering and Information Technology Vol 7 No 2 (2024): September 2024
Publisher : NAROTAMA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29138/ijeeit.v7i2.2918

Abstract

SISGANIS (Rengganis Management Information System), developed in 2023 by the ITS Mandala Jember team and granted intellectual property rights (EC002023118017), focuses on automating raw material stock balances and financial reporting. Despite its active use by Cafe Rengganis in Jember Regency, it remains a Basic Information System, concentrating primarily on transaction data. Consequently, it lacks accurate real-time inventory forecasts and interactive visual analyses. The research is driven by Cafe Rengganis's need to enhance raw material inventory management efficiency. Frequent issues with determining appropriate stock levels lead to stockouts and inaccurate records. This necessitates exploring an advanced SISGANIS for more effective operations. The research utilizes Exponential Smoothing, Decomposition Methods, and Machine Learning (ML)-based data transformation to improve historical data processing, identifying complex patterns and trends in inventory management. Adopting an AGILE approach, the research team comprising IT experts, accountants, and students ensures rapid response and continuous iteration. The goal is to successfully implement the new SISGANIS version, enhancing inventory management efficiency, predicting raw material needs, and providing interactive data visualization tools, ultimately optimizing Cafe Rengganis's operational performance and customer experience
IoT-Based Prototype for Parking Gate Security Monitoring and Customer Satisfaction Survey Dhaniswara, Erwin; Subagiyo, Subagiyo; Mudjanarko, Sri Wiwoho; Mayestino, Alexander Machicky; Hidayat, Dwi Taufik; Talakua, Eddy Lybrech
IJEEIT : International Journal of Electrical Engineering and Information Technology Vol 8 No 2 (2025): September 2025
Publisher : NAROTAMA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29138/ijeeit.v8i2.3436

Abstract

Digital transformation in parking systems is essential to improving operational efficiency, staff integrity, and customer satisfaction. PT Reska Multi Usaha (KAI Services) has implemented various technology-based parking systems such as Manless, Full Manless, Combo, and LPR. However, several locations still rely on manual supervision, which increases the risk of fraud and inaccurate overnight vehicle data. This study developed an Internet of Things (IoT)-based prototype system to monitor gate status and manage customer surveys automatically, with real-time data transmission to a centralized dashboard. The system utilizes gate position sensors, microcontrollers, and digital survey forms integrated with an online server. Test results show that the system operates effectively without manual input, with an average data latency of 1.57 seconds and sensor detection accuracy of up to 50 cm. The system has the potential to be integrated with the Early Warning System (EWS) Command Center to support safer and more responsive parking services.

Page 7 of 7 | Total Record : 62

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