Exploration of the Evolution of SISGANIS: Analytical Intelligence Approach in Raw Material Inventory Management and Interactive Visual Analysis Cafe Rengganis

Ferry Wiranto; Muhamat Abdul Rohim; Lia Rachmawati

doi:10.29138/ijeeit.v7i2.2918

Ferry Wiranto Institut Teknologi dan Sains Mandala
Muhamat Abdul Rohim
Lia Rachmawati

DOI: https://doi.org/10.29138/ijeeit.v7i2.2918

Keywords: Forecasting, Exponential Smoothing, Decomposition Methods, Interactive Visual Analysis, Raw Material Inventory

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

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