PROPOSED INFORMATION SYSTEMS AND DATABASE MANAGEMENT TO SUPPORT EFFECTIVE INVENTORY MANAGEMENT WITH PREDICTIVE INVENTORY FEATURES FOR MSMES
Micro, Small, and Medium Enterprises (MSMEs) are vital to Indonesia’s economy, contributing 61.1% to the GDP and employing 97% of the workforce. Despite their importance, MSMEs face challenges in managing inventory efficiently. Many still rely on manual inventory systems, leading to inefficiencies,...
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| Format: | Theses |
| Language: | Indonesia |
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| Online Access: | https://digilib.itb.ac.id/gdl/view/85744 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Micro, Small, and Medium Enterprises (MSMEs) are vital to Indonesia’s economy, contributing 61.1% to the GDP and employing 97% of the workforce. Despite their importance, MSMEs face challenges in managing inventory efficiently. Many still rely on manual inventory systems, leading to inefficiencies, errors, and high operational costs. Digitalization is crucial to help MSMEs overcome these challenges and improve operations. This research addresses the need for a digital inventory management system tailored to MSMEs.
The main issue is the inefficiency of inventory management within MSMEs, stemming from their reliance on manual processes, which leads to inaccurate stock levels, procurement delays, and financial losses. The lack of an integrated system capable of providing real-time data, predictive analytics, and accurate forecasting compounds this problem. This research aims to design a digital inventory management solution to enhance MSMEs' efficiency and reduce operational costs.
This research uses a qualitative approach with the System Development Life Cycle (SDLC) methodology. Primary data was gathered through interviews with 30 MSME owners in West Java, focusing on their inventory practices. Secondary data from relevant literature supported system design. A sample of 30 respondents was deemed sufficient to represent MSME challenges. The data was analyzed to identify gaps and develop a solution integrating predictive inventory features and real-time data management.
The findings show that MSMEs face key challenges such as manual data entry, lack of real-time information, and inefficient procurement processes. The proposed inventory management system, designed using the SDLC approach, addresses these issues by incorporating predictive analytics, real-time synchronization, and a user-friendly interface. The system offers improved accuracy, reduced operational costs, and enhanced decision-making, demonstrating that digital solutions can significantly improve MSMEs' efficiency.
The proposed system can be implemented in MSMEs, with development and testing estimated to take two months. Although the system is user-friendly, additional training and support will be necessary for successful adoption. The implementation does not require major organizational changes, though further research may be needed to refine predictive algorithms for specific industries. Once implemented, the system is expected to enhance inventory accuracy and operational efficiency.
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