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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control)
Suci Mutiara
Darmajaya Institute of Informatics and Business
Computer Science & IT

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Optimization of MSMEs promotion strategy using GIS with random forest algorithm and A-star algorithm Sulyono Sulyono; Suci Mutiara; Agus Rahardi; Sri Lestari; Yulmaini Yulmaini; Ruki Rizal Nul Fikri; Ali Syarifuddin
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 24, No 5: October 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v24i5.26692

Abstract

Micro, small, and medium enterprises (MSMEs) make a main contribution to improving a country’s economy, but it still faces various problems including limited market access, ineffective promotion, and lack of understanding in business profiles. The purpose of this study is to design a geographic information system (GIS) combined with the random forest (RF) algorithm and the A-star algorithm. The RF algorithm functions are to classify MSMEs. Meanwhile, the A-star algorithm is to recommend the shortest route to support accessibility. In addition, it is equipped with a dashboard and MSMEs profile as a reference for stakeholders in making MSMEs development policies and as information to the public in order to expand the reach of promotion in introducing MSMEs and attracting investors, thus optimizing MSMEs promotion strategies. In addition, the evaluation results of the classification model show an accuracy value of 99.6%, indicating that the model is able to predict very well, making it highly recommended for MSME classification.
Co-Authors Agus Rahardi Ali Syarifuddin Ruki Rizal Nul Fikri Sri Lestari Sulyono, Sulyono Yulmaini Yulmaini