Smart System Model for Market Matching Recommendations for Export Destination Countries for MSMEs
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Abstract
Export is one way to improve the performance and growth of the MSME business. However, entering the export market is not as easy as one might think. MSMEs have to consider many factors such as regulatory requirements of the destination country, consumer preferences, and competition with local producers in the destination country. In addition, some of the obstacles to the export of MSME products are slow product turnover in importing countries because product stocks do not sell out immediately in these countries and sometimes reach the expiration date. The number of Indonesian MSMEs has reached 65.5 million, which is the largest in ASEAN countries. In addition, the contribution of MSMEs is recorded at around 61% of the national PDP and absorbs 97% of the total workforce in 2021. To assist MSMEs in choosing export destination countries, an intelligent system is needed that can recommend the right destination countries based on the characteristics of MSME products. As for how to determine the Export Destination country by using one of them based on the Trademap site. The urgency of this research aims to build an intelligent system model based on machine learning using the KNN method to recommend the right export destination countries for MSMEs. This machine learning-based intelligent system model is expected to be one of the solutions for MSMEs to effectively expand their markets abroad. This research is also expected to contribute to the development of an intelligent system that can assist MSMEs in choosing the right export destination countries and increasing export effectiveness. The results showed an accuracy rate of 99%, with a precision level of 100%, 100% recall, 100% f1-score.
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