Classification Model of Exporter Maturity Levels Based on the Comparison of National FOB Values and MSME Production Capacity

Abstract

This study aims to develop a classification model for exporter maturity levels by considering the comparison between national Free on Board (FOB) values and the production capacity of Micro, Small, and Medium Enterprises (MSMEs). The research is motivated by the varying levels of readiness among businesses to enter export markets, highlighting the need for a data-driven approach to objectively classify exporter maturity. The study employs the CRISP-DM (Cross Industry Standard Process for Data Mining) methodology, including business understanding, data understanding, data preparation, modeling, evaluation, and deployment stages. The dataset consists of FOB export values, product categories, and MSME production capacity indicators. Classification algorithms are applied to categorize exporters into low, medium, and high maturity levels. The results indicate that the combination of FOB values and production capacity effectively distinguishes exporter maturity classes, with the model achieving strong performance based on accuracy, precision, recall, and F1-score metrics. These findings are expected to support policymakers in designing export-readiness development programs for MSMEs and assist businesses in understanding their position within the national export ecosystem. Overall, the CRISP-DM-based data mining approach contributes to enhancing the competitiveness of Indonesian exporters.