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All Journal Journal of Management and Informatics JIMEB: Jurnal Ilmiah Manajemen, Ekonomi dan Bisnis
Nayyiroh, Frida Ulfatun
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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Measuring the forecast accuracy in retail MSMEs: A comparative analysis between AI and traditional methods in the era of digital selling Hikmah, Nur; Fauzi, Achmad; Nayyiroh, Frida Ulfatun
Journal of Management and Informatics Vol. 4 No. 1 (2025): April Season | JMI: Journal of Management and Informatics
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jmi.v4i1.166

Abstract

Accurate sales forecasting is essential for retail Micro, Small, and Medium Enterprises (MSMEs) to optimize operations and inventory planning in the digital economy. This study compares the forecasting accuracy between Artificial Intelligence (AI)-based methods (Random Forest, Decision Tree) and traditional techniques (Moving Average, Exponential Smoothing) using 3,600 transaction records from five retail MSMEs over three months. A quantitative experimental approach was employed to evaluate model performance under real-world conditions, including market fluctuations and seasonal anomalies. Evaluation metrics include Mean Absolute Percentage Error (MAPE), Root Mean Squared Error (RMSE), and cross-validation techniques. The findings indicate that the Random Forest model achieves superior accuracy (MAPE = 8.5%) compared to traditional methods (MAPE = 15.2%). Explainable AI (XAI) using SHAP and LIME further enhances transparency and managerial trust. Although traditional methods offer faster computation and ease of interpretation, AI-based models show resilience against unpredictable sales patterns. This research recommends hybrid adoption strategies that balance predictive power with interpretability for MSMEs with limited technical capacity. The results contribute to the discourse on digital transformation and intelligent forecasting in the MSME sectors.
Shadow Economy Management Strategies in Digital Business Ecosystems Fauzi, Achmad; Nayyiroh, Frida Ulfatun; Aisyah, Siti; Laila, Nur; Abadi, Fitria
Jurnal Ilmiah Manajemen, Ekonomi dan Bisnis Vol. 4 No. 1 (2025): JIMEB
Publisher : Universitas Sains dan Teknologi Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/9c3bwh39

Abstract

In the form of an enormous shadow economy that lies outside the purview of formal regulations, the thriving digital economy of Indonesia is hesitant in traversing its path. This research will survey the strategy for managing informal activities in the digital business ecosystem, based on a survey of 300 respondents and interviews with 12 informants from five cities. The results revealed that 67% of participants engage in informal businesses, especially in e-commerce (38%), the gig economy (29%), and informal online services (21%). The logistic regression identified high legalization costs, low incentives, and a negative perception of the government as the key variables driving informality. Lower digital literacy was associated with lower informality, but the effect was not statistically significant. The research proposes a framework comprising three pillars to support formalization: digital platform governance, socioeconomic incentives, and data-driven technologies. The findings here inform the formulation of candidate policies for an inclusive, equitable, and sustainable digital economy in Indonesia.
Co-Authors Abadi, Fitria Achmad Fauzi Nur Hikmah NUR LAILA Siti Aisyah