<![CDATA[The expansion of Indonesia’s digital economy has amplified the demand for privacy-preserving technologies, particularly in the e-commerce sector. This study explores the implementation of Differential Privacy (DP) to strike a balance between data utility and regulatory compliance. Through simulations involving BPS microdata, synthetic modeling via SmartNoise, and financial time series from Bank Indonesia, we applied calibrated DP mechanisms and evaluated performance using utility metrics (MAPE, MAE, AUC) across varying epsilon (ε) values. Results indicate that ε values between 1 and 3 offer optimal privacy-utility trade-offs, preserving analytical accuracy while ensuring compliance. The findings highlight SmartNoise’s usability and ISO 27559's role in promoting privacy by design. This work contributes a practical framework for DP adoption in Indonesia’s e-commerce sector, with broader relevance for Southeast Asia.]]>
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