<![CDATA[Optimization of State Property (BMN) requires an efficient valuation process to support the utilization of idle or underused government assets. This study aims to identify the factors that affect the rental value of Automated Teller Machine (ATM) placement in Medan City and to provide empirical support for the List of Rental Valuation Components (DKPS) as a basis for desktop valuation. The study uses a quantitative associative design with saturated sampling of 38 ATM rental observations from 2024 in the Medan KPKNL work area. Data were analyzed using multiple linear regression with EViews 12, supported by residual normality, serial-correlation, heteroscedasticity, multicollinearity, and model-specification diagnostics. The regression model explains 85.42% of the variation in ATM placement rental value (R-squared = 0.8542; adjusted R-squared = 0.8002), and the simultaneous F-test is significant (F = 15.81954; p < 0.001). At the 5% significance level, Transaction Year and ATM Room Type have statistically significant positive effects on rental value, while Rental Period is marginal but not significant (p = 0.0537). Distance to the CBD, Rental Object, Accessibility, Shopping Center Allocation, Commercial Provisions, Public Service Designation, and Road Type are not statistically significant. These findings indicate that the tested factors are jointly relevant, but their individual contributions differ. Practically, the model can support a more evidence-based DKPS and desktop valuation process for Government Appraisers at KPKNL Medan, subject to validation with broader data]]>
Copyrights © 2025
