<![CDATA[This study investigates comfort in public open spaces in Bandung by linking measured environmental conditions with visitor perceptions collected through questionnaires. Logistic regression was applied to model the relationship between the two data sets. The model achieved good discriminatory power for predicting comfort, with Area Under the Curve (AUC) of 0.752, accuracy of 0.679, precision of 0.884, and sensitivity of 0.686. Five parameters emerged as significant predictors of comfort: L90, relative humidity, DGI, wind speed, and temperature. Higher comfort is associated with lower values of L90, DGI, and temperature, while increasing relative humidity and wind speed improves comfort. These results confirm that overall comfort in outdoor urban environments arises from multisensory interactions. Understanding these interactions provides urban planners and architects with a practical basis for developing strategies to improve the quality and livability of public open spaces.]]>
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