Geo-demographic analysis (GDA) studies the attributes of population demographic based on location, using spatially explicit analytical approaches. Fuzzy Geographically Weighted Clustering (FGWC), a variant of Fuzzy C-Means (FCM), has been serving as the state-of-the-art in Geo-demographic Analysis. FGWC is an effective algorithm, but sensitive to initialization when the random selection in center points makes iterative process falling into the local optimal solution easily. Artificial Bee Colony (ABC), one of metaheuristic algorithms is usually used as a global optimization tools. This research aims to propose a integration design of ABC based optimization and FGWC for improving geo-demographic clustering accuracy. Keywords—clustering; fuzzy geographically weighted clustering; geo-demographic analysis; artificial bee colony I. INTRODUCTION Geo-demographic analysis (GDA) studies the attributes of population demographics based on location, using spatially explicit analytical approaches [1]. GDA is an important tool to explore the underlying rules from data, and is widely applied to support effective development policies [2].