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Serial crime recognition is a critical task. Usually, police officer investigates the serial crime behavior based on their heuristics, evidence or prior information from public. Sometimes, the police officer makes inadequate decision when handling the serial crime problems due to lack of preliminary study on relationship between serial crime and amenities. Therefore, this study explores k-means to identify pattern of surroundings area at serial comersial crime scene. In Malaysia, precisely Selangor, Wilayah Persekutuan Kuala Lumpur and Wilayah Persekutuan Putrjaya, a set data of serial crime including index and non-index, and its surroundings area at crime scene are being investigated. Experimental result shows that ‘ hot spot ’ amenities such as bank, commercial center, restorant, place of worship, resident and school are highly involved with three types of crime namely house breaking at night, day and robbery without firearm. Furthermore, radius distance with 0.2 km and 0.3 km between the crime scene location and its amenities at surroundings area captured from Safe City Monitoring System are also being evaluated and analyzed. Consequently, our finding helps the police to easily observe and prevent criminal behavior by assigning necessary human resource based on their ‘hot spot’ amenities.

jurnal teknologi/jurnal teknologi

AMENITIES SURROUNDING COMMERCIAL SERIAL CRIME PREDICTION AT GREATER VALLEY AND KUALA LUMPUR USING K-MEANS CLUSTERING/PENGECAMAN KEMUDAHAN AWAM SEKITAR LOKASI JENAYAH KORMESIAL BERSIRI DI LEMBAH KLANG DAN KUALA LUMPUR MENGGUNAKAN KAEDAH GUGUSAN K-MEANS