BIG DATA ANALYTICS FOR SAFE AND SECURE CITY

• Main Author: Setiyono
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/45596
• Institution: Institut Teknologi Bandung

According to the UN around 68% of the world population in 2050 will live in urban areas. With the increasing population of the city every year, it will cause several problems that arise, among others, problems of security, health, education, traffic congestion, energy, and so on. Smart solutions are needed from the city government to overcome this problem. One solution is smart city. To realize a smart city one of the main challenges is the solution to the problem of security. Based on the results of a literature study, research on urban problems is still global in nature to get to smart cities. The research topic in this thesis is about one component of smart city, namely city safe and secure city. The method used in this study uses quantitative research methods. From this research topic, a literature study is conducted to find the focus and research problem that we want to study, namely how to design a model to find out the level of security of cities in Indonesia by utilizing big data through predictive analysis of people's perception sentiments on Twitter? In this study a security analysis of 25 cities in Indonesia will be conducted using primary data from the 2019 RKCI (Indonesian Smart Cities Rating) questionnaire in the security sector and secondary data from the big data analysis in the form of twitter sentiment analysis about the perceptions of citizens' security. The measurement of security indicators in this study uses the measurement of safe and secure city maturity level by adopting the Garuda Smart City Model (GSCM). The results of the prediction model of public perception sentiment analysis designed in this study in general are not much different from the results of the 2019 RKCI survey. The results of performance measurement of this model are for an Accuracy value of 80.10% while a precision value of 81.10% and a recall value by 82.62%. From the results of this study it was found that 5 cities were at the level of Integrative maturity (score 60 to 79), namely Tangerang, Kediri, Parepare, Probolinggo and Bogor, while the other 20 cities were at the Scattered level (score 40 to 59). The average score of big cities category in Indonesia in this study was 57.73, medium cities was 56.81 and small cities was 54.21.