Linear mixed model approach: The effect of poor people & unemployment rate on various types of crime in 34 provinces in Indonesia - Atmadi; Nieldy R Tarigan; I Putu Aditya Brama Putra Cakra Negara; Najlaa Syalaisa; Muhammad Iqbal Al-Banna Ismail (International Journal of Applied Mathematics, Sciences, and Technology for National Defense, 2024)
Currently, Indonesia faces serious challenges related to increasing crime rates throughout the country. Various types of crime, such as increasing drug cases, increasingly concerning violations of decency, and disturbing acts of fraud, embezzlement, and corruption, have become a major concern for society and the government. In this context, this research plays an important role in efforts to understand the factors that drive the growth of crime and pursue the vision and mission of Indonesia Emas 2045, which sets targets to reduce poverty to reach zero percent. The main focus of the research is to link poverty and unemployment rates with three key types of crime that affect Indonesia's future. In this study, we try to understand how poverty rates and unemployment rates affect these types of crime in 34 provinces in Indonesia. The study used a statistical method called Linear Mixed Model with the support of R software. Of the 27 models analyzed, several models had a significant impact. The data used in this study was obtained from the Central Statistics Agency (BPS). The results of this study provide valuable insights into the factors influencing crime in Indonesia, which in turn can be used as a basis for designing more effective policies in an effort to achieve the vision and mission of Indonesia Emas 2045.