PENERAPAN DATA MINING DALAM MENEMUKAN POLA DATA ANGGARAN PENDAPATAN BELANJA DAERAH KOTA MALANG METODE FP-GROWTH

Abstract

Unraveling the intricate web of financial data in urban governance, this study employs cutting-edge data mining techniques to unearth budgetary patterns within the city of Malang. Utilizing the FP-growth algorithm, this research overcomes the challenges posed by data mining analysis, illuminating the trends within budgetary allocations. The ultimate goal is to develop a strategic blueprint for optimizing budget utilization. The study reveals compelling insights: to maximize revenue, there is a crucial need to augment allocations in employee expenses, capital investments, procurement of goods and services, as well as subsidies to regional governments and local villages. This research not only enriches our understanding of Malang's fiscal landscape but also offers actionable strategies for enhancing financial efficiency in urban administration.