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Menakar Keefektifan Mandatory Spending Bidang Pendidikan Hadiyanto Hadiyanto; Teguh Dwi Prasetyo; Dian Merini; Febrian Yalisman
Indonesian Treasury Review: Jurnal Perbendaharaan, Keuangan Negara dan Kebijakan Publik Vol 7 No 2 (2022): Indonesian Treasury Review: Jurnal Perbendaharaan, Keuangan Negara dan Kebijakan
Publisher : Direktorat Jenderal Perbendaharaan, Kementerian Keuangan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33105/itrev.v7i2.626

Abstract

This study aims to map the distribution of education inputs (expenditures) and education outcome indicators, as well as analyze the impact of education expenditure on education outcome indicators in Indonesia. The mapping analysis of expenditure distribution and education outcome indicators was carried out by using biplot analysis. Meanwhile, the impact of education expenditure on outcome indicators was analyzed using panel data regression. The results of the Biplot analysis show that Education Expenditure per Capita has a positive correlation with outcome indicators. In several provinces, the Teacher-Student Ratio (RGM) has a positive correlation with outcome indicators, especially the Gross Enrollment Rate (GER) indicator for SMA level. The results of panel data regression analysis show that School Operational Assistance (BOS), Teacher Allowances, Physical Special Allocation Funds (DAK Fisik) for Education, and Number of Schools have a positive and significant impact on the Net Enrollment Rate (APM) and Compulsory Education and Average Years of Schooling (RLS). This study recommends that the government need to consider education outcome indicators per province in allocating the budget of education expenditure and to ensure the distribution ratios as well as teacher quality to improve the quality of education in each province.
Penumpukan Belanja di Akhir Tahun Berdasarkan Perspektif Karakteristik Belanja Tommi Helmiwan; Febrian Yalisman; Risky Utama; Norma Suci Prihartini; Priyo Arif Wicaksono
Jurnal Manajemen Perbendaharaan Vol 3 No 1 (2022): Jurnal Manajemen Perbendaharaan
Publisher : Direktorat Sistem Perbendaharaan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3970.191 KB) | DOI: 10.33105/jmp.v3i1.425

Abstract

Government’s year-end spending spikes is a yearly phenomenon that could reduce the government expenditure quality. Therefore, it is necessary to anticipate through identifying the characteristics of expenditure which is in principle can be accelerated and prevent accumulation. This study aims to measure the variable components of government agency’s expenditure which can be used as an initial step in anticipating the year-end spending spikes using Random Forest Regression algorithm machine learning method with a Feature Importance approach. The results of the study shows that several expenditure variables that should not spike at the end of the year tends to accumulate at the end of the year while at the same time confirms procrastinating behavior. Through the development of existing models, the stakeholders can take advantage of these tools as an early warning on potential spike in spending at end of the year and map out recommendations for spending acceleration to realize quality spending.