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Governmentality Practices in Community Empowerment: One Step to Create Economic Income and Social Protection in Pematang Johar Village, Deli Serdang Regency Mujahiddin, Mujahiddin; Badaruddin, Badaruddin; Lubis, Zulkifli; Daulay, Harmona
Jurnal Riset Multidisiplin dan Inovasi Teknologi Том 2 № 03 (2024): September 2024
Publisher : Pt. Riset Press International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59653/jimat.v2i03.1095

Abstract

Linking governmentality practices to community empowerment programs in rural areas is based on the Indonesian government's claim that the success of development in villages is due to the involvement of the central government in directing development planning in villages through the various technical regulations they issue. Village governments are only given space for elaboration and accommodation of regulations made by the central government based on local values, local potential, needs and interests of village communities. The existence of this space for elaboration and accommodation makes the practice of governmentality applicable in rural areas, namely giving freedom and authority to villages but at the same time directing them with various possible choices that are actually desired by the state. This article finds the operation of governmentality practices in the discourse of increasing economic welfare rationalized by the Pematang Johar Village Government for the community through the development of rice field tourism objects in their village. This discourse is able to change the village community's perception of the goals of village development, which until now have only been understood in terms of infrastructure development. Through this discourse, the village government is able to form empowered people; namely village people who are continuously trained in skills, corrected and disciplined. The self-adaptation that they carry out is of course aimed at increasing their capacity and quality from the status of the tasks they carry out daily in the rice field tourism which leads them to become economically prosperous.
COVID-19 pandemic and population density problem in Indonesia: transmigration policy as an alternative program Saleh, Arifin; Khadafi, Rizal; Nurmandi, Achmad; Mujahiddin, Mujahiddin; Saputra, Agung; Ritonga, Soritua; Hardiyanto, Sigit
Otoritas : Jurnal Ilmu Pemerintahan Vol 13, No 3 (2023): (December 2023)
Publisher : Department of Government Studies Universitas Muhammadiyah Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26618/ojip.v13i3.11961

Abstract

The objective of this study is to examine the associations between levels of population density and the transmission of COVID-19 in Indonesia. Descriptive analysis is employed to determine the data distribution of the response variable (dependent variable Y) as well as the independent variables X1 and X2. Therefore, inferential analysis is a quantitative technique that involves examining a sample in order to draw conclusions about a larger population. The present investigation has revealed a statistically significant positive connection (r = 0.954) between the incidence of COVID-19 patients and population density in Indonesia. The Model Summary provides the R value (Correlation Coefficient) of 0.959, indicating a strong positive correlation between the variables. Additionally, the multiple correlation coefficient r (Multiple R) is 0.920, which represents the determination index or the proportion of the influence of X on Y. Therefore, it can be asserted that 92% of COVID-19 cases are driven by population density and the number of individuals experiencing employment terminations, whilst the remaining 8% is affected by additional factors. The regression equation can be constructed from the Coefficients table in the following manner: The equation can be expressed as . The calculation of the Standard Error of the Estimate (SE) yields a value of 8151.076 or 8151. The standardized coefficient (Beta) of 1.381 represents the extent of association between the number of COVID-19 infection cases and population density.