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Literasi SWOT untuk meningkatkan partisipasi masyarakat dalam perencanaan pembangunan desa Rostiana, Endang; Saepudin, Tete; Murniati, Neni; Hermawan, Heri; Acuviarta
Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) Vol 6 No 3 (2023)
Publisher : University of Islam Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33474/jipemas.v6i3.19191

Abstract

Pengabdian kepada masyarakat (PkM) di Desa Harumansari Kecamatan Kadungora Kabupaten Garut PkM dilaksanakan dengan metode Service Learning dan memiliki dua tujuan. Tujuan pertama adalah memberikan pengetahuan dan pemahaman tentang metode analisis SWOT (Strengths, Weaknesses, Opportunities, and Threats) kepada perwakilan pemangku kepentingan, termasuk aparat desa Harumansari. Tujuan kedua adalah melakukan pendampingan kepada aparat desa dalam menggunakan metode SWOT secara sederhana untuk menentukan jenis strategi pembangunan ekonomi Desa Harumansari. Sebanyak 96% peserta mengerti dan memahami materi pelatihan yang diberikan dan mereka juga merasa yakin dapat menggunakan metode SWOT untuk mengidentifikasi aspek-aspek SWOT dalam pembangunan bidang ekonomi desa. Kegiatan pendampingan pengisian dan penilaian kuesioner SWOT dilakukan kepada aparat Desa Harumansari. Berdasarkan kuesioner yang diisi dan dianalisis dengan matriks SWOT menunjukkan strategi pembangunan ekonomi Desa Harumansari dapat bersifat agresif dengan menggunakan kekuatan internal untuk memanfaatkan peluang semaksimal mungkin. Hasil pendampingan sekaligus menjadi bahan evaluasi sejauhmana aparat Desa Harumansari dapat memahami dan mengaplikasikan metode SWOT sederhana dalam penyusunan rencana pembangunan desa.
Pola Spasial dan Determinan Ketimpangan Pendapatan di Indonesia Dian Novita Ramadani; Endang Rostiana; Gugum Mukdas Sudarjah
JIEP: Jurnal Ilmu Ekonomi dan Pembangunan Vol. 9 No. 1 (2026)
Publisher : PPJP ULM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jiep.v9i1.2971

Abstract

This study comparatively analyzes the spatial patterns and determinants of inter-provincial income inequality in Indonesia using the Theil Index for the years 2016 and 2023. Based on the Theil Index calculations, the level of inequality increased in 2023 compared to 2016. The Global Moran’s I test results reveal a significant positive spatial autocorrelation in both observation periods, confirming the existence of spatial dependence. The analysis proceeds with the Local Indicator of Spatial Association (LISA) and the Spatial Error Model (SEM). Specifically, the LISA mapping identifies regional polarization, wherein provinces with high inequality cluster together (High-High cluster) and are concentrated in Eastern Indonesia. Furthermore, the SEM estimations indicate that per capita GRDP and economic structure have a positive and significant effect on widening inequality. Conversely, formal labor exhibits a negative and significant effect in reducing inequality, while the Human Development Index (HDI) shows a negative but insignificant effect. Additionally, the significant spatial error coefficient (λ) confirms the presence of spatial dependence within the error component, indicating that unobserved shocks in one province generate spatial spillover effects on the inequality levels of its neighboring regions.
Total Factor Productivity Calculation of the Indonesian Micro and Small Scale Manufacturing Industry Endang Rostiana; Horas Djulius; Gugum Mukdas Sudarjah
EKUILIBRIUM : JURNAL ILMIAH BIDANG ILMU EKONOMI Vol 17 No 1 (2022): March
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24269/ekuilibrium.v17i1.2022.pp54-63

Abstract

The purpose of this research is to determine the total factor productivity (TFP) of Indonesia's micro and small-scale manufacturing industries. The production function estimation approach established by Levinsohn-Petrin as the basis for computing TFP is employed in this study, with value added as the dependent variable and the value of labor costs and capital value proxied by the value of investment as the independent variables. This study uses secondary data from the Central Statistics Agency (BPS), which includes 23 sub-sectors of Indonesia's micro and small scale manufacturing industries that are included in the 2-digit ISIC, with the exception of the ISIC code 19 sub-sector, and covers the years 2010 to 2019, excluding 2016. The TFP value in the micro-scale Indonesian manufacturing industry was often higher than the TFP value on the small scale, according to this study. This research also demonstrates that low-tech sub-sectors, such as the food processing industry, have low productivity. On a small size, the estimated TFP value shows a decreasing trend, but on a micro scale, the estimated TFP value indicates an increasing trend.