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<![CDATA[ANALISIS PERBANDINGAN SEKTOR UNGGULAN TIGA KABUPATEN TERMUDA DI PROVINSI SUMATERA BARAT ]]>
<![CDATA[Putri Cicilia Agus Seppina]]>;
<![CDATA[Alpon Satrianto]]>
<![CDATA[ Journal of Economic, Bussines and Accounting (COSTING) Vol. 8 No. 2 (2025): COSTING : Journal of Economic, Bussines and Accounting ]]>
Publisher : <![CDATA[Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE) ]]>
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DOI: 10.31539/costing.v8i2.14601
<![CDATA[Penelitian ini bertujuan untuk mengetahui dan membandingkan sektor unggulan di tiga kabupaten termuda di Provinsi Sumatera Barat. Data yang digunakan dalam penelitian ini adalah data sekunder dari tahun 2016-2020 yang diperoleh dari Badan Pusat Statistik. Metode analisis yang digunakan adalah metode Location Quentient dan metode Shift Share Analysis. Hasil analisis data menunjukkan bahwa berdasarkan metode Location Quentient terdapat 4 sektor unggul dan berdasarkan metode ShiftShare Analysis terdapat 12 sektor unggul di Kabupaten Solok Selatan. Berdasarkan metode Location Quentient terdapat 7 sektor unggul dan berdasarkan metode ShiftShare Analysis terdapat 8 sektor unggul di Kabupaten Dharmasraya. Berdasarkan metode Location Quentient terdapat 2 sektor unggul dan berdasarkan metode ShiftShare Analysis terdapat 11 sektor unggul di Kabupaten Pasaman Barat. Selanjutnya Kabupaten Dharmasraya memiliki sektor unggulan paling banyak berdasarkan metode Location Quentient dan Kabupaten Solok Selatan memiliki sektor unggulan paling banyak berdasarkan metode ShiftShare Analysis.]]>
<![CDATA[PENGARUH MODAL MANUSIA TERHADAP KESEJATERAAN MASYARAKAT PROVINSI SUMATERA BARAT ]]>
<![CDATA[Leoni Amanda Istiazah]]>;
<![CDATA[Alpon Satrianto]]>
<![CDATA[ Journal of Economic, Bussines and Accounting (COSTING) Vol. 8 No. 3 (2025): COSTING : Journal of Economic, Bussines and Accounting ]]>
Publisher : <![CDATA[Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE) ]]>
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DOI: 10.31539/costing.v8i3.15249
<![CDATA[Penelitian ini bertujuan untuk menganalisis pengaruh modal manusia terhadap kesejahteraan masyarakat di Provinsi Sumatera Barat dengan menggunakan pendekatan regresi data panel. Data yang digunakan merupakan data panel tahunan kabupaten/kota di Sumatera Barat selama periode 2017–2023 yang bersumber dari Badan Pusat Statistik (BPS) dan Direktorat Jendral Perimbangan Keuangan (DJPK). Hasil penelitian menunjukkan bahwa modal manusia memiliki pengaruh positif dan signifikan terhadap peningkatan kesejahteraan masyarakat. Temuan ini menegaskan bahwa investasi dalam pembangunan modal manusia merupakan strategi efektif untuk mendorong pertumbuhan sosial-ekonomi di tingkat regional. Oleh karena itu, kebijakan yang mendukung peningkatan kualitas pendidikan dan kesehatan perlu menjadi prioritas dalam agenda pembangunan daerah.]]>
<![CDATA[PELATIHAN DIGITALISASI LAPORAN KEUANGAN UNTUK MENINGKATKAN KINERJA BUMDESMA SABANA KAMEK LKD ]]>
<![CDATA[Halkadri, Halkadri]]>;
<![CDATA[Mesta, Hendri Andi]]>;
<![CDATA[Satrianto, Alpon]]>
<![CDATA[ Jurnal Abdimas Sangkabira Vol. 5 No. 2 (2025): Jurnal Abdimas Sangkabira, Juni 2025 ]]>
Publisher : <![CDATA[Program Studi Diploma III Akuntansi Fakultas Ekonomi dan Bisnis Universitas Mataram ]]>
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DOI: 10.29303/abdimassangkabira.v5i2.1596
<![CDATA[Kegiatan pelatihan ini bertujuan untuk memberikan pemahaman kepada pengelola keuangan Bumdesma Sabana Kamek LKD Kecamatan Kamang Magek Kabupaten Agam Provinsi Sumatera Barat tentang penyusunan laporan keuangan BUMDesma yang dilakukan secara terkomputerisasi otomatisasi. Metode yang digunakan adalah ceramah, diskusi, tanya jawab dan pendampingan. Peserta yang mengikuti kegiatan berjumlah 10 orang terdiri atas direktur, sekretaris, bendahara, pengawas serta staf keuangan. Hasil kegiatan menunjukkan bahwa pengelola keuangan Bumdesma dapat memahami dan menyusun laporan keuangan dengan baik secara komputerisasi otomatisasi dengan baik sehingga menunjang untuk digitalisasi laporan keuangan. Dengan memiliki pemahaman tentang siklus akuntansi dan penyusunan laporan keuangan secara komputerisasi otomatisasi maka pengurus Bumdesma membuat keputusan jangka pendek dan jangka panjang yang lebih tepat sehingga berdampak pada kinerja Bumdesma yang semakin baik.]]>
<![CDATA[Analisis Efisiensi Bank Umum Konvensional di Indonesia ]]>
<![CDATA[Yewisa, Tania Dara]]>;
<![CDATA[Satrianto, Alpon]]>
<![CDATA[ Jurnal Informatika Ekonomi Bisnis Vol. 7, No. 2 (June 2025) ]]>
Publisher : <![CDATA[SAFE-Network ]]>
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DOI: 10.37034/infeb.v7i2.1130
<![CDATA[This study aims to analyze the efficiency level of conventional commercial banks in Indonesia based on asset classification during the 2019–2023 period. The method used is Data Envelopment Analysis (DEA) with a Constant Returns to Scale (CRS) approach. The sample consists of 29 banks, divided into two groups: 20 large-asset banks and 9 medium-asset banks. The input variables include fixed assets, equity, and operating expenses, while the output is net profit. The results show that large banks had a higher average efficiency than medium-sized banks. In 2023, the average efficiency score for large banks reached 0.7012, while medium-sized banks scored only 0.2917. The minimum efficiency scores for large and medium banks were 0.0475 and 0.0352, respectively. The percentage of large banks achieving optimal efficiency (DEA=1) ranged from 5% to 35%, while for medium banks it ranged from 5% to 22.2%. BCA and OCBC NISP consistently achieved efficiency and served as benchmarks for other banks. Differences in efficiency are influenced by business scale, technology adoption, and cost management. These findings provide a vital foundation for improving operational strategies and bank efficiency in Indonesia.]]>
<![CDATA[Analisis Efisiensi Bank Umum Konvensional di Indonesia ]]>
<![CDATA[Yewisa, Tania Dara]]>;
<![CDATA[Satrianto, Alpon]]>
<![CDATA[ Jurnal Informatika Ekonomi Bisnis Vol. 7, No. 2 (June 2025) ]]>
Publisher : <![CDATA[SAFE-Network ]]>
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DOI: 10.37034/infeb.v7i2.1130
<![CDATA[This study aims to analyze the efficiency level of conventional commercial banks in Indonesia based on asset classification during the 2019–2023 period. The method used is Data Envelopment Analysis (DEA) with a Constant Returns to Scale (CRS) approach. The sample consists of 29 banks, divided into two groups: 20 large-asset banks and 9 medium-asset banks. The input variables include fixed assets, equity, and operating expenses, while the output is net profit. The results show that large banks had a higher average efficiency than medium-sized banks. In 2023, the average efficiency score for large banks reached 0.7012, while medium-sized banks scored only 0.2917. The minimum efficiency scores for large and medium banks were 0.0475 and 0.0352, respectively. The percentage of large banks achieving optimal efficiency (DEA=1) ranged from 5% to 35%, while for medium banks it ranged from 5% to 22.2%. BCA and OCBC NISP consistently achieved efficiency and served as benchmarks for other banks. Differences in efficiency are influenced by business scale, technology adoption, and cost management. These findings provide a vital foundation for improving operational strategies and bank efficiency in Indonesia.]]>
<![CDATA[Analisis Determinan Ekspor Komoditas Utama Sumatera Barat ke Negara Mitra Dagang ]]>
<![CDATA[Novi, Olivia Putri]]>;
<![CDATA[Satrianto, Alpon]]>
<![CDATA[ Media Riset Ekonomi Pembangunan (MedREP) Vol. 2 No. 2 (2025): MedREP: Volume 2, No. 2, Juni 2025 ]]>
Publisher : <![CDATA[Universitas Negeri Padang ]]>
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<![CDATA[This study aims to analyze the influence of Gross Domestic Product (GDP), Distance, Inflation, Exchange Rate, and Export Prices on the export value of animal/vegetable fats and oils from West Sumatra. The method used in this research is panel data analysis covering seven partner countries over the period 2016–2022, using a Fixed Effect Model (FEM) approach. The dependent variable in this study is the export value of animal/vegetable fats and oils, while the independent variables consist of the partner countries. GDP, distance, inflation, exchange rate, and export prices. The results of the study indicate that the GDP of partner countries and export prices have a significant positive effect on the export value of animal/vegetable fats and oils from West Sumatra. In contrast, distance, inflation, and exchange rate have a significant negative effect on the export value of these commodities.]]>
<![CDATA[Analisis Efisiensi Belanja Sektor Publik Di Kabupaten/Kota Provinsi Sumatera Barat ]]>
<![CDATA[Mailina, Septia]]>;
<![CDATA[Satrianto, Alpon]]>
<![CDATA[ Media Riset Ekonomi Pembangunan (MedREP) Vol. 2 No. 2 (2025): MedREP: Volume 2, No. 2, Juni 2025 ]]>
Publisher : <![CDATA[Universitas Negeri Padang ]]>
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<![CDATA[This study aims to measure the level of efficiency of public sector spending in the education, health and economic sectors. The data used is panel data, namely data from 19 districts / cities in West Sumatra Province in 2018-2022. The data used is secondary data obtained from the Central Bureau of Statistics and the Directorate General of Fiscal Balance. This research uses the Data Envelopment Analysis method. Efficiency measurement in this study uses the assumption of Variable Return to Scale with output-oriented. The results showed (1) there was 1 city that had achieved perfect efficiency, 11 regencies/cities achieved high efficiency and 7 districts/cities achieved medium efficiency in the education sector, (2) there were 2 cities that had achieved perfect efficiency, and 17 regencies /cities achieved high efficiency in the health sector and (3) there were no districts/cities that had achieved perfect efficiency, 12 regencies /cities achieved high efficiency and 7 regencies /cities achieved medium efficiency in the economic sector.]]>
<![CDATA[ANALISIS DAYA SAING SEKTOR PARIWISATA KOTA PADANG ]]>
<![CDATA[Alwi, Farhan]]>;
<![CDATA[Satrianto, Alpon]]>
<![CDATA[ Media Riset Ekonomi Pembangunan (MedREP) Vol. 2 No. 2 (2025): MedREP: Volume 2, No. 2, Juni 2025 ]]>
Publisher : <![CDATA[Universitas Negeri Padang ]]>
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<![CDATA[This study aims to determine the growth of the tourism sector of Padang City compared to the reference area of West Sumatra and to find out what variable indicators are superior in determining the competitiveness of the tourism sector in Padang City, as well as to find out the position of the development of the competitiveness of the tourism sector against its comparative areasThe method used is quantitative. The object of this study is Padang City with Bukittinggi City and Pariaman City as a comparison, the analysis method in this study uses shift share analysis, composite index, and quadrant analysisThe results of this study show that the tourism sector of Padang City is experiencing faster growth and is able to be competitive with the same sector at the provincial level, variable indicators of production factors and demand factors are superior indicators and have good competitiveness for the tourism sector of Padang City, and Padang City is in Quadrant II in the position of the development of the competitiveness of the city's tourism sector Padang with its comparison area.The role of the government and the opportunities that have run effectively should continue to be improved through consistent supervision, advocative policy formulation, and transparent communication. The government is also expected to remain responsive to the needs of the community and conduct periodic evaluations of the programs carried out so that they remain relevant and have a positive impact.]]>
<![CDATA[MSME lending and its impact on the unemployment rate: Evidence from Indonesia ]]>
<![CDATA[Ulya MahaPutri, Ummi Khalida]]>;
<![CDATA[Satrianto, Alpon]]>
<![CDATA[ Optimum: Jurnal Ekonomi dan Pembangunan Vol. 14 No. 1 (2024) ]]>
Publisher : <![CDATA[Universitas Ahmad Dahlan ]]>
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DOI: 10.12928/optimum.v14i1.9259
<![CDATA[Micro, small, and medium enterprises (MSMEs) are business sectors that contribute positively to economic development and their contribution to national income. However, as the number of MSMEs increases but MSME faces several problems. The most prominent issue is the lack of capital owned by the entrepreneurs to develop their businesses. In lending, there are several things that need to be considered by creditors and debtors to maintain the intermediary function of the bank. By providing targeted credit, more workers can be absorbed so that Indonesia's unemployment rate continues to fall. This study using panel data regression. First model using the random effect model (REM) method and second model using the fixed effect model (FEM) method with a cross-section of 33 provinces in Indonesia and time series 2015-2022. The test results show that the DPK variable, the number of branches, and inflation have a positive and significant effect on total MSME lending and the NPL variable has no effect on total MSME credit. Furthermore, the total MSME lending variable and the economic growth rate have a negative significant effect on the unemployment rate. This research provides a deeper understanding of the factors that determine MSME lending and how they relate to the unemployment rate in 33 Indonesian provinces. It can also be used as a basis for formulating more effective policies related to MSME lending with the potential to reduce the unemployment rate.]]>
<![CDATA[Tourism sector in Bukittinggi: Analysis of tourism competitiveness before and after COVID-19 ]]>
<![CDATA[Syawal, Fadhilah]]>;
<![CDATA[Satrianto, Alpon]]>
<![CDATA[ Optimum: Jurnal Ekonomi dan Pembangunan Vol. 14 No. 2 (2024) ]]>
Publisher : <![CDATA[Universitas Ahmad Dahlan ]]>
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DOI: 10.12928/optimum.v14i2.9611
<![CDATA[The tourism industry, a crucial service sector, has been significantly impacted by the global pandemic, Covid-19. This impact has not only affected the development of tourism but also the regional economy. Bukittinggi, a key tourism city in West Sumatra, now more than ever, requires a competitive analysis to ensure its continuous growth. This research is aimed at analyzing and comparing Bukittinggi's tourism competitiveness before and after Covid-19. The research, a quantitative descriptive study with an exploratory research design, utilizes Competitiveness Monitor analysis. The data, sourced from BPS, BKD, and Bukittinggi Tourism Office, is secondary. The research results present the comparative results of the Tourism Competitiveness Analysis of Bukittinggi city as follows: a). PCI before Covid-19 was greater than after Covid-19; b). EI competitiveness before Covid-19 was higher than after Covid-19; c). HTI after Covid-19 was higher than before Covid-19; d). IDI after Covid-19 is higher than before Covid-19; e). OI after Covid-19 is higher than before Covid-19; 6). HRI after Covid-19 is higher than before Covid-19; f). TAI Value competitiveness index after Covid-19 is higher than before Covid-19; g). SDI before and after Covid-19 is equal. This research explains comparison of Bukittinggi's tourism competitiveness before and after Covid-19. The contribution of study are: a). consideration on improving tourism sites; b). Tourism management needs to be carried out in an integrated manner; and c). The government is expected to conduct more repairs and maintenance on tourism locations to increase visitor comfort when traveling.]]>
