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All Journal Jurnal Litbang Kota Pekalongan Jurnal Archipelago
Apriliawan, Yohanes Eki
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Public Health Social Sciences Other

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Inklusi Keuangan dalam Pengentasan Kemiskinan di Wilayah Kepulauan: Studi Kasus Provinsi Kepulauan Riau Apriliawan, Yohanes Eki
Jurnal Archipelago Vol 3 No 01 (2024): Jurnal Archipelago
Publisher : Badan Perencanaan, Penelitian dan Pengembangan Pemerintah Provinsi Kepulauan Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69853/ja.v3i01.117

Abstract

This research examines the importance of accessibility to financial infrastructure in efforts to alleviate poverty in the archipelagic region of the Riau Islands Province. The geographical condition consisting of numerous islands poses unique challenges in providing equitable access to financial services. Utilizing the Spatial Error Model and granular data down to the village/sub-district level, this study finds that the number of Banks and the presence of Automatic Teller Machines have a significant influence on the Global Relative Deprivation Index (GRDI) of poverty. The more Banks and ATMs in an area, the lower the poverty level tends to be. However, the accessibility of financial infrastructure in the Riau Islands is still uneven, especially in rural areas that have higher poverty rates. Therefore, the recommended policy measures include expanding Bank networks and placing ATMs in rural areas, innovating financial services tailored to the archipelagic conditions, improving financial literacy and inclusion among the community, developing digital finance, as well as improving inter-island transportation infrastructure. These recommendations are expected to broaden access to financial services and contribute to poverty alleviation efforts in Riau Islands Province.
Pola Spasial Aksesibilitas Fasilitas Publik Kota Pekalongan: Pendekatan Grid dan Machine Learning Apriliawan, Yohanes Eki
JURNAL LITBANG KOTA PEKALONGAN Vol. 22 No. 2 (2024)
Publisher : Badan Perencanaan Pembangunan, Penelitian dan Pengembangan Daerah (Bappeda) Kota Pekalongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54911/litbang.v22i2.959

Abstract

This study analyzes infrastructure accessibility patterns in Pekalongan City using a grid-based approach and machine learning methods. By integrating data from BPS, OpenStreetMap, and ESRI 2023, the research employs 100m × 100m grid analysis units to measure accessibility to public facilities such as education, healthcare, and commerce. Analysis using three clustering methods (K-Means, Bisecting K-Means, and Agglomerative) identifies three distinctive accessibility patterns. The first cluster (40.29%) demonstrates optimal accessibility with high road density, predominantly in the city center. The second cluster (31.64%) exhibits moderate accessibility, characterizing transitional areas. The third cluster (32.90%) shows the lowest accessibility, particularly in southern and coastal regions. Machine learning modeling using Catboost achieves the highest accuracy with a logloss value of 0.0091, confirming distance to healthcare and commercial facilities as key determinants of accessibility. These findings provide empirical foundations for more targeted infrastructure development, with policy recommendations tailored to each cluster's characteristics. The developed methodology offers a novel approach to urban accessibility analysis that can be replicated in other cities with similar characteristics.
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