Article Per Year (5 Year)
p-Index From 2021 - 2026
2.439
P-Index
This Author published in this journals
All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi Journal of Innovation and Applied Technology Jurnal Teknologi Informasi dan Ilmu Komputer Science and Technology Indonesia Jurnal Penelitian Pendidikan IPA (JPPIPA) BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Journal of Multidisciplinary Applied Natural Science
Eni Sumarminingsih
brawijaya university
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Energy Engineering Environmental Science Immunology & microbiology Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Transportation

Published : 16 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Journal of Multidisciplinary Applied Natural Science

 1 
Spatial Clustering with Autocorrelation-Based Weighting for Regional Socio-Economic Pattern Analysis: A Case Study of East Java Fitriani, Rahma; Sumarminingsih, Eni; Amaliana, Luthfatul
Journal of Multidisciplinary Applied Natural Science Vol. 6 No. 2 (2026): Journal of Multidisciplinary Applied Natural Science
Publisher : Pandawa Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47352/jmans.2774-3047.345

Abstract

Clustering, an unsupervised machine learning technique, categorizes objects into groups based on shared characteristics. When applied to spatial data, the assumption of independence is often violated due to similarities among adjacent regions—a phenomenon known as spatial autocorrelation. To address this, spatial clustering incorporates both non-spatial attributes (e.g., socio-economic indicators) and spatial attributes (e.g., geographic location), with spatial attributes weighted based on their influence in defining clusters. In regional economic development, creating clusters that are both spatially coherent and socio-economically homogeneous is critical for effective policy design. Strong interactions among neighboring regions can promote more integrated and balanced growth. This study proposes a spatial clustering framework that optimizes spatial attribute weighting according to the degree of spatial autocorrelation. A simulation study using 2023 data from East Java’s 38 regencies/municipalities determines optimal weights under varying spatial dependence levels. The results show that optimal spatial weights increase with the number of clusters and vary according to the strength of spatial autocorrelation. Applied to East Java, the method produced clusters with higher socio-economic homogeneity than official zones, though with reduced spatial contiguity. These findings highlight the importance of adaptive, autocorrelation-aware clustering to improve regional planning and support more evidence-based development strategies.
Co-Authors Achmad Efendi Ani Budi Astuti Asaliontin, Lisa Atiek Iriany Elfrida Ratnawati Fernandes, Adji Achmad Rinaldo Hamdan, Rosita Henny Pramoedyo Iriany , Atiek Jannah, Berliana Kalangi, Olyvia Maria Lusia, Dwi Ayu Luthfatul Amaliana, Luthfatul Mashfia, Fidia Raaihatul Maulana, Eka Dani Melanwati, Rinda Lolita Menufandu, Dahlia Gladiola Rurina Ni Wayan Surya Wardhani Nurdin, Muhammad Rafi Hasan Nurjannah Rahma Fitriani Rotchildi, Gusti Ayu Putu Rawi Sa'diyah, Nur Kamilah Semathea, Karen Sepriadi, Hanifa Shofa, Elvo Ramadhan Solimun, Solimun Sovia, Nabila Ayunda Suci Astutik Ullah, Mohammad Ohid Ullah, Muhammad Ohid Waego Hadi Nugroho Wahyuni, Djihan