Subdistrict Welfare Level Ranking in Semarang City Using Hybrid Entropy-EDAS Method

Authors

  • Tan Bagas Endrihartono Sistem Informasi, Fakultas Teknologi Informasi & Komunikasi, Universitas Semarang, Semarang, Indonesia
  • Isa Ghani Al-Hadid Sistem Informasi, Fakultas Teknologi Informasi & Komunikasi, Universitas Semarang, Semarang, Indonesia
  • Prind Triajeng Pungkasanti Sistem Informasi, Fakultas Teknologi Informasi & Komunikasi, Universitas Semarang, Semarang, Indonesia

DOI:

https://doi.org/10.36080/idealis.v9i2.3700

Keywords:

Decision Support System, EDAS, Entropy, Ranking, Social Welfare

Abstract

Sustainable regional development in Semarang City faces challenges regarding unmapped social welfare disparities and uneven infrastructure distribution across its 16 districts. Conventional assessment methods often suffer from subjective bias and fail to capture multidimensional data complexity, potentially leading to misallocated resources. This research aims to objectively analyze and rank district welfare levels using a Decision Support System (DSS) approach, assisting local government in accurately prioritizing development strategies. The systematic research stages encompass problem identification, dataset collection, objective weighting using the Entropy method, alternative ranking using the Evaluation Based on Distance from Average Solution (EDAS) method, and final result analysis. The hybrid framework utilizes Entropy to determine objective weights for five critical criteria (number of households, population size, healthcare facilities, stunting cases, and school facilities) based on data variation, eliminating human error. Meanwhile, EDAS evaluates district performance by calculating positive and negative distances from the average solution. Results reveal sharp inequality; Pedurungan District achieved the top rank (0.935), reflecting an optimal balance between public facilities and population needs. Conversely, Semarang Utara District ranked last (0.058), primarily driven by high stunting incidence as a major cost factor. The integrated Entropy-EDAS model provides a robust scientific basis for policymakers to effectively target budget allocation and stunting reduction programs in disadvantaged areas.

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References

[1] A. F. Nashrullah, I. N. K. W. Yudha, R. D. Mahardhika, A. T. Damaliana, and S. S. M. Waras, "Klasifikasi tingkat kesejahteraan kabupaten/kota di Jawa Barat, Jawa Tengah, dan Jawa Timur menggunakan regresi logistik multinomial," Emerging Statistics and Data Science Journal, vol. 3, no. 3, pp. 711–715, 2025. Available: https://doi.org/10.20885/esds.vol3.iss.3.art23. [Accessed: 09-Jun-2026]

[2] M. T. W. Pangesti, B. Ardianto, and P. T. Pungkasanti, "Penentuan daerah prioritas pembangunan di Jawa Tengah menggunakan metode Entropy dan TOPSIS," DINAMIK, vol. 30, no. 2, pp. 160–163, 2025. Available: https://doi.org/10.35315/dinamik.v30i2.10129. [Accessed: 09-Jun-2026]

[3] A. N. I. Muna and R. Yotenka, "Penerapan algoritma K-Means clustering untuk mengelompokkan kecamatan di Kabupaten Grobogan menurut tingkat kesejahteraan keluarga tahun 2020," Emerging Statistics and Data Science Journal, vol. 1, no. 3, pp. 290–293, 2023. Available: https://doi.org/10.20885/esds.vol1.iss.3.art36. [Accessed: 09-Jun-2026]

[4] Badan Pusat Statistik Kota Semarang, Indikator Kesejahteraan Rakyat Kota Semarang 2024. Semarang: Badan Pusat Statistik Kota Semarang, 2024. Available: https://semarangkota.bps.go.id/id/publication/2024/09/02/dac67b7000f5e80b7c25b4d9/indikator-kesejahteraan-rakyatkota-semarang-2024.html. [Accessed: 09-Jun-2026]

[5] Badan Pusat Statistik Kota Semarang, Data Strategis Kota Semarang 2023. Semarang: Badan Pusat Statistik Kota Semarang, 2023. Available: https://semarangkota.bps.go.id/id/publication/2023/04/21/6f1a8892387104318405ba52/data-strategis-kota-semarang-2023.html. [Accessed: 09-Jun-2026]

[6] H. Priyono, Susliansyah, H. Sumarno, L. Maulida, and F. Indriyani, "Pemilihan minuman yang banyak terjual dengan metode Evaluation Based on Distance from Average Solution (EDAS)," Remik: Riset dan E-Jurnal Manajemen Informatika Komputer, vol. 7, no. 3, pp. 1428–1437, 2023. Available: https://doi.org/10.33395/remik.v7i3.12658. [Accessed: 09-Jun-2026]

[7] N. W. E. R. Dewi, K. F. Danamastyana, and I. M. S. Putra, "Penerapan metode SAW dalam sistem pendukung keputusan untuk menentukan kelayakan tempat praktik kerja lapangan," Idealis: Indonesia Journal Information System, vol. 6, no. 2, pp. 146–155, 2023. Available: https://doi.org/10.36080/idealis.v6i2.3008. [Accessed: 09-Jun-2026]

[8] Rahmawati, Y. S. Hanifa, D. Juliansyah, S. Fadjarajani, and C. Darmawan, "Analisis ketimpangan pembangunan fasilitas kesehatan di Kecamatan Karangnunggal Kabupaten Tasikmalaya," Jurnal Multidisiplin Ilmu Akademik, vol. 2, no. 5, pp. 659–668, 2025. Available: https://doi.org/10.61722/jmia.v2i5.6812. [Accessed: 09-Jun-2026]

[9] Badan Pusat Statistik Kota Semarang, Statistik Kesejahteraan Rakyat Kota Semarang 2024. Semarang: Badan Pusat Statistik Kota Semarang, 2024. Available: https://semarangkota.bps.go.id/id/publication/2024/12/13/30279b457ff9422239a661b0/statistik-kesejahteraan-rakyatkota-semarang-2024.html. [Accessed: 09-Jun-2026]

[10] Setiawansyah, "Combination of EDAS method and Entropy weighting in the selection of the best customer service," CHAIN: Journal of Computer Technology, Computer Engineering and Informatics, vol. 2, no. 3, pp. 107–119, 2024. Available: https://doi.org/10.58602/chain.v2i3.144. [Accessed: 09-Jun-2026]

[11] A. Yudhistira, "Penerapan metode Simple Additive Weighting dan pembobotan Entropy untuk penentuan teknisi terbaik," Journal of Artificial Intelligence and Technology Information (JAITI), vol. 2, no. 3, pp. 143–152, 2024. Available: https://doi.org/10.58602/jaiti.v2i3.133. [Accessed: 09-Jun-2026]

[12] A. Syahputra, A. Diana, and D. Achadiani, "Penerapan metode Analytical Hierarchy Process dan Simple Additive Weighting untuk pemilihan supplier toko beras," Idealis: Indonesia Journal Information System, vol. 7, no. 2, pp. 219–229, 2024. Available: https://doi.org/10.36080/idealis.v7i2.3169. [Accessed: 09-Jun-2026]

[13] I. S. Sinambela, P. Uvaira, and A. Putri, "Implementasi metode Entropy dan TOPSIS dalam pemilihan dosen pembimbing skripsi mahasiswa Teknik Informatika Universitas Malikussaleh," Suliwa: Jurnal Multidisiplin Teknik, Sains, Pendidikan dan Teknologi, vol. 2, no. 3, pp. 205–216, 2025. Available: https://doi.org/10.62671/suliwa.v2i3.88. [Accessed: 09-Jun-2026]

[14] D. P. Indini, T. A. Siregar, and D. P. Utomo, "Implementasi metode EDAS dalam penilaian kinerja dosen pada masa pandemi Covid-19 dengan pembobotan Entropy," Journal of Informatics, Electrical and Electronics Engineering (JIEEE), vol. 3, no. 2, pp. 190–202, 2023. Available: https://doi.org/10.47065/jieee.v3i2.1613. [Accessed: 09-Jun-2026]

[15] E. Hermawan and E. T. Siregar, "Penerapan metode EDAS dalam penentuan karyawan yang layak mendapatkan insentif pada CV. Roda Andalas Pratama menggunakan pembobotan ROC," Jurnal JUREKSI (Jurnal Rekayasa Sistem), vol. 2, no. 3 A, pp. 1678–1688, 2024. Available: https://kti.potensi-utama.org/index.php/JUREKSI/article/view/1570. [Accessed: 09-Jun-2026]

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Published

07/31/2026

How to Cite

[1]
T. B. Endrihartono, I. G. Al-Hadid, and P. T. Pungkasanti, “Subdistrict Welfare Level Ranking in Semarang City Using Hybrid Entropy-EDAS Method”, IDEALIS, vol. 9, no. 2, pp. 237–246, Jul. 2026.