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All Journal Prosiding Seminar Nasional Official Statistics
Shafira, Hervira Nur
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Humanities Computer Science & IT Economics, Econometrics & Finance Social Sciences

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Perbandingan Agglomerative Nesting dan K-Means untuk Klasterisasi Ketimpangan Gender berdasarkan Dimensi Kesehatan Reproduksi Raihannabil, Syfriza Davies; Ilyas, Hilmi Malika Atim; Shafira, Hervira Nur; Riani, May Alya; Hastin, Nadya Noor; Siregar, Tiara Khorijah Hamid
Seminar Nasional Official Statistics Vol 2024 No 1 (2024): Seminar Nasional Official Statistics 2024
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2024i1.1977

Abstract

Gender inequality in Indonesia is ranked 4th out of 11 ASEAN countries with key problems such as high maternal mortality rates and teenage births. Indonesia ranks 3rd with the highest maternal mortality rate in Southeast Asia. Besides that, around 61% of provinces still have adolescent birth rates above the national average. This research uses clustering techniques to group provinces based on reproductive health dimensions to provide insight for policymakers. The two clustering methods used are Agglomerative Nesting (AGNES) and K-Means. The analysis found that the K-Means method was more effective in producing three clusters: 15 provinces in the medium category, 10 provinces in the high category, and 9 provinces in the low category. It is hoped that the results of this research can help the government make appropriate policies regarding improvements in the reproductive health dimensions to achieve gender equality in Indonesia, especially in provinces with high categories.
Co-Authors Hastin, Nadya Noor Ilyas, Hilmi Malika Atim Raihannabil, Syfriza Davies Riani, May Alya Siregar, Tiara Khorijah Hamid