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All Journal Zeta - Math Journal Mandalika Mathematics and Educations Journal Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi
Candra, Yossy
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Computer Science & IT Mathematics

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Pengelompokan Provinsi Berdasarkan Indikator Ekonomi, Pendidikan, Kesehatan, dan Kriminalitas di Indonesia Menggunakan Algoritma Centroid Linkage Candra, Yossy; Goejantoro, Rito; Dani, Andrea Tri Rian
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi EULER: Volume 12 Issue 1 June 2024
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v12i1.24887

Abstract

With its rich cultural diversity and abundant natural resource potential, Indonesia still faces various social science problems. Economic inequality, low quality of education, limited access to health, and high crime rates are social problems that hit various provinces in Indonesia. This research was conducted to group provinces in Indonesia based on social indicators, which include economy, education, health, and crime. This research uses cluster analysis with the Centroid Linkage algorithm to group provinces in Indonesia. The Centroid Linkage algorithm was chosen because of its advantages in producing optimal grouping. Test cluster validity using the Silhouette Coefficient (SC). The case studies used are variables that are thought to be related to economic, health, education, and crime problems in 34 provinces in Indonesia in 2021. Based on the analysis, the grouping results using the Centroid Linkage algorithm show that the optimal number of clusters is 2, with an SC value of 0.538. Cluster 1 consists of 33 provinces, and Cluster 2 consists of only one province, DKI Jakarta.
A District/City Profiling Based on Poverty Indicators in East Nusa Tenggara Using the Centroid Linkage Algorithm Dani, Andrea Tri Rian; Candra, Yossy; Putra, Fachrian Bimantoro; Fauziyah, Meirinda
Zeta - Math Journal Vol 10 No 2 (2025): November
Publisher : Universitas Islam Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31102/zeta.2025.10.2.81-91

Abstract

Poverty is a complex multidimensional phenomenon that significantly impacts human life. Poverty has always been a problem that the government has discussed regionally, centrally, and internationally. The issue of poverty is interesting to approach and analyze using a statistical approach, namely cluster analysis. Cluster analysis is used to group objects based on their level of similarity. In this research, the algorithm used is the Centroid Linkage Algorithm. The Centroid Linkage algorithm was chosen based on its advantages in the grouping process. Distance similarity measurement uses Squared Euclidean. The data used are district/city poverty indicators in East Nusa Tenggara Province. The analysis results show that two optimal clusters were obtained with their distinguishing characteristics. Hopefully, the results of this analysis can be used as a reference in formulating policies for alleviating poverty.
Transformasi Data Menjadi Kebijakan: Studi Clustering Hierarki pada Layanan Keagamaan Kementerian Agama Candra, Yossy; Andrea Tri Rian Dani
Mandalika Mathematics and Educations Journal Vol 7 No 4 (2025): Desember
Publisher : FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jm.v7i4.10261

Abstract

Indonesia adalah negara dengan keberagaman agama, budaya, dan kondisi geografis yang sangat kaya. Untuk memastikan kebijakan layanan keagamaan yang merata dan adil, penelitian ini menganalisis keberagaman karakteristik daerah. Tujuannya adalah untuk mengklasifikasikan provinsi-provinsi di Indonesia berdasarkan data layanan keagamaan. Metode yang digunakan adalah hierarchical clustering dengan lima algoritma dan tiga ukuran jarak. Kombinasi average linkage dan jarak chebyshev menghasilkan koefisien korelasi cophenetic tertinggi (0,969), menjadikannya algoritma paling optimal. Uji silhouette coefficient menunjukkan dua klaster sebagai jumlah optimal, dengan nilai silhouette coefficient sebesar 0,736, dan uji ANOVA memvalidasi bahwa perbedaan antar klaster signifikan. Klaster pertama terdiri dari Provinsi Aceh, Jawa Timur, Jawa Barat, dan Jawa Tengah, yang memiliki rata-rata setiap variabel lebih tinggi. Klaster kedua mencakup seluruh provinsi lainnya, termasuk DKI Jakarta, yang menunjukkan bahwa masih ada peluang untuk peningkatan kualitas layanan keagamaan. Temuan ini memberikan gambaran penting bagi Kementerian Agama untuk terus berupaya meningkatkan kualitas layanan keagamaan di seluruh wilayah Indonesia, dengan fokus pada perbaikan aspek layanan yang lebih luas.
Pemodelan Indeks Kerukunan Umat Beragama di Indonesia Menggunakan Regresi Nonparametrik Deret Fourier Berdasarkan Fungsi Basis Sinus dan Basis Cosinus Candra, Yossy; Dani, Andrea Tri; Wagimin, Wagimin
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 14 Issue 1 April 2026
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v14i1.37721

Abstract

This study aims to analyze the factors suspected of influencing the Interfaith Harmony Index (IKUB) across all provinces in Indonesia and determine the best prediction model. The predictor variables suspected of influencing are the number of religious organizations, religious instructors, educational institutions, and houses of worship. The analysis was conducted using nonparametric Fourier series regression with a comparison of cosine and sine basis functions, and evaluation through MSE, RMSE, MAPE, GCV, UBR, and . The results show that the 4-oscillating cosine basis function model is the most accurate, with MSE (2.27), RMSE (1.51), MAPE (1.47), GCV (6.56), UBR (1.29×10-10)and  (86.28%), compared to the sine basic function model. This model is able to flexibly represent complex nonlinear relationship patterns and variations in IKUB between provinces. These findings demonstrate a relationship between the research variables and variations in IKUB values, thus providing a basis for understanding harmony patterns and supporting data analysis for policy considerations. While the research findings are predictive, they place greater emphasis on uncovering the relationships between variables that influence interfaith harmony.
Co-Authors Andrea Tri Rian Dani Dani, Andrea Tri Dani, Andrea Tri Rian Fauziyah, Meirinda Putra, Fachrian Bimantoro Rito Goejantoro, Rito Wagimin Wagimin, Wagimin