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All Journal Jurnal Gaussian Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal BPPK : Badan Pendidikan dan Pelatihan Keuangan Sulolipu: Media Komunikasi Sivitas Akademika dan Masyarakat Parameter: Journal of Statistics
Gustriza Erda
Department Of Statistics Universitas Riau, Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Environmental Science Mathematics Public Health Other

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Journal : Parameter: Journal of Statistics

 1 
Classifiying The Factors Influencing The Human Development Index in Riau Province using Principal Component Analysis Gustriza Erda; Sartika Mega Aulia; Zulya Erda
Parameter: Journal of Statistics Vol. 2 No. 3 (2022)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2022.v2.i3.16203

Abstract

The Human Development Index is a critical indicator of economic growth. Several factors, including average length of schooling (X1), expected length of schooling (X2), life expectancy at birth (X3), number of health workers (X4), number of health facilities (X5), spending per capita (X6), open unemployment rate (X7), number of poor people (X8), percentage of households with proper drinking water sources (X9), and GRDP growth rate (X10), can influence the Human Development Index. The purpose of this research was to simplify the factors that influence the human development index in Riau Province in 2021. Data analysis used R-Studio software by applying descriptive statistical analysis, Principal Component analysis, and Biplot analysis. The analysis revealed that the ten variables that influence human development index in Riau in 2021 can be divided into three categories: community service quality, health facilities, access, and economic conditions. These three factors can describe up to 80% of the diversity of the data.
GROUPING OF POVERTY IN INDONESIA USING K-MEANS WITH SILHOUETTE COEFFICIENT Gustriza Erda; Chairani Gunawan; Zulya Erda
Parameter: Journal of Statistics Vol. 3 No. 1 (2023)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2023.v3.i1.16435

Abstract

Poverty is an enormous problem in numerous nations including Indonesia. Poverty can be measured using several indicators, including the unemployment rate, the percentage of poor people, expenditures per capita, and the poverty line. The purpose of this study is to categorize Indonesian provinces based on poverty indicators in 2021 using K-Means with the Silhouette Coefficient approach. Based on the silhouette coefficient approach, there are two clusters that are created. The first cluster is a high-poverty-rate regional group that includes the provinces of Aceh, Bengkulu, West Nusa Tenggara, East Nusa Tenggara, Central Sulawesi, Gorontalo, Maluku, West Papua, and Papua. On the other hand, the second cluster is an association of regions with a low poverty rate, and it includes 25 provinces. The greater number of provinces in the low poverty rate cluster implies that the poverty rate in Indonesia in 2021 is included in the low category
IMPLEMENTATION OF THE K-MEDOIDS METHOD IN CLUSTERING HUMAN DEVELOPMENT INDEXES IN INDONESIA Gustriza Erda; Radhiatul Khaira Usdika; Rizka Pitri; Zulya Erda
Parameter: Journal of Statistics Vol. 3 No. 2 (2023)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2023.v3.i2.16906

Abstract

The Human Development Index (HDI), which takes into account three fundamental aspects of human existence, a long and healthy life, knowledge, and a reasonable level of living, is one tool used to assess the effectiveness of human progress. Clustering provinces based on the human development index is important so that development disparities can be identified and help identify provinces with high, medium or low levels of development. The purpose of this study was to use the k-medoids approach to perform a cluster analysis of HDI in Indonesia based on life expectancy, average years of schooling, expected years of schooling, and expenditure per capita adjusted for 2022. The analysis indicate that two clusters were created: cluster 1 had a high human development index, while cluster 2 had a low human development index. More provinces belonged to cluster 1 than cluster 2 suggesting that human development index in Indonesia in 2022 was largely in the high category
Co-Authors Anne Mudya Yolanda Arisman Adnan Chairani Gunawan Erie Sadewo Goldameir, Noor Ell Radhiatul Khaira Usdika Rezzy Eko Caraka Riris Putri Kinanti Rizka Pitri Sartika Mega Aulia Simbolon, Veronika Amelia Tatik Widiharih Wawan Sugiyarto Yuciana Wilandari Zul Indra Zulya Erda Zulya Erda