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All Journal Jurnal Gaussian Jurnal Statistika Universitas Muhammadiyah Semarang Program Kreativitas Mahasiswa - Penelitian JPM17: Jurnal Pengabdian Masyarakat MUST: Journal of Mathematics Education, Science and Technology Jurnal Penamas Adi Buana Variance : Journal of Statistics and Its Applications Inferensi Jurnal Visi Pengabdian Kepada Masyarakat Seminar Nasional Hasil Riset dan Pengabdian (SNHRP) JAPI: Jurnal Akses Pengabdian Indonesia VARIANSI: Journal of Statistics and Its Application on Teaching and Research Jurnal PADI (Pengabdian mAsyarakat Dosen Indonesia) SOSIO KONSEPSIA: JURNAL PENELITIAN DAN PENGEMBANGAN KESEJAHTERAAN SOSIAL MANGGALI RAGAM: Journal of Statistics and Its Application
Alfisyahrina Hapsery
Program Studi Statistika, Fakultas Sains Dan Teknologi, Universitas PGRI Adi Buana Surabaya
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Nursing Public Health Social Sciences Other

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Journal : Jurnal Gaussian

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PERBANDINGAN METODE OPTIMASI UNTUK PENGELOMPOKAN PROVINSI BERDASARKAN SEKTOR PERIKANAN DI INDONESIA (Studi Kasus Dinas Kelautan dan Perikanan Indonesia) Edy Sulistiyawan; Alfisyahrina Hapsery; Lucky Junita Ayu Arifahanum
Jurnal Gaussian Vol 10, No 1 (2021): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.v10i1.30936

Abstract

The fisheries sector has an important role in supporting the food security chain, where the world's protein needs can be met by fisheries resources, both from capture fisheries and aquaculture. There are several fisheries sectors including fishing companies, capture fisheries production, number of ships, types and size of cultivated land. Therefore a statistical analysis is needed to increase the potential of fisheries in Indonesia. Data on the fisheries sector used in this study from the Indonesian Central Statistics Agency in 2018, which included the 2016 fisheries sector with 34 observation units in Indonesia. By using cluster analysis K-Means aims to group provinces in Indonesia based on the fisheries sector so that several groups are formed which will show the characteristics of each group. There are three determinations of the optimum number of clusters, namely the Elbow method, Silhouette method, and GAP Statistics. The results showed that optimum clusters were formed in 2 clusters, with the best Elbow and Silhouette methods. Where the first cluster is a region that shows a low value of the fisheries sector consisting of 30 provinces this is due to inadequate infrastructure and use that is not optimal while cluster 2 regions that have great potential in the Indonesian fisheries sector in 2016 as many as 4 provinces namely West Java, Java Central, East Java, and South Sulawesi as dominating capture fisheries production and aquaculture. Keywords: Fisheries Sector, K-Means Cluster Analysis, Elbow Method, Silhoutte Method and GAP Statistics.
PERBANDINGAN SAR DAN SARQR PADA PEMODELAN INDEKS PEMBANGUNGAN MANUSIA DI JAWA TENGAH TAHUN 2022 Hapsery, Alfisyahrina; Hermanto, Elvira Mustikawati Putri; Aprilia, Yohanita Uniyantri
Jurnal Gaussian Vol 12, No 4 (2023): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.12.4.581-592

Abstract

The Human Development Index (HDI) is one of the indicators created to measure the success of human quality of life. Central Java is one of the provinces that has experienced a significant increase in HDI in recent years. However, the rankings of its regencies/cities have not shown significant changes. This study aims to model the HDI in Central Java based on the factors that influence it. The data used for modeling the HDI are secondary data obtained from the Central Statistics Agency (BPS) of Central Java, encompassing 35 regencies/cities in Central Java. The analysis in this study employs spatial analysis, specifically Spatial Autoregressive (SAR). Given the potential spatial effects at certain quantiles of the independent variables, the appropriate analysis is Spatial Autoregressive Quantile Regression (SARQR), which combines the SAR method with quantile regression. The best model from the study results is the SAR model, with factors influencing the HDI in Central Java including Population Percentage, Labor Force Participation Rate, Crime Rate, and Average Non-Food Expenditure. The cities of Semarang, Salatiga, and Surakarta have the highest HDI values at each quantile, ranging from the 0.10 quantile to the 0.90 quantile.
Co-Authors Abdullah Jabbar Daimuddin Achmad Chikham Nouriel Rosyadi Agustin, Risca Aida Meimela Al-Amin, Moch. Iqbal Nasurulloh Aliffia Rahma Anandyani Andriana Yoshinta, Andriana Aprilia, Yohanita Uniyantri Ardina Eka Nawang Sari Arief Ibrahim, Caraka Bunga , Natasha Caraka Arief Ibrahim Caraka Arief Ibrahim Choliq, Maulivia Idham DEA TRISHNANTI Dwi Cahya Julia Kartikasari Edy Sulistiyawan, Edy Ega Riski Suci Cahyani Ellya Susilowati Elvira Mustikawati Putri Hermanto Elvira Mustikawati Putri Hermanto Fajarulloh, Moh Subhan Faldianus Karno Faldianus Karno Fanny Ayu Octaviana, Fanny Ayu Fitriani, Fenny Gangga Anuraga Gili, Ireni Lusyanti Giyanti Linda Purnama, Giyanti Linda Hamidah, Wanda Nur Haryanto, Intan Amelia Heppy Reihana K. S Indrasetianingsih, Artanti Intan Amelia Haryanto Ireni Lusyanti G Izzadin Muhamad Nur Irfan Khusnul Khotimah Khusnul Khotimah Lubis, Reysha Rizki Amanda Lucky Junita Ayu Arifahanum Maria Hernita Elvine Pramesty Mochammad Iqbal Nasrulloh Al Amin Muhammad Alim Alhakam Muhammad Rafli Nofrian Risalah Novi Rahmawati Nuraini , Salsa Rifqah pramesti, wara Prizka Rismawati Arum Rabiatul Adawiyah Ratu Bunga Prawesti Arie Salim Risca Agustin Sadewa, Arief Saputri Dyah Pratiwi Syeni Agustin Ningtias Tutut Januar Pertiwi, Tutut Januar Ulul Azmi Wara Pramesti Yasmin Findi Ariska Yohanita Uniyatri Aprilia Yohanita Uniyatri Aprilia