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All Journal Inferensi Limits: Journal of Mathematics and Its Applications
Muhammad Fikry Al Farizi
Universitas Airlangga
Computer Science & IT Decision Sciences, Operations Research & Management Engineering Mathematics Social Sciences

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Pengelompokan Daerah di Jawa Timur Berbasis Indikator Kesejahteraan Masyarakat dengan Pendekatan Analisis Cluster Hierarki dan Nonhierarki Muhammad Fikry Al Farizi; Faradilla Harianto; Maria Setya Dewanti; Cynthia Anggelyn Siburian; M. Fariz Fadillah Mardianto; Dita Amelia; Elly Ana
Inferensi Vol 6, No 2 (2023)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v6i2.15452

Abstract

Based on Central Statistics Agency (BPS) data in September 2021, East Java is a province with the largest number of poor people in Indonesia with a total of 26,503 million people. Poverty is one of the factors that affect people's welfare in East Java. Therefore, this research was conducted to classify regencies and cities in East Java based on indicators of community welfare through a hierarchical cluster analysis approach using the single linkage, complete linkage, average linkage, and ward methods, determine the optimum cluster for each method using Pseudo – F, then compare the four methods and determine the best method using the rated value, as well as identify the characteristics of each cluster group based on the best method. There are six variables that will be used in this study. All variable data is secondary data obtained from the official website of the Central Statistics Agency (BPS) of East Java Province. This study produced four clusters using the average linkage method as the best method. This research is expected to be useful as a consideration for evaluating the government and related agencies to overcome the main problems that still occur in each regency and city. Thus, the welfare of the people of East Java can be realized and the SDGs targets in Indonesia can be achieved.
Pemodelan Angka Harapan Hidup Negara G7 dengan Pendekatan Analisis Regresi Data Longitudinal Muhammad Fikry Al Farizi; Sugha Faiz Al Maula; Sofia Andika Nur Fajrina; Dzuria Hilma Qurotu Ain Hilma; Alda Fuadiyah Suryono; Nur Chamidah
Limits: Journal of Mathematics and Its Applications Vol. 22 No. 1 (2025): Limits: Journal of Mathematics and Its Applications Volume 22 Nomor 1 Edisi Ma
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/limits.v22i1.3368

Abstract

Life expectancy is the average number of years of life a newborn baby will live in a given year. In general, life expectancy is a tool to evaluate government performance in improving community welfare. The aim of this research is prediction using longitudinal data regression analysis methods, namely Generalized Least Square with a Restricted Maximum Likelihood approach using a uniform correlation structure, Autoregressive (AR) (1), and Gaussian with factors that influence life expectancy, namely Tax to GDP ratio, Gross Domestic Product per Capita (GDPPC) and Health Expenditure per Capita from 2000-2020 in G7 countries. Based on the analysis results, it was found that tax revenues had a negative effect of 0.155 but the effect was not significant, GDP had a positive effect of 0.715 but had a significant effect, while health expenditure had a negative effect of 0.49 on Life Expectancy. The research results found that conditions in the G7 that were not ideal caused negative effects on taxes and health spending that were not in accordance with theory. The suggestions that can be given include tax reform from the source and its implementation, such as cigarette tax and sugary drink tax. In addition, it also provides suggestions to include universal health for a healthier and more prosperous society. This research is also in accordance with the aim of Sustainable Development Goals (SDGs) number 3, namely "Ensuring healthy lives and improving the welfare of all populations of all ages" and can be used as a policy reference for Indonesia.
Co-Authors Alda Fuadiyah Suryono Ana, Elly Cynthia Anggelyn Siburian Dita Amelia Dzuria Hilma Qurotu Ain Hilma Faradilla Harianto M. Fariz Fadillah Mardianto Maria Setya Dewanti Nur Chamidah Sofia Andika Nur Fajrina Sugha Faiz Al Maula