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Eksponensial
Published by Universitas Mulawarman
ISSN : 20857829     EISSN : 27983455     DOI : https://doi.org/10.30872/
Core Subject : Economy, Science, Education,
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Other
Jurnal Eksponensial is a scientific journal that publishes articles of statistics and its application. This journal This journal is intended for researchers and readers who are interested of statistics and its applications.
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 12 Documents
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Search results for , issue "Vol. 13 No. 2 (2022)" : 12 Documents clear
Pengelompokan Kabupaten/Kota Di Pulau Kalimantan Berdasarkan Indikator Indeks Pembangunan Manusia Tahun 2020 Menggunakan Optimasi K-Means Cluster Dengan Principle Component Analysis (PCA) Anwar, Khoiril; Goejantoro, Rito; Prangga, Surya
EKSPONENSIAL Vol. 13 No. 2 (2022)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (964.676 KB) | DOI: 10.30872/eksponensial.v13i2.1053

Abstract

Data mining is a technique or process to obtain useful information from a large database. Based on its functionality, one of the tasks of data mining is to group data. Cluster analysis is an analysis that aims to group objects based on the information found in the data. One of the cluster analysis methods is the K-Means cluster method, which is a non-hierarchical grouping method by dividing the data set into a number of groups that do not overlap between one group and another. This study aims to classify districts/cities on the island of Kalimantan based on indicators of the human development index and obtain the sillhoutte coefficient value from the optimal cluster analysis using the K-Means algorithm on principle component analysis. The data used is the 2020 human development index data in districts / cities on the island of Kalimantan and used 8 variables from the human development index indicator. The results of the optimal cluster formed in the grouping of regencies/cities on the island of Kalimantan using the K-Means cluster method on the principle component analysis are 4 clusters. Cluster 1 has 20 regencies/cities, cluster 2 has 3 regencies/cities, cluster 3 has 26 regencies/cities and cluster 4 has 7 regencies/cities. The sillhoutte coefficient value for data validation from district/city clustering on the island of Kalimantan using the K-Means cluster method on principle component analysis produces 4 clusters of 0.540 which states that the cluster structure formed in this grouping is a medium structure.
Pemodelan Regresi Spasial Data Panel: Studi Kasus : Indeks Pembangunan Manusia di Provinsi Kalimantan Timur Menurut Kabupaten/Kota Tahun 2017-2020 Murdani, Endah Mulia; Fathurahman, M; Goejantoro, Rito
EKSPONENSIAL Vol. 13 No. 2 (2022)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1125.51 KB) | DOI: 10.30872/eksponensial.v13i2.956

Abstract

Panel data is a combination of cross-section data and time-series data. The panel data regression can model the panel data. In its development, panel data regression has been developed to model spatial data, called panel data spatial regression. Spatial data is data that considers the empirical observations and considers the location factor of these observations. This study examines the spatial regression modeling of panel data and applies it to model the factors that influence the Human Development Index (HDI) of districts/cities in East Kalimantan Province from 2017 to 2020. HDI is a composite index that measures the average achievement in the three basic dimensions of human development that are considered very basic, namely life expectancy, knowledge, and a decent standard of living. HDI is one of the measuring tools considered to reflect the status of human development in a region and plays an essential role in improving the quality of human resources. The results show that the panel data spatial regression model suitable for modeling the HDI of districts/cities in East Kalimantan Province from 2017 to 2020 is the Spatial Autoregressive Fixed Effect (SAR-FE) model. The rate of economic growth and the district/city minimum wage factors that significantly influence the HDI of districts/cities in East Kalimantan Province from 2017 to 2020 based on the SAR-FE model is the rate of economic growth and the district/city minimum wage. Keywords : Panel Data, Spatial Data, Panel Data Spatial Regression, SAR-FE, HDI

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