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All Journal Indonesian Journal of Statistics and Its Applications ComTech: Computer, Mathematics and Engineering Applications
Zerlita Fahdha Pusdiktasari
University of Brawijaya
Computer Science & IT Engineering Mathematics Other

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The Clustering of Provinces in Indonesia by The Economic Impact of Covid-19 using Cluster Analysis: Pengelompokkan Provinsi di Indonesia dengan Ekonomi Terdampak Covid-19 Menggunakan Analisis Cluster Zerlita Fahdha Pusdiktasari; Widiarni Ginta Sasmita; Wulaida Rizky Fitrilia; Rahma Fitriani; Suci Astutik
Indonesian Journal of Statistics and Applications Vol 5 No 1 (2021)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v5i1p117-129

Abstract

The Covid-19 pandemic has hit Indonesia since March 2020. Several policies have been issued by the Indonesian government to reduce the level of the spread of Covid-19. This policy has an impact on various fields of life, especially the economic sector in various sectors. This study was conducted to analyze the grouping of provinces whose economies are at risk of being affected by Covid-19 based on various economic sectors, namely the unemployment rate, the percentage of poor people, the provincial minimum wage, and the occupancy rate of hotels using cluster analysis. Cluster analysis was performed using several hierarchical methods, namely Simple, Complete, Average, and Centroid Linkage and Ward. The Cophenetic correlation coefficient (rCoph) was used to determine the best method, while the number of clusters was determined based on the Dunn, Connectivity, and Silhoutte indexes. The analysis result shows that Average Linkage is the best method with two clusters. The first cluster consists of all provinces in Indonesia except Papua, whose economy is highly at risk of being affected by Covid-19, characterized by a low percentage of the poor and a low provincial minimum wage, as well as high levels of open unemployment and hotel occupancy rates. Meanwhile, the second cluster consists of the Province of Papua, which is an economic group with a low risk of being affected by Covid-19. By looking at the impact of the Covid-19 disaster, the government can make recovery efforts and generalize economic recovery policies due to Covid-19 which have an impact on the economy of almost all provinces in Indonesia.
An Improved Weighted Median Algorithm for Spatial Outliers Detection Zerlita Fahdha Pusdiktasari; Rahma Fitriani; Eni Sumarminingsih
ComTech: Computer, Mathematics and Engineering Applications Vol. 13 No. 2 (2022): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v13i2.7821

Abstract

A spatial outlier is an object that significantly deviates from its surrounding neighbors. The median algorithm is one of the spatial outlier methods, which is robust. However, it assumes that all spatial objects have the same characteristics. Meanwhile, the Average Difference Algorithm (AvgDiff) has accommodated the differences in spatial characteristics, but it does not use statistical tests to determine the status of an object, whether it is an outlier or not. The research developed an improved version of the median algorithm and AvgDiff, called the Weighted Median Algorithm (WMA) which combined the advantages of the two methods. From the median algorithm, WMA adopted median and statistical test concepts. Meanwhile, from AvgDiff, WMA adopted the concept of using differences in objects’ spatial characteristics as weights. A combination of the two advantages was innovated by calculating WMA’s neighborhood score using a weighted median. Then, a simulation was conducted to analyze the accuracy of the method. The result confirms that when objects have heterogeneous spatial characteristics, WMA performs better than the median algorithm. The accuracy of WMA is not much higher than AvgDiff, but the use of WMA can prevent a serious false detection problem. The methods can be applied to an incidence rate of Covid-19 data in East Java.
Co-Authors Eni Sumarminingsih Rahma Fitriani Suci Astutik Widiarni Ginta Sasmita Wulaida Rizky Fitrilia