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All Journal Enthusiastic : International Journal of Applied Statistics and Data Science
Dina Tri Utari
Universitas Islam Indonesia, Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics

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Risk Analysis on the Growth Rate of Covid-19 Cases in Indonesia Using Statistical Distribution Model Dina Tri Utari; Andrie Pasca Hendradewa
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 1 Issue 1, April 2021
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (244.284 KB) | DOI: 10.20885/enthusiastic.vol1.iss1.art3

Abstract

Coronavirus or Covid-19 outbreak has been declared as a pandemic and many countries were not ready to deal with such an eventuality. The highly rapid rate of transmission is one reason for the need to take mitigation measures, since healthcare system has limited capacity. Indonesia is one of the countries that has lost medical resources to the pandemic. In order to provide more comprehensive information about the characteristics of Covid-19 in Indonesia, risk analysis of the occurrence of new cases was needed. This study proposes a related overview about risk occurrence of new Covid-19 cases per daily basis by performing distribution fitting technique to form a statistical distribution model. Among the available alternative models, Geometric distribution is the most suitable to describe the growth of new cases in Indonesia. Received February 12, 2021Revised March 25, 2021Accepted April 15, 2021
Implementation K-Means Algorithm to Group Provinces By Factors Influenced Criminal Act in Indonesia in 2019 Zumrotul Wahidah; Dina Tri Utari
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 2 Issue 1, April 2022
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol2.iss1.art5

Abstract

A criminal act is an act that is prohibited by a criminal law accompanied by a sanction in the form of a particular crime for whoever violates the prohibition. Criminal action as a social phenomenon is more influenced by various aspects of life in society, including poverty and unemployment factors. Grouping the factors that influence a crime is necessary to find the most recent information that was not previously known. This research uses the K-Means method, a non-hierarchical cluster analysis that seeks to partition data with the same characteristics into one cluster. The results showed that 3 clusters formed, with cluster 1 covering 17 provinces are areas with the characteristics of the lowest percentage of poverty and the highest average unemployment, the cluster group 2 includes 12 provinces which are areas with the characteristics of the percentage of moderate poverty and the lowest average unemployment, the cluster group 3 includes five provinces which are areas with the characteristics of the highest percentage of poverty and moderate unemployment.
Implementation of Markov Chain in Detecting Opportunities for Natural Disasters in Klaten (Case Study: Number of Floods, Landslides, and Hurricanes 2019-2020) Afdelia Novianti; Dina Tri Utari
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 1 Issue 2, October 2021
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (441.484 KB) | DOI: 10.20885/enthusiastic.vol1.iss2.art2

Abstract

Java Island is one of the areas that is very fertile and densely populated, but on the other hand, Java Island is also one of the areas that is most frequently hit by natural disasters, one of which is Klaten Regency. Natural disaster itself is an event that threatens and disrupts human life caused by nature. Some of the natural disasters that often occur simultaneously in Klaten Regency are floods, landslides, and hurricanes. These three disasters usually occur during the rainy season. This of course makes the government need to take action by seeing the large chance of a disaster occurring in order to optimize disaster management. Then research will be carried out that aims to determine the chances of natural disasters occurring in the next few years. Forecasting will be carried out using the Markov chain method, with this method the probability value of the future period can be estimated using the current period probability value based on the characteristics of the past period. So that the value of the steady state chance of floods and landslides in period 36 (December 2023) and hurricanes in period 15 (March 2022) with the chances of a disaster are 34.21%, 15.38%, and 73.53%, respectively.Received August 31, 2021Revised October 27, 2021Accepted November 11, 2021
Co-Authors Afdelia Novianti Andrie Pasca Hendradewa Zumrotul Wahidah