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INDONESIA
Indonesian Journal of Statistics and Its Applications
Published by Institut Pertanian Bogor
ISSN : 25990802     EISSN : 25990802     DOI : -
Core Subject : Science, Education,
Computer Science & IT Mathematics Other
Indonesian Journal of Statistics and Its Applications (eISSN:2599-0802) (formerly named Forum Statistika dan Komputasi), established since 2017, publishes scientific papers in the area of statistical science and the applications. The published papers should be research papers with, but not limited to, the following topics: experimental design and analysis, survey methods and analysis, operation research, data mining, statistical modeling, computational statistics, time series and econometrics, and statistics education. All papers were reviewed by peer reviewers consisting of experts and academicians across universities and agencies
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 5 Documents
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Search results for , issue "Vol 7 No 1 (2023)" : 5 Documents clear
Nested Linear Mixed Models with Repeated Measurement for Analyzing Telecommunication Products: Model Linier Campuran Tersarang dengan Pengukuran Berulang untuk Menganalisis Produk Telekomunikasi Rahmawati, Fardilla; Notodiputro, Khairil Anwar; Rahman, La Ode Abdul
Indonesian Journal of Statistics and Applications Vol 7 No 1 (2023)
Publisher : Statistics and Data Science Program Study, IPB University, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v7i1p1-14

Abstract

Nested linear mixed model is a model that combines fixed factors and random factors. Observations made over time with the same object being observed are called repeated measurements. This research was conducted to determine the determinant factors of internet data quota sales which are influenced by SA (Sales Area), MC (Mutual Check), PC (Product Category), and time factors using a nested linear mixed model with repeated measurement. SA, PC, and time factors as fixed factors while the MC factor nested in SA as a random factor. The results showed that the interaction effect between three fixed factors, namely between SA, PC, and time have a significant effect on the sales volume of internet data quota. Moreover, variation in the sales volume between MC factors was significant. The interaction between MC and PC, and the interaction between MC and time were significant on the sales volume of internet data quota.
Sentiment Analysis of Twitter Users’ Opinion Towards Face-to-Face Learning: Analisis Sentimen Tanggapan Masyarakat Pengguna Twitter terhadap Pembelajaran Tatap Muka Manaf, Silmi Annisa Rizki; Alamudi, Aam; Fitrianto, Anwar
Indonesian Journal of Statistics and Applications Vol 7 No 1 (2023)
Publisher : Statistics and Data Science Program Study, IPB University, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v7i1p15-31

Abstract

In early 2022, the government allowed face-to-face learning again after approximately one year of online learning. When face-to-face learning will be held again in several areas, the number of Covid-19 has increased and the government has imposed the enforcement of restrictions on community activities. The pros and cons of face-to-face learning also occur on social media, one of them is on Twitter. This study used twitter data for January 30th – February 7th 2022. Opinions on twitter regarding face-to-face learning were studied by sentiment analysis using the binary logistic regression method with sentiment classes being positive and negative. Labeling uses based on the final score of the difference between the number of positive and negative words. The purpose of this study is to determine the public’s perception of the policy of implementing face-to-face learning in the era of the Covid-19 on social media especially Twitter. From this study, public’s perception tends to be in a negative direction which indicates that they have not agreed enough with the existence of face-to-face learning in the period of February 2022 with the accuracy was 85%, sensitivity was 77%, specificity was 88%, and AUC was 91%.
Grouping Provinces in Indonesia Based on the Causes of Stunting Variables using Hierarchical Clustering Analysis: Pengelompokan Provinsi di Indonesia Berdasarkan Peubah Penyebab Stunting Menggunakan Analisis Cluster Hierarki Meilani, Detia; Masjkur, Mohammad; Afendi, Farit M
Indonesian Journal of Statistics and Applications Vol 7 No 1 (2023)
Publisher : Statistics and Data Science Program Study, IPB University, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v7i1p32-43

Abstract

Stunting is a condition due to chronic malnutrition that causes children to be shorter in height compared to their age. The prevalence of stunting in Indonesia still exceeds the standards set by WHO. This study aims to classify provinces in Indonesia based on the characteristics of the causes of stunting. Cluster analysis is a statistical method used to group objects with similar characteristics. Province grouping is done using hierarchical cluster analysis consisting of Single Linkage, Complete Linkage, Average Linkage, Ward's method, and Centroid method. The Cophenetic correlation coefficient was used to determine the best cluster method and the optimal number of clusters using the Silhouette coefficient. The results show that the centroid method has the highest Cophenetic correlation coefficient with four clusters. The first cluster consists of 1 province with low stunting characteristics, the second cluster consists of 3 provinces with high stunting characteristics, the third cluster consists of 22 provinces with very high stunting characteristics, and the fourth cluster consists of 8 provinces with moderate stunting characteristics.
Analysis Of Stock Market, Mining Commodity, Exchange Rate, And Energy Sector Stock Index Using Vector Error Correction Model: Analisis Bursa Saham, Komoditas Pertambangan, Kurs, Dan Indeks Saham Sektor Energi Menggunakan Vector Error Correction Model Melati; Silvianti, Pika; Afendi, Farit Mochamad
Indonesian Journal of Statistics and Applications Vol 7 No 1 (2023)
Publisher : Statistics and Data Science Program Study, IPB University, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v7i1p44-55

Abstract

Energy Sector is one of the sectors that has a significant impact on the overall economic growth of a country. Economic growth is always linked to energy consumption, as increasing economic development leads to higher energy demand. Therefore, this study aims to analyze the factors influencing the energy sector stock index in Indonesia using Vector Error Correction Model (VECM). The data used include the energy sector stock index, crude oil prices, coal prices, gas prices, Nikkei Index, Shanghai Index, Dow Jones Index, and exchange rates from January 2021 to March 2023. VECM analysis results indicate that in the short term, crude oil prices and coal prices have a significant impact on the energy sector stock index. In the long term, significant factors are coal prices, gas prices, Nikkei Index, and exchange rates. The Impulse Response Function (IRF) analysis reveals that shocks to the energy sector stock index, crude oil prices, and coal prices can increase the energy sector stock index. Conversely, shocks to the Nikkei Index can decrease the energy sector stock index. The Forecast Error Variance Decomposition (FEVD) results demonstrate that the contributions of the energy sector stock index, crude oil prices, coal prices, and gas prices are significant in explaining the behavior of changes in the energy sector stock index.
Spatio-temporal Clustering Analysis of Dengue Hemorrhagic Fever Cases in West Java 2016 – 2021: Analisis Penggerombolan Spasio-temporal Kasus DBD di Jawa Barat Tahun 2016 – 2021 Yanti, Yusma; Rahardiantoro, Septian; Dito, Gerry Alfa
Indonesian Journal of Statistics and Applications Vol 7 No 1 (2023)
Publisher : Statistics and Data Science Program Study, IPB University, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v7i1p56-63

Abstract

In 2020, WHO included dengue as a global health threat among 10 other diseases. This is also a problem in Indonesia, especially the province of West Java. Based on data from the Ministry of Health for 2022, West Java is the largest contributor to cases of Dengue Hemorrhagic Fever (DHF) in Indonesia. The spread of dengue fever is through mosquitoes, but climate also greatly influences the spread of this disease. The spread of West Java is quite wide, consisting of 27 city districts and a relatively high population density. This greatly influences the increase in the number of dengue fever cases. In this research, we will group years with the same dengue fever cases and identify groups of districts/cities in West Java with the same pattern of dengue fever cases for 2016 to 2021. The results obtained are that 2016 is the group with the highest number of cases. Meanwhile, from 27 city districts in West Java, three groups were obtained. Group 1 is the group with the highest number of cases consisting of Sukabumi City, Bandung City, Cimahi City, Depok City, Tasikmalaya City.

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