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All Journal Jurnal Pendidikan Ekonomi (JUPE) Interest : Jurnal Ilmu Kesehatan Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) JOIN (Jurnal Online Informatika) Sistemasi: Jurnal Sistem Informasi Jurnal Pendidikan Nonformal BAREKENG: Jurnal Ilmu Matematika dan Terapan Jiko (Jurnal Informatika dan komputer) International Journal of Remote Sensing and Earth Sciences (IJReSES) Jurnal Aplikasi Statistika & Komputasi Statistik Jurnal Kajian Pariwisata PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS Indonesian Journal of Statistics and Its Applications Jurnal Ekonomi Kependudukan dan Keluarga
Nooraeni, Rani
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

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KAJIAN EFEK SPASIAL KASUS DIFTERI DENGAN GEOGRAPHICALLY WEIGHTED NEGATIVE BINOMIAL REGRESSION (GWNBR) Mustika, Diva Arum; Nooraeni, Rani; IJSA, Indonesian Journal of Statistics and Its Applications
Indonesian Journal of Statistics and Applications Vol 3 No 1 (2019)
Publisher : Statistics and Data Science Program Study, SSMI, 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.v3i1.185

Abstract

Diphtheria is an infectious disease caused by the Corynebacterium diphtheriae bacteria. Indonesia is the country with the most cases of diphtheria in Southeast Asia and ranks third in the world. In 2016, cases of diphtheria increased by 65 percent and became Extraordinary Events (KLB) in Indonesia, even though during 2013 to 2015 the number of cases of diphtheria has decreased. The province that has the highest number of diphtheria cases in Indonesia in 2016 is East Java. Diphtheria is centered and spread in certain districts / cities in East Java Province so that there are indications of spatial effects in the spread of diphtheria. Because data on the number of diphtheria cases overdispersed and indicated spatial effects in its spread, the main method used in this study was Geographically Weighted Negative Binomial Regression (GWNBR). This method will be compared with other alternative methods namely Poisson regression method and Negative Binomial Regression to get the best modeling. Based on the AIC value of each model it can be concluded that the best method for modeling the number of diphtheria cases is GWNBR. The modeling results with GWNBR show that there is indeed a spatial influence on the number of diphtheria cases and risk factors in East Java Province in 2016. The percentage of DPT-HB3 / DPT-HB-Hib3 immunization coverage is not significant in all observation areas, while the percentage of drug and vaccine availability is significant at entire observation area.
DAMPAK REDENOMINASI TERHADAP INFLASI INDONESIA: PENANGANAN MISSING MENGGUNAKAN METODE CASE DELETION, PMM, RF DAN BAYESIAN Bemi, Windri Wucika; Nooraeni, Rani
Indonesian Journal of Statistics and Applications Vol 3 No 3 (2019)
Publisher : Statistics and Data Science Program Study, SSMI, 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.v3i3.360

Abstract

Indonesia is the country with the third largest currency digit after Vietnam and Zimbabwe. In 2010, Indonesia conveyed a discourse on the application of rupiah redenomination, but in its implementation it was necessary to estimate the economic factors that would be affected, especially inflation, where inflation was one of the decisive indicators of the success of the redenomination policy of the currency. To estimate the impact of redenomination on inflation, Indonesia can reflect on the historical data of countries that have implemented the policy. Based on historical data, a model can be applied to Indonesia. Historical data includes macroeconomic variables and forms of government. To get a model with better precision, complete data needs to be considered. The historical missing will make the inferencing obtained invalid and important information that can be used for analysis also diminishes. The case deletion method, mean matching predictive, random forest, and bayesian linear regression can be used to handle it. The results showed that there were 38.18% missing data from total observations and the case deletion method as the best method. Then the condition of hyperinflation, economic growth, and the index of government forms significantly impacted inflation after the implementation of redenomination. So, if Indonesia applies redenomination between the period 2010-2017, with the classification accuracy of 64.71%, it is estimated that it will have a negative impact because the inflation will increase after redenomination is implemented.
PENGARUH TINDAK KORUPSI TERHADAP KEMISKINAN DI NEGARA-NEGARA ASIA TENGGARA DENGAN MODEL PANEL DATA Baktiar, Aditya Firman; Fadhilah, Herpanindra; Simatupang, Margareth Dwiyanti; Warman, Mula; Vira, Salsa; Nooraeni, Rani
Indonesian Journal of Statistics and Applications Vol 4 No 2 (2020)
Publisher : Statistics and Data Science Program Study, SSMI, 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.v4i2.634

Abstract

Poverty is still being an issue all over the world. It also happens in Southeast Asia that mostly consists of developing countries that identic with high poverty rates. Countries in the world have tried to eradicate the problem of poverty, it's just that it can be hampered due to the high level of corruption. This study aims to look at suitable models and the relationship between corruption and poverty. The data source in this study is secondary data from ten countries in Southeast Asia from 2015 to 2018. Analysis of the data used in this study is panel data. The result obtained is a panel data regression model that is more suitable for modeling the effect of corruption on poverty in Southeast Asian countries is a fixed effect model. Based on the model, the corruption represented by Corruption Perception Index (CPI) and the poverty represented by Human Development Index (HDI) is directly proportional which means every increase in one unit of CPI will also increase the HDI score by 0.001443 unit.
Co-Authors A, Yolanda Rizkie Adi Lumaksono Agung Budi Santoso Al Baihaqi, Rakai Astriani, Vina Baktiar, Aditya Firman Bemi, Windri Wucika Briliyanto, Muhamad Bagus Adji Candra, Arya Candra Dewi, Aprilia Lutviana Fadhilah, Herpanindra Firmansyah, Adrian Fitri, Muti Nurjannah Fitri, Nurhidayatul Hakim, Syifa Rahmawati Hamdani, Febri Helmiah, Najia Hirma, Emalia Septiani IJSA, Indonesian Journal of Statistics and Its Applications Khoirun Nisa', Intan Maulida Lestariningsih, Eni Mahendra, Fiqih Tri MS, Muhammad Muawwad Mumtaz Siregar, Amir Munia, Nufaisa Muqiit WS, Andriansyah Mustika, Diva Arum Nulkarim, Aldi Rochman Prasetya, Ananda Galuh Intan Pratama, Firza Refo Adi Pulungan, Ridson Alfarizal Putra, Amran Pratama Rifa Geandra, Alfitra Rizki, M. Alfa Salsabila, Atikah Saputri, Aprillia Anis Saragih, Meilani Thereza Br. Sari, Esa Anindika Satria, Manca Shariati, Ilhamsyah Ali Simatupang, Margareth Dwiyanti Siregar, Aisyah Anjani Putri Sofyan, Sabiq Sudianto, Fauzan Bayu Hera Susanti, Amalia Taufiqurrahman, Febi Vira, Salsa Warman, Mula Yusnissa, Hertina Yustiani, Dwi Zekha F, Noval Irgi