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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 12 Documents
 1   2 
Search results for , issue "Vol 4 No 3 (2020)" : 12 Documents clear
ANALISIS SPASIAL KETERTINGGALAN DAERAH DI INDONESIA TAHUN 2018 MENGGUNAKAN GEOGRAPHICALLY WEIGHTED LOGISTIC REGRESSION Tata Pacu Maulidina; Siskarossa Ika Oktora
Indonesian Journal of Statistics and Applications Vol 4 No 3 (2020)
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.v4i3.690

Abstract

Development inequality in Indonesia has led the developed and underdeveloped regions. Regional backwardness caused by high inequality must be handled properly to prevent negative impacts on national stability. But in fact, the handling of underdeveloped regions is only effective in Western Indonesia, while in Eastern Indonesia tends to be not optimal. This study aims to explore regional backwardness in Indonesia and examines the factors that influence it. Based on data, underdeveloped regions tend to cluster in eastern Indonesia, and the independent variables have large variations between regions. This indicates dependence and spatial heterogeneity. Therefore, this study applies spatial analysis using the Geographically Weighted Logistic Regression (GWLR) method. GWLR shows better performance in modeling the regional backwardness in Indonesia compared to its global model (binary logistic regression). This study provides a local model for each district/city that can be used by local governments to implement more effective policies based on factors that do have significant effects on regional backwardness.
ANALISIS INFLASI MENGGUNAKAN DATA GOOGLE TRENDS DENGAN MODEL ARIMAX DI DKI JAKARTA Newton Newton; Anang Kurnia; I Made Sumertajaya
Indonesian Journal of Statistics and Applications Vol 4 No 3 (2020)
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.v4i3.694

Abstract

Inflation is an important economic indicator in showing the economic symptoms of a region's price level. DKI Jakarta is the capital of Indonesia chosen as the center of the economic barometer because it can provide the greatest contribution and influence on the Indonesian economy. The ARIMAX model was used for forecasting by adding independent variables in the Google trends data. Google trends data were explored based on seven expenditure groups published by IHK. The purpose of this study was to determine the effect of forecast Google trends using BPS inflation data in DKI Jakarta. The result of the exploration of Google Trends data was forecasted to get the best forecast model results. The result of data analysis indicates that the forecast results approached the original BPS data with the best forecast model is ARIMAX (2.0.3) all variables X. Google Trends data can be used as forecasting but cannot be used as a reference policy decision.

Page 2 of 2 | Total Record : 12

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