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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 192 Documents
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ESTIMASI KEBUTUHAN IMPOR DAGING SAPI UNTUK KONSUMSI RUMAH TANGGA DI INDONESIA MENGGUNAKAN REGRESI ROBUST Ratnasari Ratnasari; Ray Sastri
Indonesian Journal of Statistics and Applications Vol 2 No 2 (2018)
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.v2i2.186

Abstract

Beef import to Indonesia always gets pros and cons. The government argue that we need it to reduce the high price of beef due to the scarcity. On the other hand, Indonesia is an agrarian country with a lot of cattle farms. We should be able to meet the needs of beef from domestic production without import. The aim of this study is to get the best model for household consumption of beef at the district level, and use the model to estimate the import needs. This study uses data from Statistics Indonesia, both the raw data of National Sosio-economic Survey (SUSENAS) and beef production in district level. The methods of analysis is a robust regression model. The results is robust regression fit the data well. For households need, estimation of household consumption of beef is lower than domestic production. So that, Indonesia does not need to import beef for household need.
GEOGRAPHICALLY WEIGHTED LOGISTIC REGRESSION DENGAN FUNGSI KERNEL FIXED GAUSSIAN PADA KEMISKINAN JAWA TENGAH Wulandari Wulandari
Indonesian Journal of Statistics and Applications Vol 2 No 2 (2018)
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.v2i2.189

Abstract

Poverty alleviation is a problem faced by many countries in the world, included Indonesia. Poverty in Indonesia still relatively high. Poverty is one indicator of welfare. In general, the decline in poverty means that people's welfare increasing. Poverty is a multi-dimensional problem, which involves various microeconomic and macroeconomic factors, including the influence of the surrounding region. Modeling with geographically weighted regression (GWR) accommodates heterogeneous effects of independent variables on the dependent variable and produces a local parameter estimates. Central Java has the second highest poverty rate among provinces in Java. This study will model poverty in Central Java with a model that accommodates the influence of the surrounding region, named Geographically Weighted Logistic Regression (GWLR). Poverty modeling in Central Java with GWLR, in general, literacy rates (AMH), per capita GRDP, and Labor Force Participation Rate (TPAK) significantly affected poverty in Central Java with values that varied between districts / cities.
DETERMINAN TRANSAKSI NONTUNAI DI INDONESIA DENGAN PENDEKATAN ERROR CORRECTION MECHANISM (ECM) MODEL Zulfa Nur Fajri Ramadhani; Siskarossa Ika Oktora; Indonesian Journal of Statistics and Its Applications IJSA
Indonesian Journal of Statistics and Applications Vol 3 No 1 (2019)
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.v3i1.190

Abstract

Consumption is an activity that must be done by everyone. In order to consume something, a transaction is needed to get the goods or services desired. One kind of transaction that is used by many people nowadays is non-cash transaction. Since Bank Indonesia established Gerakan Nasional Non Tunai (GNNT) in August 2014, the value of non-cash transactions exceeds the value of cash transactions. It happenned because people prefer non-cash to cash transaction which is easier, safer, more practical, and more economical. Besides, an increase in non-cash transactions can also be influenced by other factors. Therefore, a study is conducted to analyze the determinants of non-cash transactions from the macro side by using Error Correction Mechanism (ECM). The data used in this study are secondary data from Bank Indonesia and Badan Pusat Statistik with monthly period from January 2010 until December 2017. The results showed that in the long run, private savings and BI rate have positive effect on non-cash transactions. In the short run, private savings and money supply have positive effect on non-cash transactions. While inflation does not affect non-cash transactions, both in the short and long run.
ANALISIS VARIABEL-VARIABEL YANG MEMPENGARUHI PERTUMBUHAN EKONOMI DI PROVINSI KEPULAUAN BANGKA BELITUNG TAHUN 2008-2015 Syamsu Pratama
Indonesian Journal of Statistics and Applications Vol 3 No 2 (2019)
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.v3i2.194

Abstract

Economic growth of a region can assess from various aggregate sizes, one of them is GDRP (Gross Regional Domestic Product). Based on theory, GDRP can influenced by several variables, including world commodity prices which have the largest share of GDP, labor force participation rate (LFPR), Human Development Index (HDI), income inequality, open unemployment rate and percentage of the poor. In 2015 Bangka Belitung Islands Province GRDP had a share of around 0.5 percent of Indonesia's GDP. The largest share is West Bangka Regency with 11.46 trillion rupiahs, while the smallest one is East Belitung with 6.112 trillion rupiahs.To find out picture of economic growth and the influence of variable prices of palm oil commodities, LFPR, HDI income inequality, open unemployment and the percentage of the poor on economic growth in the Bangka Belitung Islands Province 2008-2015, the method used is descriptive analysis and panel data regression.The best model for estimating GDRP growth in Bangka Belitung Islands Province in 2008-2015 is the fix effect model with Seemingly Uncorrelated Regression Method. With alpha 5 percent, the variables that significantly influence economic growth are HDI, the percentage of the poor, labor force participation rate (LFPR), income inequality, open unemployment rate and world commodity prices.economic growth
CONSTRUCTING EARTHQUAKE DISASTER-EXPOSURE LIKELIHOOD INDEX USING SHAPLEY-VALUE REGRESSION APPROACH Rahma Anisa; Bagus Sartono; Pika Silvianti; Aam Alamudi; Indonesian Journal of Statistics and Its Applications IJSA
Indonesian Journal of Statistics and Applications Vol 3 No 1 (2019)
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.v3i1.198

Abstract

Indonesia is very prone to earthquake disaster because it is located in the Pacific ring of fire. Therefore, a reference level of earthquake disaster exposure likelihood events in Indonesia is needed in order to increase people's awareness about the risks. This study aims to determine the index that describes the risk of possible future earthquake disaster. As initial research, this study is focus on earthquake disasters in Java region, as it has the largest population in Indonesia. Several indicators that are related to the severity of earthquake disaster impact, were used in this study. The weights of each indicators were determined by considering its shapley-value, thus all indicators gave equal contribution to the proposed index. The results showed that shapley-value approach can be utilized to construct index with equal contribution of each indicators. In general, the resulted index had similar pattern with the number of damaged houses in each districts.
THE BETA TRANSMUTED POWER DISTRIBUTION: PROPERTIES AND APPLICATION Abdelhakim Alabid; Ahmed Ali Hurairah; Indonesian Journal of Statistics and Its Applications IJSA
Indonesian Journal of Statistics and Applications Vol 3 No 1 (2019)
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.v3i1.204

Abstract

In this this paper, we define and study a new generalization of the Power distribution and the quadratic rank transmutation map (QRTM) in order to generate a flexible family of probability distribution taking Power distribution as the base distribution. The new distribution is called the beta transmuted Power (BTP) distribution. Some properties of the distribution such as moments, quantiles, mean deviation and order statistics are derived. The method of maximum likelihood is proposed to estimate the model parameters. The asymptotic confidence intervals for the parameters are also obtained based on asymptotic variance-covariance matrix. A simulation study is conducted to study the performance of the estimators. The importance and flexibility of the new model is proved empirically using a real data set.
MODELING OF THE PERCENTAGE OF AIDS SUFFERERS IN EAST JAVA PROVINCE WITH NONPARAMETRIC REGRESSION APPROACH BASED ON SPLINE TRUNCATED ESTIMATOR Nadia Murbarani; Yolanda Swastika; Ananda Dwi; Baktiar Aris; Nur Chamidah
Indonesian Journal of Statistics and Applications Vol 3 No 2 (2019)
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.v3i2.209

Abstract

Acquired Immune Deficiency Syndrome (AIDS) is a set of symptoms and infection or a syndrome that arise due to damage to the human immune system. AIDS is a health problem that often occurs in developing countries, including in Indonesia. East Java Province was ranked first in the highest number of AIDS sufferers in Indonesia ever reported from 1987-2016 as many as 16,911 people out of a total of 86,780 people. In order to overcome AIDS cases, it is necessary to know the factors that influence it. Data on the percentage of AIDS sufferers and their predictor variables have irregular data patterns or do not match in certain patterns, then the method that can solve these problems is by using the nonparametric regression based on spline truncated estimator. A spline truncated estimator is a segmented polynomial function that has better flexibility because there are knot points indicating changes in data behaviour patterns. The data that used in this study is a secondary data in 2016 obtained from the East Java Provincial Health Office. The results showed that the determination coefficient (R2) based on the best model of 93.84%. This shows that the variables of health facilities, blood donors, health workers, condom users, and residents of 25-29 years are able to explain 93.84% of the percentage of AIDS sufferers in East Java Province in 2016.
ANALISIS SPASIAL UNTUK MENGIDENTIFIKASI TINGKAT PENGANGGURAN TERBUKA BERDASARKAN KABUPATEN/KOTA DI PULAU JAWA TAHUN 2017 Eka Amalia; Liza Kurnia Sari
Indonesian Journal of Statistics and Applications Vol 3 No 3 (2019)
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.v3i3.240

Abstract

Unemployment is one of the economic problems faced by many countries. In Indonesia, the total workforce has reached 128.06 million and 7.04 million people are unemployed. The indicator to measure unemployment is open unemployment rate (TPT). Java Island becomes the island with the highest TPT, which is 4.04 million people, equivalent to 63.08 percent. The regions that have high TPT rates tend to be in the western region of Java, while the eastern region of Java is moderate. This is an initial allegation of regional influence so spatial analysis needs to be carried out. On the other hand, not many studies have included territorial effects. This study aims to spatially identify the influence of human development index (IPM), labor force particapation rate (TPAK), minimum wage and the dependency ratio on the number of TPT in Java in 2017 with the geographically weighted regression (GWR) method. The results of this study indicate that there are differences in the influence of IPM, TPAK, minimum wage and the dependency ratio on TPT in each area in Java. The most significant independent variables and have a positive relationship are minimum wage. This research also shows that GWR is suitable to be applied in modeling the number of TPT regencies /cities in Java Island in 2017. The results of this study can be used by the government in determining the right policy by looking at regional aspects in overcoming unemployment.
PEMODELAN DATA TERSENSOR KANAN MENGGUNAKAN ZERO INFLATED NEGATIVE BINOMIAL DAN HURDLE NEGATIVE BINOMIAL Kusni Rohani Rumahorbo; Budi Susetyo; Kusman Sadik
Indonesian Journal of Statistics and Applications Vol 3 No 2 (2019)
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.v3i2.247

Abstract

Health is a very important thing for humanity. One way to look at a person's health condition is through the number of unhealthy days which can also shows the productivity of the community in a region. Modeling the number of unhealthy days which are examples of count data can be done using Poisson regression. Problems that are often faced in data counts are overdispersion and excess zero. Poisson regression cannot be applied to data that experiences both of these. Zero Inflated Negative Binomial and Hurdle Negative Binomial modeling was performed on data with 2 conditions, uncensored and censored. The explanatory variables used are gender, age, marital status, education level, home ownership status and rural-urban status. According to the results of the AIC and RMSE calculation, Zero Inflated Negative Binomial on censored data showed the best performance for estimating the number of unhealthy days.
ON GENERALISATION OF GOMPERTZ-MAKEHAM DISTRIBUTION Akinlolu Olosunde; Tosin Adekoya
Indonesian Journal of Statistics and Applications Vol 4 No 1 (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.v4i1.250

Abstract

In this paper an exponentiated generalised Gompertz-Makeham distribution. An exponentiated generalised family was introduced by Codeiro, et. al., which allows greater flexibility in the analysis of data. Some Mathematical and Statistical properties including cumulative distribution function, hazard function and survival function of the distribution are derived. The estimation of model parameters are derived via the maximum likelihood estimate method.

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