cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Sachnaz Desta Oktarina
Contact Email
sachnazdes@apps.ipb.ac.id
Phone
-
Journal Mail Official
ijsa@apps.ipb.ac.id
Editorial Address
sachnazdes@apps.ipb.ac.id
Location
Kota bogor,
Jawa barat
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
 1   2   3   4   5 
KAJIAN SIMULASI PENDUGAAN SELANG KEPERCAYAAN BOOTSTRAP BAGI ARAH MEDIAN DATA SIRKULAR Cici Suhaeni; I Made Sumertajaya; Anik Djuraidah
Indonesian Journal of Statistics and Applications Vol 2 No 1 (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.v2i1.64

Abstract

The median direction is one of central tendency of circular data. The estimation process usually requires information about sampling distribution of statistic that want to be used as a parameter estimate. Theoretically, sampling distribution derived from population distribution. But, it is not easy to get sampling distribution of median although the population distribution is known. When the sampling distribution cannot be derived easily from population distribution, the bootstrap method can be an alternative to handle it. This study wants to evaluate the effect of increasing concentration parameter to the performance of bootstrap confidence interval estimation for median direction through simulation study. Three methods were used to estimate the interval which are equal-tailed arc (ETA), symmetric arc (SYMA), and likelihood-based arc (LBA). The most important criterion to evaluate them were true coverage and interval width. The simulation results that in general, the increasing of concentration parameter followed by more narrow interval. For small concentration parameter (k<1), all methods give unstable true coverage and interval width. The authors also identify that those three methods produce intervals with identical width when the parameter concentration is 20 or more. In terms of coverage and interval width, the best method was ETA.
PENGGEROMBOLAN DESA/KELURAHAN BERDASARKAN INDIKATOR KEMISKINAN DENGAN MENERAPKAN ALGORITMA TSC DAN K-PROTOTYPES Andrew Donda Munthe; I Made Sumertajaya; Utami Dyah Syafitri
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.v2i2.169

Abstract

Statistic Indonesia (BPS) noted that in 2014 there were 3.270 villages in Nusa Tenggara Timur Province. Most of them have a high percentage of poverty. Therefore, the village clustering based on poverty indicators is very important. The clustering algorithm that can be used on large data size and with mixed variables are Two Step Cluster (TSC) and K-Prototypes. The purpose of this research is to compare of TSC and K-Prototypes algorithm for village clustering in Nusa Tenggara Timur Province based on poverty indicators. The data were taken from 2014 village potential data (PODES 2014) collected by BPS. The best selection criteria for the cluster is the minimum ratio between variance within groups and variance between groups. The result showed that the best clustering algorithm was TSC which had the smallest ratio (2.6963). The best clustering showed that villages in Nusa Tenggara Timur Province divided into six groups with different characteristics.
KAJIAN MODEL PERAMALAN KUNJUNGAN WISATAWAN MANCANEGARA DI BANDARA KUALANAMU MEDAN TANPA DAN DENGAN KOVARIAT Isti Rochayati; Utami Dyah Syafitri; I Made Sumertajaya; 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.v3i1.171

Abstract

Foreign tourist arrivals could be considered as time series data. Modelling these data could make use of internal and external factors. The techniques employed here to model these time series data are SARIMA, SARIMAX, VARIMA, and VARIMAX. SARIMA is a model for seasonal data and VARIMA is a model for multivariate time series data. If some explanatory variables are incorporated and have significant influence on the response, the former two models become SARIMAX and VARIMAX respectively. Three stages of creating the model are model identification, parameter estimation, and model diagnostics. The variables used in this study were foreign tourist visits, international passenger arrivals, inflation rates, currency exchange rates, and Gross Regional Domestic Product (GRDP) over the period of 2010-2017. All four models fulfill their model assumptions and therefore could be applied. The best model of foreign tourist arrivals was VARIMA with the value of MAPE testing data = 6.123.
PENGGUNAAN SUPPORT VECTOR REGRESSION DALAM PEMODELAN INDEKS SAHAM SYARIAH INDONESIA DENGAN ALGORITME GRID SEARCH Galih Hedy Saputra; Aji Hamim Wigena; Bagus Sartono
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.v3i2.172

Abstract

Indonesia as the largest Muslim population country in the world is a very potential market for sharia stocks. Sharia stocks performance can be seen from the Indonesia Sharia Stock Index (ISSI). Stock index modeling is conducted to determine the factors that affect the stock index or to predict the value of the stock index. Modeling using regression analysis is based on assumptions that do not always match with the characteristics of stock data that fluctuate. Support Vector Regression (SVR) method is a non-parametric approach based on machine learning. The problem often encountered in the analysis using SVR is to determine the optimal parameters to produce the best model. The determination of the optimal parameters can be solved by using the grid search algorithm. The purpose of this research is to make ISSI model using SVR with grid search algorithm with independent variable BI Rate, money supply, and exchange rate (USD / IDR). The best SVR model was obtained using weekly data with a total of 343 periods as well as a linear kernel with parameters ε = 0.03 and C = 2. The evaluation of the best model SVR is RMSE of 2.289 and correlation value of 0.873.
ANALISIS AMMI DENGAN RESPON GABUNGAN PADA UJI STABILITAS TANAMAN PADI GOGO DI KABUPATEN PACITAN Abdullah Ilman Fahmi; Rahma Anisa; Anang Kurnia; 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.v3i1.173

Abstract

Gogo rice is one of the results of various rice cultivation development by planting in a dry land. Gogo rice is expected to give yield a better production of paddy in dry rice fields. The varieties Inpago 7, Inpago 8, Inpago 8 IPB, Inpago 9, Inpago 10, Situ Gintung, Situ Patenggang, Situ Bagendit, Gajah Mungkur, Slengreng TG, Slegreng GK, Srijaya, Towuti, Merah Wangi, dan Inpari 24 were used in this study. This study aims to identify the Gogo rice varieties that are stable and superior in six Pacitan Garden Experimental Plant locations based on a combined response using the AMMI method. The AMMI analysis combines an additive variety analysis as the main effects of treatment with multiple principle component analysis by bilinier modeling for interaction effect. This study used two combined responses, which described the plant productivity and the resistancy. The result of this study explained that some varieties, Inpago 8, Inpago 10, and Situ Patenggang, were stable varieties in all planting location based on the combined responses. According to productivity stability and plant resistancy superior gogo rice variety is Inpago 8 and Inpago 10.
MODELLING THE NUMBER OF NEW PULMONARY TUBERCULOSIS CASES WITH GEOGRAPHICALLY WEIGHTED NEGATIVE BINOMIAL REGRESSION METHOD Tsuraya Mumtaz; Agung Priyo Utomo
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.v2i2.175

Abstract

Tuberculosis (TB) is an infectious disease caused by Mycobacterium Tuberculosis. Untill now, TB is still one of the main problems in many countries, especially developing countries. Indonesia ranked second as the country with the highest TB cases in the world in 2015, where most cases were found in Java. This study was conducted to model the number of new pulmonary TB cases in Java by considering the spatial aspects using Geographically Weighted Negative Binomial Regression (GWNBR). GWNBR method was chosen because the data used in this study are overdispered. The result showed that the population density and percentage of healty homes were not significantly influential in each region. While the number of puskesmas, the percentage of smokers, the percentage of good PHBS, the percentage of diabetes mellitus, and the percentage of less IMT were significant in some regions. In general, the GWNBR model was better for modelling the number of new pulmonary TB cases than negative binomial regression and GWPR.
DETERMINAN INISIASI MENYUSU DINI (IMD) WANITA USIA 15-49 TAHUN DI INDONESIA (ANALISIS DATA SDKI 2012) Nur Aini; Budyanra Budyanra; 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.v3i1.176

Abstract

Early Breastfeeding Initiation (EBI) is one of the most effective ways to reduce neonatal mortality in Indonesia. Implementation of EBI in Indonesia in 2012 is still in the "adequate" category according to World Health Organization (WHO) and is in "less" category according to International Baby Food Action Network (IBFAN). Implementation of EBI in Indonesia is still under other ASEAN Association countries such as Philippines, Cambodia and Myanmar. The low application of the EBI is thought to be influenced by maternal factors as well as environmental factors. This study aims to determine the factors that affect the status of EBI in Indonesia and see a general description of the status of EBI based on its characteristics. The data used are raw data of IDHS 2012 and analyzed using logistic regression model of proportional partial ordinal odds. The results obtained are the variables of antenatal care visit, maternal working status, place of residence, place of delivery, method of delivery, and parity are determinant of EBI status in Indonesia.
ANALISIS PENGARUH PENGETAHUAN TENTANG SEKS TERHADAP PERILAKU SEKSUAL REMAJA DI INDONESIA MENGGUNAKAN REGRESI LOGISTIK MULTINOMIAL Muhammad Ricky Pranata; Ray Sastri
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.v4i1.180

Abstract

Sexual impulse will begin to appear in a person when entering adolescent age. The adolescent does different things to fulfill their sexual impulse such as holding hands, hugging, kissing, touching and even having sex. Because this is a new experience to them, they need a lot of information about sexuality such as the reproductive system, sexually transmitted diseases, and others. They can get it in school, the internet, or discuss it with others. The way they deal with their sexual impulse is largely determined by their individual characteristics, knowledge, and discussion partners. This study aims to determine the effect of individual characteristics, knowledge, and information sources on adolescent sexual behavior. This study uses data from the Indonesian Demographic and Health Survey (SDKI) in 2012 with a unit of analysis adolescence age of 15─19 years and is never married. The method of analysis uses multinomial logistic regression with adolescent sexual behavior as response variables divided into three categories; quiet (ignore it), minor sexual activity, and serious (touching the sensitive area and or having sex). The conclusion is the individual's background, sexual knowledge, and sources of information influence sexual behavior both in boy and girl. Serious sexual behavior tends to occur in adolescents who do not attend school, a man who understands about contraception, girls who misunderstand about pregnancy, and those who discuss sexuality with friends.
DETERMINAN PEMILIHAN MODA TRANSPORTASI PEKERJA KOMUTER JABODEBATEK DENGAN MODEL REGRESI LOGISTIK MULTINOMIAL MULTILEVEL Hernanto Adwiluvito; 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.v3i1.184

Abstract

The BPS noted that commuters in Jabodetabek had increased by 400 thousand people from 2001 to 2014. The BPS also recorded that around 81,3% of the commuters in Jabodetabek were workers. A growing number of commuter workers in Jabodetabek makes transportation is very important to support the connection of suburban area and workplace in Jakarta. The result showed that 73% of the commuter workers used private transportation, 19% used ground public transportation and the rest of commuter workers used train. This research use Jabodetabek Commuter Survey 2014 as the main source data to shed light on how socioeconomic factors and spatial attributes affect the selection of a primary mode of transportation for commuter workers. Using multilevel multinomial logistic regression, the result confirm that the age, sex, marital status, ownership of vehicle, travel distance and time have a significant effect in explaining train choice. Furthermore, the result also showed that the age, sex, marital status, income, ownership of vehicle, travel distance and cost are found to be significant in explaining ground public transportation choice.
KAJIAN EFEK SPASIAL KASUS DIFTERI DENGAN GEOGRAPHICALLY WEIGHTED NEGATIVE BINOMIAL REGRESSION (GWNBR) Diva Arum Mustika; Rani Nooraeni; 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.v3i1.185

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.

Page 2 of 20 | Total Record : 192

 1   2   3   4   5 

Filter by Year

2017 2025


Reset
Filter By Issues
All Issue Vol 9 No 1 (2025) Vol 8 No 2 (2024) Vol 8 No 1 (2024) Vol 7 No 2 (2023) Vol 7 No 1 (2023) Vol 6 No 2 (2022) Vol 6 No 1 (2022) Vol 5 No 2 (2021) Vol 5 No 1 (2021) Vol 4 No 4 (2020) Vol 4 No 3 (2020) Vol 4 No 2 (2020) Vol 4 No 1 (2020) Vol 3 No 3 (2019) Vol 3 No 2 (2019) Vol 3 No 1 (2019) Vol 2 No 2 (2018) Vol 2 No 1 (2018) Vol 1 No 1 (2017) More Issue