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All Journal Jurnal Aplikasi Statistika & Komputasi Statistik Indonesian Journal of Statistics and Its Applications
Sastri, Ray
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Computer Science & IT Decision Sciences, Operations Research & Management Mathematics Other

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The Application of Partial Proportional Odds Model on Determinants Analysis of Household Food Insecurity Level in Papua, Indonesia Abigael, Rolyn; Sumarni, Cucu; Sastri, Ray
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 17 No 1 (2025): Jurnal Aplikasi Statistika & Komputasi Statistik
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/jurnalasks.v17i1.798

Abstract

Introduction/Main Objectives: Food insecurity in Papua, Indonesia, is still high. However, the study on that issue is limited. This research aims to analyze the determinants of food insecurity in Papua. Background Problems: An ordinal logistic regression can be used. However, this model generally requires the parallel lines assumption. However, somehow, the assumption is often violated. Novelty: This study used a model that relaxes the assumption of parallel lines. This model can capture the condition that some parameters are assumed to meet parallel lines and some do not. Research Methods: In this case, the partial proportional odds model was applied to find the determinant of household food insecurity status by using the National Socioeconomic Survey (SUSENAS) data. Finding/Results: The results show that a female head of household, age 60 years and above, junior high school education and below, has a higher tendency to be at least mildly food insecure, and the effect is the same for each level of food insecurity. Household heads who do not work, work in agriculture, and have household drinking water sources that are not feasible can aggravate the food insecurity level. Meanwhile, food assistance provided by the government influences reducing food insecurity levels.
ANALISIS PENGARUH PENGETAHUAN TENTANG SEKS TERHADAP PERILAKU SEKSUAL REMAJA DI INDONESIA MENGGUNAKAN REGRESI LOGISTIK MULTINOMIAL Pranata, Muhammad Ricky; Sastri, Ray
Indonesian Journal of Statistics and Applications Vol 4 No 1 (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.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.
ESTIMASI KEBUTUHAN IMPOR DAGING SAPI UNTUK KONSUMSI RUMAH TANGGA DI INDONESIA MENGGUNAKAN REGRESI ROBUST Ratnasari, Ratnasari; Sastri, Ray
Indonesian Journal of Statistics and Applications Vol 2 No 2 (2018)
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.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.
ON THE MODELLING OF LEPROSY PREVALENCE IN SOUTH SULAWESI USING SPATIAL AUTOREGRESSIVE MODEL Sabil, Rezki Melany; Sastri, Ray
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.v4i2.529

Abstract

The prevalence of leprosy is the number of leprosy cases per 10.000 peoples. Based on data from the Ministry of Health, the highest prevalenece of leprosy was in South Sulawesi. This is needs a special attention because leprosy is a contagious disease. The number of leprosy cases in an area may be influenced by the number of leprosy case in the neighbor area due to the movement of the air. So that, the location of area need to be included in analysis of leprosy. The aim of this study is to identify the variables that spatially affect the prevalence of leprosy in South Sulawesi and modelling it. This study uses data from the Ministry of Health for year 2016. The method of analysis is Spatial Autoregressive Model (SAR). The results is There is a positive spatial autocorrelation in the prevalence of leprosy in district level, which means that regions with high prevalence of leprosy are surrounded by areas with high prevalence of leprosy, and vice versa. The prevalence of leprosy in an area is influenced by the prevalence of leprosy in neighbor districts, the percentage of BCG vaccines recipient and the percentage of households with healthy lifestyle.
Co-Authors Abigael, Rolyn Pranata, Muhammad Ricky Ratnasari Ratnasari Sabil, Rezki Melany Sumarni, Cucu