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All Journal Jurnal Penelitian dan Evaluasi Pendidikan Jurnal Ilmu Sosial dan Ilmu Politik Jurnal Matematika Sains dan Teknologi Jurnal Organisasi Dan Manajemen Communications in Science and Technology Jurnal Ketenagakerjaan Prosiding Seminar Nasional Official Statistics Jurnal Ekonomi Kependudukan dan Keluarga
Agung Priyo Utomo
Sekolah Tinggi Ilmu Statistik
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Kesejahteraan Rumah Tangga dalam Pengaruh Wanita Kepala Rumah Tangga Utomo, Agung Priyo; Rahani, Rini
Jurnal Ilmu Sosial dan Ilmu Politik Vol 17, No 2 (2013)
Publisher : Fakultas Ilmu Sosial dan Ilmu Politik Universitas Gadjah Mada

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Abstract

This study focused on the welfare of the household headed by a working widow, viewed through the assets and the quality of their residence. Household welfare level is based on the wealth index. Ordinal logistic regression analysis show that level of education, age and employment status significantly influence the level of wealth of households headed by them. The higher the educational level of a widow, the household will tend to be richer. The older widows, the smaller tendency to have poor household. Households headed by widows who work in the agricultural sector, have a greater tendency to get a lower level of wealth status compared with who work in the non-agricultural sector.
KAJIAN TENTANG PENGARUH TWO STAGE CLUSTER SAMPLING TERHADAP STATISTIK UJI-F Utomo, Agung Priyo
Jurnal Matematika Sains dan Teknologi Vol 8 No 2 (2007)
Publisher : LPPM Universitas Terbuka

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Abstract

In regression analysis we make several assumptions about the error term. The following assumptions are often made: 1) the error terms are random variables with mean 0; 2) nonautocorrelation; 3) homoscedasticity, and 4) normality. The assumption of identically and independently distributed (iid) observations that underlies regression procedures is called into question when analyzing complex survey data. Particularly the existence of clusters in two stage samples usually exhibit positive intracluster correlation. If we use Ordinary Least Squares (OLS) procedures to make inferences in regression analysis for two stage cluster samples, we will be faced with a problem. This study aims to know the effect of two stage least squares on the F-Statistic. In general, although OLS procedures are unbiased but not fully efficient for estimation of the regression coefficients. Variance of the OLS estimators for the regression coefficients can be larger than the usual OLS variance expression would indicate. Failure to consider this possibility leads to underestimation of variances, with consequences for confidence intervals and the F-Statistic. The effect of intracluster correlation on the F-Statistic is the distortion of its distribution. The F-Statistic will not follow the Central F distribution anymore. Consequently, the hypothesis testing procedure is invalid.
REGRESI ROBUST UNTUK MEMODELKAN PENDAPATAN USAHA INDUSTRI MAKANAN NON-MAKLOON BERSKALA MIKRO DAN KECIL DI JAWA BARAT TAHUN 2013 Utomo, Agung Priyo
Jurnal Matematika Sains dan Teknologi Vol 15 No 2 (2014)
Publisher : LPPM Universitas Terbuka

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Abstract

Kontribusi subsektor industri makanan, minuman, dan tembakau merupakan penyumbang terbesar Produk Domestik Bruto (PDB) sektor industri pengolahan non-migas Indonesia yaitu sebesar 36,27%. Industri ini mampu menyerap 29,29% tenaga kerja sektor industri. Industri tersebut pada umumnya merupakan industri berskala mikro dan kecil. Penelitian ini bertujuan untuk menganalisis variabel-variabel yang mempengaruhi pendapatan usaha industri makanan bukan jasa (non-makloon) skala mikro dan kecil. Data yang digunakan bersumber dari Survei Tahunan Industri Mikro dan Kecil (IMK) tahun 2013 yang dilakukan oleh Badan Pusat Statistik (BPS). Metode analisis yang digunakan adalah regresi robust karena data menunjukkan terjadinya nilai pencilan (outlier). Hasil penelitian menunjukkan bahwa variabel jumlah pengeluaran, jumlah tenaga kerja, dan jumlah modal berpengaruh terhadap pendapatan usaha industri makanan non-makloon skala mikro dan kecil. Pengeluaran untuk material memiliki nilai elastisitas lebih besar dibandingkan jumlah tenaga kerja dan jumlah modal. Usaha industri makanan non-makloon skala mikro dan kecil, sebaiknya lebih fokus pada peningkatan bahan baku dan bahan-bahan lainnya yang digunakan untuk keperluan produksi jika ingin meningkatkan pendapatan.
FAKTOR-FAKTOR YANG MEMPENGARUHI KEMISKINAN SECARA MAKRO DI LIMA BELAS PROVINSI TAHUN 2007 Saputro, Agung Eddy Suryo; Utomo, Agung Priyo
Jurnal Organisasi dan Manajemen Vol 6 No 2 (2010)
Publisher : LPPM Universitas Terbuka

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Abstract

One factor which influences the success of poverty alleviation program is to determine where the poverty is concentrated. There are 15 provinces that have a value index of poverty depth (P1) higher than the value of P1 Indonesia. This study will describe the characteristics of poverty in 15 provinces; identify key factors affecting poverty at the macro level; and the relationship between each of the major factors in P1. Based on factor analysis obtained there are three main factors that characterize the 15 poor provinces, which are employment, education, and residence. Logistic regression analysis showed the relationship between employment factors and education with the negative P1. Both employment and educational factors have a significant effect on P1. Meanwhile, factor of residence was positively related to P1 but the effect is not significant.
PELUANG PEKERJA WANITA DALAM MEMILIH LAPANGAN PEKERJAAN PERTANIAN DAN NON PERTANIAN DI KOTA BATAM Utomo, Agung Priyo
Jurnal Organisasi dan Manajemen Vol. 2 No. 1 (2006)
Publisher : LPPM Universitas Terbuka

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Abstract

Batam strategically located at the international shipping route; therefore it attracts investors and labor market. About 52% of citizens of Batam is female. The purpose of this research are to identify characteristics of female labor force; to recognize social and demographic factors that influence female labor in selecting job in the city of Batam; and to recognize the probability and tendency of female labor in selecting job by social and demographic aspects. The 2000 population census indicates that social and demographic characteristics influence the way female labor selecting jobs. There is a tendency that younger female labor is more interested working in non-agricultural sector. Female labors with high school education and higher education have larger probability to get jobs in non-agricultural sector as compare to female labor with lower education.
Analisis Pengangguran Milenial Lulusan Perguruan Tinggi di Jawa Barat Tahun 2022 Menggunakan Firth Logit Farihah, Raisa; Utomo, Agung Priyo
Jurnal Ketenagakerjaan Vol 19 No 2 (2024)
Publisher : Pusat Pengembangan Kebijakan Ketenagakerjaan Kementerian Ketenagakerjaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47198/jnaker.v19i2.358

Abstract

In August 2022, Indonesia has an open unemployment rate (TPT) of 5,86 percent with the highest province, West Java at 8,31 percent, which is still quite far from the target of the 2020?2024 National Medium-Term Development Plan (RPJMN) of 3,6?4,3 percent. This situation is exacerbated by the highly educated labour force (diplomas and bachelors) which is only absorbed by 11,81 percent, and the percentage of highly educated millennial unemployment covered by the age of 25?44 years is 46,1 percent. This study was conducted to analyze the general picture and variables that affect millennial unemployment of university graduates in West Java in 2022 using the firth logit method. The data used is raw data from the August 2022 National Labor Force Survey (Sakernas) in West Java. The results of this study are 3.61 percent who have the status of unemployed millennial college graduates, then there are variables of marital status, ownership of training certificates, and work experience have a significant effect on the unemployment status of millennial college graduates in West Java in 2022.
Analisis Spasial Pengaruh Infrastruktur Sosial Dan Infrastruktur Ekonomi Terhadap Kemiskinan Pulau Jawa 2021 Gabriela, Patrisia; Utomo, Agung Priyo
Seminar Nasional Official Statistics Vol 2023 No 1 (2023): Seminar Nasional Official Statistics 2023
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2023i1.1672

Abstract

Java Island is the center of Indonesia's development with poverty problems still a major concern. Compared with other islands, Java Island experienced the highest growth in poverty rate during the COVID-19 phenomenon in 2021. Based on regional characteristics, infrastructure is one of the determinants of poverty. Even today, infrastructure development is one of the five main directions of the government. When considering infrastructure development, Java Island is an island with adequate infrastructure compared to other islands. However, the adequacy of Java Island's infrastructure is not in line with the conditions of the poverty rate in 2021. The pattern of poverty rate distribution among districts/cities on Java Island shows a clustering trend. It is necessary to further analyze the effect of social and economic infrastructure on the poverty rate in Java in 2021 by considering spatial effects. The data used comes from the Central Bureau of Statistics. The analysis method uses the spatial error model (SEM). The results showed a positive spatial autocorrelation in the poverty rate. The results of this study indicate that social (health facilities) and economic infrastructure (access to electric lighting sources and access to adequate sanitation) have a significant effect on the reduction.
Application of spatial error model using GMM estimation in impact of education on poverty alleviation in Java, Indonesia Januardi, Ryan Willmanda; Utomo, Agung Priyo
Communications in Science and Technology Vol 2 No 2 (2017)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.2.2.2017.50

Abstract

Java Island is the center of development in Indonesia, and yet poverty remains its major problem. The pockets of poverty in Java are often located in urban and rural areas, dominated by productive age group population with low education. Taking into account spatial factors in determining policy, policy efficiency in poverty alleviation can be improved. This paper presents a Spatial Error Model (SEM) approach to determine the impact of education on poverty alleviation in Java. It not only focuses on the specification of empirical models but also in the selection of parameter estimation methods. Most studies use Maximum Likelihood Estimator (MLE) as a parameter estimation method, but in the presence of normality disturbances, MLE is generally biased. The assumption test on the poverty data of Java showed that the model error was not normally distributed and there was spatial autocorrelation on the error terms. In this study we used SEM using Generalized Methods of Moment (GMM) estimation to overcome the biases associated with MLE. Our results indicate that GMM is as efficient as MLE in determining the impact of education on poverty alleviation in Java and robust to non-normality. Education indicators that have significant impact on poverty alleviation are literacy rate, average length of school year, and percentage of high schools and university graduates.
Analisis Variabel-variabel yang Memengaruhi Insiden Tuberkulosis di Provinsi Jawa Timur Tahun 2022 Karim, Abdul; Utomo, Agung Priyo
Seminar Nasional Official Statistics Vol 2024 No 1 (2024): Seminar Nasional Official Statistics 2024
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2024i1.2072

Abstract

Tuberculosis is one of the most dangerous infectious diseases in the world and is still a major problem in Indonesia. In 2022, the number of tuberculosis cases in East Java became the second highest nationally and became the province with the highest increase in tuberculosis incidence in Indonesia. This study aims to model the incidence of tuberculosis in East Java Province in 2022. The data used originated from the Central Statistics Agency (BPS) of East Java and the East Java Provincial Health Office. The Robust MM-Estimator method is used in this study. The results showed that the population density variables, the average number of cigarettes per week smoked by residents aged 5 years and older who smoked tobacco, and the number of new OD-HIV cases were found to have a significant positive effect on the incidence of tuberculosis in East Java.. The variable of the percentage of households with a floor area per capita ≤ 7.2 m2 had a significant negative effect on the incidence of tuberculosis in East Java.
Pengaruh ukuran sampel dan intraclass correlation coefficients (ICC) terhadap bias estimasi parameter multilevel latent variable modeling: studi dengan simulasi Monte Carlo Putra, Muhammad Dwirifqi Kharisma; Umar, Jahja; Hayat, Bahrul; Utomo, Agung Priyo
Jurnal Penelitian dan Evaluasi Pendidikan Vol. 21 No. 1 (2017)
Publisher : Graduate School, Universitas Negeri Yogyakarta in cooperation with Himpunan Evaluasi Pendidikan Indonesia (HEPI) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (96.024 KB) | DOI: 10.21831/pep.v21i1.12895

Abstract

Studi ini menggunakan simulasi Monte Carlo dilakukan untuk melihat pengaruh ukuran sampel dan intraclass correlation coefficients (ICC) terhadap bias estimasi parameter multilevel latent variable modeling. Kondisi simulasi diciptakan dengan beberapa faktor yang ditetapkan yaitu lima kondisi ICC (0.05, 0.10, 0.15, 0.20, 0.25), jumlah kelompok (30, 50, 100 dan 150), jumlah observasi dalam kelompok (10, 20 dan 50) dan diestimasi menggunakan lima metode estimasi: ML, MLF, MLR, WLSMV dan BAYES. Jumlah kondisi keseluruhan sebanyak 300 kondisi dimana tiap kondisi direplikasi sebanyak 1000 kali dan dianalisis menggunakan software Mplus 7.4. Kriteria bias yang masih dapat diterima adalah < 10%. Hasil penelitian ini menunjukkan bahwa bias yang terjadi dipengaruhi oleh ukuran sampel dan ICC, penelitian ini juga menujukkan bahwa metode estimasi WLSMV dan BAYES berfungsi lebih baik pada berbagai kondisi dibandingkan dengan metode estimasi berbasis ML.Kata kunci: multilevel latent variable modeling, intraclass correlation coefficients, Metode Markov Chain Monte Carlo THE IMPACT OF SAMPLE SIZE AND INTRACLASS CORRELATION COEFFICIENTS (ICC) ON THE BIAS OF PARAMETER ESTIMATION IN MULTILEVEL LATENT VARIABLE MODELING: A MONTE CARLO STUDYAbstractA monte carlo study was conducted to investigate the effect of sample size and intraclass correlation coefficients (ICC) on the bias of parameter estimates in multilevel latent variable modeling. The design factors included (ICC: 0.05, 0.10, 0.15, 0.20, 0.25), number of groups in between level model (NG: 30, 50, 100 and 150), cluster size (CS: 10, 20 and 50) to be estimated with five different estimator: ML, MLF, MLR, WLSMV and BAYES. Factors were interegated into 300 conditions (4 NG  3 CS  5 ICC  5 Estimator). For each condition, replications with convergence problems were exclude until at least 1.000 replications were generated and analyzed using Mplus 7.4, we also consider absolute percent bias <10% to represent an acceptable level of bias. We find that the degree of bias depends on sample size and ICC. We also show that WLSMV and BAYES estimator performed better than ML-based estimator across varying sample sizes and ICC's conditions.Keywords: multilevel latent variable modeling, intraclass correlation coefficients, Markov Chain Monte Carlo method
Co-Authors Abdul Karim Bahrul Hayat, Bahrul Farihah, Raisa Gabriela, Patrisia Januardi, Ryan Willmanda Putra, Muhammad Dwirifqi Kharisma Rini Rahani Samosir, Omas Bulan Saputro, Agung Eddy Suryo Sarni Maniar Berliana, Sarni Maniar Sugiarto S Syahida, Inayati Umar, Jahja