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PROPORSI KEMISKINAN DI KABUPATEN BOGOR Suhartini, Titin; Sadik, Kusman; Indahwati, Indahwati
Sosio Informa Vol 1, No 2 (2015): Sosio Informa
Publisher : Puslitbangkesos

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Kemiskinan merupakan salah satu permasalahan mendasar yang menjadi pusat perhatian pemerintahIndonesia. Aspek penting untuk mendukung strategi penanggulangan kemiskinan adalah ketersediaandata dan informasi yang akurat. Penelitian ini bertujuan untuk menduga proporsi status kemiskinan rumahtangga pada tingkat kecamatan di Kabupaten Bogor dan mengidentifikasi sumber/jenis pekerjaan rumahtangga. Metode yang disusun berdasarkan pendugaan langsung dengan asumsi metode sampel acaksederhana untuk memperoleh penduga proporsi dan berdasarkan tabulasi silang untuk mengetahui latarbelakang jenis pekerjaan yang berdampak pada kemiskinan. Penelitian ini menggunakan data sekunderberupa Survei Sosial Ekonomi Nasional (Susenas) dengan variabel terpilih. Badan Pusat Statistik memilikiprogram pengumpulan data melalui sensus dan survei. Survei tersebut menggunakan metode rancanganpenarikan sampel yang kompleks. Hasil penelitian menunjukkan bahwa rumah tangga miskin di KabupatenProporsi Kemiskinan di Kabupaten Bogor, Titin Suhartini, Kusman Sadik, dan Indahwati 161Bogor sebesar 6,84%. 31,08% rumah tangga miskin berasal dari jenis pekerjaan pertanian tanaman pangan.Hanya 24 kecamatan yang dapat dilakukan pendugaan proporsi status kemiskinan rumah tangga.Pendugaanproporsi rumah tangga miskin terbesar berada di kecamatan Nanggung yaitu sebesar 45%. Untuk mengatasiketerbatasan pendugaan yang dilakukan terhadap 16 kecamatan lainnya dapat menggunakan alternatifmetode pendugaan area kecil.Kata Kunci: pendugaan, proporsi, rumah tangga.

Pemodelan Pengukuran Luas Panen Padi Nasional Menggunakan Generalized Autoregressive Conditional Heteroscedastic Model (GARCH) Iqbal, Teuku Achmad; Sadik, Kusman; Sumertajaya, I Made
Jurnal Penelitian Pertanian Tanaman Pangan Vol 33, No 1 (2014): April 2014
Publisher : Pusat Penelitian dan Pengembangan Tanaman Pangan

This study was aimed to build a model for the estimation of national harvested area of rice by incorporating element of variant heterogeneity and the influence of asymmetry factors on time series data using five types of GARCH models, namely: symmetric GARCH, exponential asymmetric GARCH, quadratic asymmetric GARCH, Threshold GARCH, and non-linear asymmetric GARCH. Those models were compared and evaluated, and then the best model was used to predict the accuracy of the national rice harvested area. The results showed that two types of GARCH had significant coefficient, indicating the validity of the model. Those models were symmetric GARCH and quadratic GARCH models. Based on the value of mean absolute percentage error (MAPE) for the twelve month periods ahead, quadratic GARCH model was better than the symmetric GARCH model. Furthermore, based on the value of mean absolute deviation (MAD) and mean square error (MSE), quadratic GARCH model also seemed to be a better model than symmetric GARCH model. The best model can be used to predict the harvested area in the subsequent year.

A COMPARISON OF POLYTOMOUS MODEL WITH PROPORTIONAL ODDS AND NON-PROPORTIONAL ODDS MODEL ON BIRTH SIZE CASE IN INDONESIA Kurniawati, Yenni; Kurnia, Anang; Sadik, Kusman
MEDIA STATISTIKA Vol 14, No 1 (2021): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.14.1.79-88

The proportional odds model (POM) and the non-proportional odds model (NPOM) are very useful in ordinal modeling. However, the proportional odds assumption is often violated in practice. In this paper, the non-proportional odds model is chosen as an alternative model when the proportional odds assumption is not violated. This paper aims to compare Proportional Odds Model (POM) and Non-Proportional Odds Model (NPOM) in cases of birth size in Indonesia based on the 2017 Indonesian Demographic and Health Survey (IDHS) data. The results showed that in the POM there was a violation of the proportional odds assumption, so the alternative NPOM model was used. NPOM had better use than POM. The goodness of fit shows that the deviance test failed to reject H0, and the value of Mac Fadden R2 is higher than POM. The risk factors that have a significant influence on all categories of birth size are the residence and gender of the child.

There have been two main topics developed by statisticians in a survey, i.e. sampling techniques and estimation methods. The current issues in estimation methods related to estimation of a particular domain having small size of samples or, in more extreme cases, there is no sample available for direct estimation. Sample survey data provide effective reliable estimators of totals and means for large area and domains. But it is recognized that the usual direct survey estimator performing statistic Kusman Sadik
FORUM STATISTIKA DAN KOMPUTASI Vol. 14 No. 2 (2009)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

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There have been two main topics developed by statisticians in a survey, i.e. sampling techniques and estimation methods. The current issues in estimation methods related to estimation of a particular domain having small size of samples or, in more extreme cases, there is no sample available for direct estimation. Sample survey data provide effective reliable estimators of totals and means for large area and domains. But it is recognized that the usual direct survey estimator performing statistics for a small area, have unacceptably large standard errors, due to the circumstance of small sample size in the area. The most commonly used models for this case, usually in small area estimation, are based on generalized linear mixed models. Some time happened that some surveys are carried out periodically so that the estimation could be improved by incorporating both the area and time random effects. In this paper we propose a state space model which accounts for the two random effects and is based on two equation, namely transition equation and measurement equation. Based on a evaluation criterion, the proposed hierarchical Bayes estimator turns out to be superior to both estimated best linear unbiased prediction (BLUP) and the direct survey estimator. The posterior variances which measure accuracy of the hierarchical Bayes estimates are always smaller than the corresponding variances of the BLUP and the direct survey estimates.

METODE E-BLUP DALAM SMALL AREA ESTIMATION UNTUK MODEL YANG MENGANDUNG RANDOM WALK Kusman . Sadik; Khairil Anwar Notodiputro
FORUM STATISTIKA DAN KOMPUTASI Vol. 11 No. 2 (2006)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

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Ada dua topik utama yang menjadi perhatian para statistisi dalam membahas persoalan survei. Yaitu persoalan pengembangan teknik penarikan contoh (sampling technique) dan pengembangan metodologi pendugaan parameter pupulasi (estimation methods). Adapaun persoalan mutakhir dalam metodologi pendugaan adalah menyangkut pendugaan untuk daerah atau domain survei yang memiliki contoh kecil atau bahkan tidak memiliki contoh satupun, Rao(2003). Misalnya survei untuk unit rumah tangga pada suatu survei berskala nasional. Umumnya untuk survei demikian banyaknya contoh rumah tangga untuk tiap kabupaten dalam suatu propinsi sangat kecil (small area). Bahkan bisa terjadi kabupaten tertentu tidak terpilih sebagai daerah survei sehingga contoh rumah tangga dari kabupaten tersebut tidak ada. Metode pendugaan langsung (direct estimation) untuk daerah atau kabupaten yang bersangkutan menjadi tidak layak karena contohnya terlalu kecil. Pada makalah ini akan dipaparkan metode pendugaan daerah kecil (small area estimation) dengan pendekatan pendugaan tidak langsung berbasis model (indirect estimation - model based). Khususnya untuk model yang mengandung langkah acak (random walk). Kata Kunci : direct estimation, indirect estimation, generalized regression, general linear mixed model, empirical best linear unbiased prediction, block diagonal covariance, random walk.

PEMODELAN DATA PANEL SPASIAL DENGAN DIMENSI RUANG DAN WAKTU (Spatial Panel Data Modeling with Space and Time Dimensions) Tendi Ferdian Diputra; Kusman Sadik; Yenni Angraini
FORUM STATISTIKA DAN KOMPUTASI Vol. 17 No. 1 (2012)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

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The modeling of spatial panel data is a method of analysis that include the dimension of space and time. In this analysis, the set of data that is required is a combination of cross sections and time series data, that is, either the data observed in each observation location periodically from time to time. On modeling of panel data, there are three approaches, namely pooled least square model, fixed and random effects model. While on modeling of spatial panel data there are several approaches which is a combination of these three approaches in modeling panel data with spatial autoregression model (SAR) and spatial error model (SEM). This research aims to apply a spatial panel data model analysis to include the dimension of space and time in a model. The data that used in this research is GDP, local revenues, a total population and total regional expenditures of ten districts in Jambi province during the years 2000-2008. The results from spatial panel data analysis obtained that model regression of spatial panel data corresponding to the data is panel data models with fixed effect model and spatial error model. From the results of such analysis can also be seen an increase in R2 compared with panel data analysis.Keywords : the modeling of panel data, the modeling of spatial panel data, SAR, SEM

EBLUP METHOD OF TIME SERIES AND CROSS-SECTION DATA FOR ESTIMATING EDUCATION INDEX IN DISTRICT PURWAKARTA Febriyani Eka Supriatin; Budi Susetyo; Kusman Sadik
FORUM STATISTIKA DAN KOMPUTASI Vol. 20 No. 2 (2015)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

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Since decentralisation was implemented in Indonesia, more detailed information about the condition of an area becomes very necessary to know as an evaluation of development that the government has done. the success development of a region can be seen through the Human Development Index (HDI). HDI consists of three basic dimensions, knowledge as one of that three basic measured by the index of education. This index is measured by the Adult Literacy Rate and Mean Years of Schooling. Education is one of the important factors in improving human development. The enhancement of education index results in increasing the HDI of an area. Purwakarta has a vision that is made as a district that excels in education in West Java, but until now Purwakarta’s education index is still below the West Java province. One step that can be done is to seek information on the education index each district in Purwakarta, with the aim to provide the right policy in each region. Direct estimation of the components forming the HDI for districts is not feasible because these estimates will generate a great value of variance, This is due to the size of the sample used is too small. This study proposes a statistical method by performing the estimation using small area estimation. These estimates using information from surrounding areas that can improve the effectiveness of the sample size and the lower the standard error. Some surveys are conducted regularly every year, in conducting indirect estimation in the survey such as this, efficiency of estimating education index for district level can be improved by including the random effect of the area as well as the random effect of time (Sadik and Notodipuro, 2006). So in this study will be used Empirical Best Linear Unbiased Prediction (EBLUP) by combining the time series and cross-section data for estimating the education index at the level of districts in Purwakarta. The direct estimation of education index produce a larger variance than our methode, it shown by comparing mean square error (MSE) of direct method and indirect method, direct method have the largest MSE.Key words : Indirect Estimation, Small Area Estimator, EBLUP, Time Series and Cross-Section, HDI, Education Index.

A SIMULATION STUDY OF LOGARITHMIC TRANSFORMATION MODEL IN SPATIAL E MPIRICAL BEST LINEAR UNBIASED PREDICTION (SEBLUP) METHOD OF SMALL AREA ESTIMATION Hazan Azhari Zainuddin; Khairil Anwar Notodiputro; Kusman Sadik
FORUM STATISTIKA DAN KOMPUTASI Vol. 20 No. 2 (2015)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

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There have been many studies developed to improve the quality of estimates in small area estimation (SAE). The standard method known as EBLUP (Empirical Unbiased Best Linear Predictor) has been developed by incorporating spatial effects into the model. This modification of the method was known SEBLUP (Spatial EBLUP) since it incorporates the spatial correlations which exist among the small areas. The data obtained (variables of concern) usually have a large variance and tend to have a a nonsymmetric distribution and therefore tend to have nonlinear relationship pattern between concomitant variables and variables of concern. the results showed that the method SEBLUP using logarithmic transformation produces estimator more than the other methods.Keywords : EBLUP, SAE, SEBLUP

PROPORSI KEMISKINAN DI KABUPATEN BOGOR Titin Suhartini; Kusman Sadik; Indahwati Indahwati
Sosio Informa Vol 1 No 2 (2015): Sosio Informa
Publisher : Politeknik Kesejahteraan Sosial

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33007/inf.v1i2.144

Kemiskinan merupakan salah satu permasalahan mendasar yang menjadi pusat perhatian pemerintahIndonesia. Aspek penting untuk mendukung strategi penanggulangan kemiskinan adalah ketersediaandata dan informasi yang akurat. Penelitian ini bertujuan untuk menduga proporsi status kemiskinan rumahtangga pada tingkat kecamatan di Kabupaten Bogor dan mengidentifikasi sumber/jenis pekerjaan rumahtangga. Metode yang disusun berdasarkan pendugaan langsung dengan asumsi metode sampel acaksederhana untuk memperoleh penduga proporsi dan berdasarkan tabulasi silang untuk mengetahui latarbelakang jenis pekerjaan yang berdampak pada kemiskinan. Penelitian ini menggunakan data sekunderberupa Survei Sosial Ekonomi Nasional (Susenas) dengan variabel terpilih. Badan Pusat Statistik memilikiprogram pengumpulan data melalui sensus dan survei. Survei tersebut menggunakan metode rancanganpenarikan sampel yang kompleks. Hasil penelitian menunjukkan bahwa rumah tangga miskin di KabupatenProporsi Kemiskinan di Kabupaten Bogor, Titin Suhartini, Kusman Sadik, dan Indahwati 161Bogor sebesar 6,84%. 31,08% rumah tangga miskin berasal dari jenis pekerjaan pertanian tanaman pangan.Hanya 24 kecamatan yang dapat dilakukan pendugaan proporsi status kemiskinan rumah tangga.Pendugaanproporsi rumah tangga miskin terbesar berada di kecamatan Nanggung yaitu sebesar 45%. Untuk mengatasiketerbatasan pendugaan yang dilakukan terhadap 16 kecamatan lainnya dapat menggunakan alternatifmetode pendugaan area kecil.Kata Kunci: pendugaan, proporsi, rumah tangga.

Overdispersion study of poisson and zero-inflated poisson regression for some characteristics of the data on lamda, n, p Lili Puspita Rahayu; Kusman Sadik; Indahwati Indahwati
International Journal of Advances in Intelligent Informatics Vol 2, No 3 (2016): November 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v2i3.73

Poisson distribution is one of discrete distribution that is often used in modeling of rare events. The data obtained in form of counts with non-negative integers. One of analysis that is used in modeling count data is Poisson regression. Deviation of assumption that often occurs in the Poisson regression is overdispersion. Cause of overdispersion is an excess zero probability on the response variable. Solving model that be used to overcome of overdispersion is zero-inflated Poisson (ZIP) regression. The research aimed to develop a study of overdispersion for Poisson and ZIP regression on some characteristics of the data. Overdispersion on some characteristics of the data that were studied in this research are simulated by combining the parameter of Poisson distribution (λ), zero probability (p), and sample size (n) on the response variable then comparing the Poisson and ZIP regression models. Overdispersion study on data simulation showed that the larger λ, n, and p, the better is the model of ZIP than Poisson regression. The results of this simulation are also strengthened by the exploration of Pearson residual in Poisson and ZIP regression.

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