Jurnal Aplikasi Statistika & Komputasi Statistik
Redaksi menerima karya ilmiah atau artikel penelitian mengenai kajian teori statistika dan komputasi statistik pada bidang ekonomi dan sosial dan kependudukan, serta teknologi informasi. Redaksi berhak menyunting tulisan tanpa mengubah makna subtansi tulisan. Isi jurnal Aplikasi Statistika dan Komputasi Statistik dapat dikutip dengan menyebutkan sumbernya.
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143 Documents
<![CDATA[Kesenjangan Penghasilan antar Gender di Indonesia Tahun 2013 dengan Metode Dekomposisi Blinder-Oaxaca ]]>
<![CDATA[Mardiana Mardiana]]>
<![CDATA[ Jurnal Aplikasi Statistika & Komputasi Statistik Vol 7 No 1 (2015): Journal of Statistical Application and Computational Statistics ]]>
Publisher : <![CDATA[Pusat Penelitian dan Pengabdian Masyarakat Politeknik Statistika STIS ]]>
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DOI: 10.34123/jurnalasks.v7i1.116
<![CDATA[This research aims to find out the gender earnings gap using Blinder-Oaxaca decomposition method. This method divides the causes of the gender earnings gap into endowment factor which is explained by age, education, residence, working hours, activity status, occupation and industry, as well as discrimination factor. Probit work participation did before estimate earnings by gender to eliminate bias in the sample selection. Using Sakernas August 2013, it is found that the gender earnings gap is 47,29 persentage point. Discrimination factor contribution is bigger than endowment factor in explaining the gender earnings gap in Indonesia. The contribution of discrimination factor is 41,40 percentage point (87,53 percent), while endowment factor contribution is 5,9 percentage point (12,47 percent).]]>
<![CDATA[Efisiensi dan Kesenjangan Teknologi Usaha Tani Padi Sawah di Pulau Jawa ]]>
<![CDATA[Mohammad Junaedi]]>;
<![CDATA[Heny K. S. Daryanto]]>;
<![CDATA[Bonar M. Sinaga]]>;
<![CDATA[Sri Hartoyo]]>
<![CDATA[ Jurnal Aplikasi Statistika & Komputasi Statistik Vol 8 No 2 (2016): Journal of Statistical Application and Computational Statistics ]]>
Publisher : <![CDATA[Pusat Penelitian dan Pengabdian Masyarakat Politeknik Statistika STIS ]]>
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DOI: 10.34123/jurnalasks.v8i2.54
<![CDATA[The characteristics of different provinces led to the use of different technologies among wetland rice farming in Java. Such differences lead to the technologthat resulted in incomparable frontier size among provinces. This study analysed the factors affected on the production, efficiency and how the technological gap in wetland rice farming. Meta-frontier analysis is applied in this article to prove that the measure of the technical efficiency level in four Java Island provinces can not be compared among each other. All variable coefficients production function as expected is positive and significant. This study also shows that the utilization of technical efficiency (TE) were measured based on their respective frontier province could lead to biased and misleading policy decisions, so it needs to be given special notes in its analysis.]]>
<![CDATA[Pengelompokkan Wilayah Bencana Endemi Demam Berdarah Dengue di Jawa Timur dengan Fuzzy Geographically Weighted Clustering - Particle Swarm Optimization ]]>
<![CDATA[Fikri Handoko Putra]]>;
<![CDATA[Robert Kurniawan]]>
<![CDATA[ Jurnal Aplikasi Statistika & Komputasi Statistik Vol 8 No 1 (2016): Journal of Statistical Application & Statistical Computing ]]>
Publisher : <![CDATA[Pusat Penelitian dan Pengabdian Masyarakat Politeknik Statistika STIS ]]>
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DOI: 10.34123/jurnalasks.v8i1.10
<![CDATA[DHF is a disease that is a public health problem and is endemic in almost all districts / cities in East Java. The disease is transmitted through the bite of Aedes aegypti and Albopictus. There is currently no anti-viral drugs and vaccines to prevent dengue fever, then to break the chain of transmission, vector control is considered most appropriate at this time, but because the vector is widespread, it is necessary to control the success of the total coverage (covering the whole area) so that mosquitoes can not be multiply. This research was proposed to investigate of classify the endemic regions in East Java based factor that causes dengue vector control can be focused on certain areas that have the highest potential of dengue fever in East Java. This research was used a method FGWC-PSO to classify areas in East Java with the approach of some of the factors associated with an increase in dengue disease. The data will be used is from the publication of the East Java in Figures In 2013, East Java Provincial Health Profile in 2012, and Indonesian Disaster Data and Information in East Java in 2012. Overall, causes the highest number of dengue fever in some areas in East Java province, namely:]]>
<![CDATA[Perancangan Algoritma untuk Menghitung Harga Opsi Reset dengan Metode Binomial ]]>
<![CDATA[Bony Parulian Josaphat]]>
<![CDATA[ Jurnal Aplikasi Statistika & Komputasi Statistik Vol 7 No 1 (2015): Journal of Statistical Application and Computational Statistics ]]>
Publisher : <![CDATA[Pusat Penelitian dan Pengabdian Masyarakat Politeknik Statistika STIS ]]>
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DOI: 10.34123/jurnalasks.v7i1.119
<![CDATA[Reset option is one of exotic options or path-dependent options, namely his payoff option depends on the behavior of the price of the underlying asset between the beginning and the time to maturity, not solely depend on the final price of the underlying asset. Reset option discussed here is the reset option with single reset time . Based on the presence or absence of early exercise facility, reset option consists of an option of European and American.This paper describes the design of algorithms for reset option price calculation using binomial method. Furthermore, in this paper also described the algorithm implementation. Algorithm implementation is done by developing a simple application using Java programming language. After implementing and testing, we obtain results that the designed algorithm is fairly accurate based on a comparison with the results of similar calculation using Ms. Excel .]]>
<![CDATA[Determinan Perilaku Merokok pada Remaja Sekolah di Indonesia ]]>
<![CDATA[Titik Harsanti]]>;
<![CDATA[Febri Wicaksono]]>
<![CDATA[ Jurnal Aplikasi Statistika & Komputasi Statistik Vol 9 No 1 (2017): Journal of Statistical Application and Computational Statistics ]]>
Publisher : <![CDATA[Pusat Penelitian dan Pengabdian Masyarakat Politeknik Statistika STIS ]]>
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DOI: 10.34123/jurnalasks.v9i1.93
<![CDATA[Smoking is a global public health concern and it imposes a heavy economic burden. However, the trend of smoking in Indonesia seems to be increasing and the magnitude of the problem affects not only adults but also adolescents. This paper identifies cigarette smoking determinants among school adolescents in Indonesia, using a multivariate binary logistic model. The analysis uses 5,986 samples of students from the 2014 Indonesia Global Youth Tobacco Survey (GYTS). The results show that 25% of the students have ever smoked and 15% of students are currently smoking. The students’ odds of smoking are higher for boys compared to girls. Higher risk of smoking is observed among the students who have closed-peer smoking compared to students who don’t have closed-peer smoking. Students whose one or both parents are smoking are more likely to smoke compared to whose parents are not smoking. Students who have seen their teacher smoking or have seen people smoking in their house and public places are more likely to smoke compared to who haven’t ever seen their teacher smoking or haven’t ever seen people smoking in their house and public places. These findings suggest that enforcement of legislations to decrease accessibility of cigarettes are necessary to curb the cigarette use among students. Beside that the interventions and education campaigns that target secondary school students are also needed.]]>
<![CDATA[Error Correction Mechanism (ECM) Analysis for Identifying Factors that Influence Tax Income in Indonesia ]]>
<![CDATA[Sugiarto -]]>;
<![CDATA[Merisa Widyasari]]>
<![CDATA[ Jurnal Aplikasi Statistika & Komputasi Statistik Vol 8 No 1 (2016): Journal of Statistical Application & Statistical Computing ]]>
Publisher : <![CDATA[Pusat Penelitian dan Pengabdian Masyarakat Politeknik Statistika STIS ]]>
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DOI: 10.34123/jurnalasks.v8i1.41
<![CDATA[The under necessity of taxpayer number and the low of tax ratio in Indonesia indicate about small tax base revenue. it is contrary to the large population size that should have great potential against the tax. Theoritically, the tax revenue in the country are affected by various factors including Foreign Direct Investment (FDI), Gross Domestic Product (GDP), exports, and imports. This study aimed to analyze the influence of foreign investment (PMA), Gross Domestic Product (GDP), exports and imports to tax revenues in Indonesia in the long term and short term. The analytical method used in this study is Error Correction Mechanism (ECM) with study period 1984-2013. The study results show that in the long term, FDI, export, and import have significant positive impact on tax revenues, while the GDP has no significant positive effect on tax revenue. In the short term, FDI, GDP, export, and import have significant positive impact on tax revenue in Indonesia. The study result can be imply to the imports selection, improving the quality of exported goods and facilitate administration services of investment is the main point to increase tax revenues.]]>
<![CDATA[Aplikasi Small Area Estimation (SAE) Metode Pseudo EBLUP pada Official Statistics di Indonesia ]]>
<![CDATA[Deo Dedianto]]>
<![CDATA[ Jurnal Aplikasi Statistika & Komputasi Statistik Vol 10 No 2 (2018): Journal of Statistical Application and Computational Statistics ]]>
Publisher : <![CDATA[Pusat Penelitian dan Pengabdian Masyarakat Politeknik Statistika STIS ]]>
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DOI: 10.34123/jurnalasks.v10i2.89
<![CDATA[Small Area Estimation (SAE) is a modeling-based estimation method. In practice, SAE that is often used is a type A model, because the availability of auxiliary variables is only available at area level. One of small area estimation method is Empirical Best Linear Unbiased Prediction (EBLUP). When the EBLUP estimation does not include an appropriate and specific sampling weight, it is assumed that the sample is selected by Simple Random Sampling (SRS) which assumes that each unit has the same probability to be selected as a sample. However, the design of Proportional Proportion to Size Sampling (PPS) sampling tends to be better and more efficient to use than SRS because each unit has different probability to be selected as a sample, depending on the size used. One of important indicator / official statistics is household expenditure as a proxy indicator of household poverty measurement. This study included a sampling weight in small area estimate of household expenditure, a case study in East Java Province. The estimation method is Pseudo-EBLUP. Based on the results of the study, Pseudo-EBLUP method produces better precision than the EBLUP method in estimating household expenditure.]]>
<![CDATA[Eksplorasi Small Area Estimation (SAE) Data SUSENAS Triwulanan dengan Add-Ins Rexcel ]]>
<![CDATA[Ibnu Santoso]]>
<![CDATA[ Jurnal Aplikasi Statistika & Komputasi Statistik Vol 10 No 2 (2018): Journal of Statistical Application and Computational Statistics ]]>
Publisher : <![CDATA[Pusat Penelitian dan Pengabdian Masyarakat Politeknik Statistika STIS ]]>
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DOI: 10.34123/jurnalasks.v10i2.122
<![CDATA[Nowadays, the demand of small area data of BPS-Statistics Indonesia is increasing. This condition needs further study about SAE for BPS data. By using SUSENAS quarterly, we want to see how SAE can produce better accuracy for estimation value in small area than design-based. The result show that SAE EBLUP-Fay Herriot can produce better estimation with lower MSE than design-based estimation. This research also create tools to calculate this estimation. The tools was wrapped in Add-Ins Rexcel based on Graphical User Interface ( GUI ). Keywords: EBLUP Fay Herriot, SAE, design-based, SUSENAS, Add-Ins, Rexcel]]>
<![CDATA[Kerentanan Kemiskinan: Pendugaan, Pemetaan, Penciri, dan Rekomendasi Kebijakan pada Data Sampel Kecil ]]>
<![CDATA[Arif Rahman]]>
<![CDATA[ Jurnal Aplikasi Statistika & Komputasi Statistik Vol 10 No 2 (2018): Journal of Statistical Application and Computational Statistics ]]>
Publisher : <![CDATA[Pusat Penelitian dan Pengabdian Masyarakat Politeknik Statistika STIS ]]>
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DOI: 10.34123/jurnalasks.v10i2.77
<![CDATA[Ukuran kemiskinan yang biasa dinyatakan dengan jumlah kemiskinan adalah konsep yang statis karena hanya memberikan gambaran kondisi kesejahteraan pada waktu tertentu. Kenyataannya, kemiskinan adalah kondisi yang sangat dinamis sehingga kemiskinan merupakan fenomena stokastik. Kerentanan kemiskinan rumah tangga perlu diukur, sebagai peluang rumah tangga akan berada pada status tidak miskin atau justru menjadi miskin pada masa mendatang. Isu kerentanan kemiskinan telah menjadi perhatian setelah terjadinya krisis ekonomi di Asia Timur, termasuk Indonesia. Pengukuran kerentanan kemiskinan rumah tangga pada level kecil, yaitu kecamatan, penting dilakukan terkait perlunya kebijakan regional yang tepat sasaran. Tujuan penelitian ini adalah menduga rumah tangga rentan miskin level kecamatan, memetakan, dan menentukan penciri rumah tangga rentan miskin sebagai dasar rekomendasi kebijakan. Studi kasus dilakukan pada Kabupaten Sambas. Metode analisis yang digunakan adalah Vulnerable Expected as Poverty (VEP), Small Area Estimation (SAE) Fay-Herriot EBLUP, dan Analisis Komponen Utama (AKU) Polikhorik. Hasil penelitian menunjukkan bahwa kecamatan dengan proporsi rumah tangga rentan miskin tertinggi adalah Pemangkat dan Teluk Keramat. Hasil ini selanjutnya disajikan dalam gradasi peta dengan sumber data kemiskinan lain sebagai pembanding. Pemetaan menghasilkan kesimpulan bahwa hasil pendugaan kerentanan sudah valid. Selanjutnya, variabel penciri rumah tangga rentan miskin diperoleh 3 komponen utama yaitu wilayah dan perumahan, karakteristik KRT, serta ukuran dan konsumsi rumah tangga. Variabel penciri ini dapat menjadi dasar kebijakan sebagai upaya preventif kemiskinan di Kabupaten Sambas.]]>
<![CDATA[Efisiensi Metode EBLUP pada Small Area Estimation ]]>
<![CDATA[Easbi Ikhsan]]>
<![CDATA[ Jurnal Aplikasi Statistika & Komputasi Statistik Vol 10 No 2 (2018): Journal of Statistical Application and Computational Statistics ]]>
Publisher : <![CDATA[Pusat Penelitian dan Pengabdian Masyarakat Politeknik Statistika STIS ]]>
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DOI: 10.34123/jurnalasks.v10i2.113
<![CDATA[ABSTRAK Kemiskinan merupakan masalah multidimensional yang membutuhkan perhatian pemerintah dan segenap unsur masyarakat yang ada. Hal ini dikarenakan masalah kemiskinan mencakup berbagai aspek kehidupan. Ketersediaan data kemiskinan hingga wilayah terkecil sangat diperlukan agar program dan kebijakan pengentasan kemiskinan dapat dilaksanakan tepat sasaran. Seiring dengan berkembangnya pemerintahan, sistem pengambilan keputusan di setiap daerah membutuhkan ketersediaan data yang akurat dan representatif hingga ke wilayah terkecil. Permasalahan muncul ketika ingin diperoleh informasi kemiskinan untuk area kecil dengan desain survei Susenas Badan Pusat Statistik (BPS). Tingkat presisi hasil estimasi yang diperoleh menjadi rendah karena sampel yang digunakan terlalu sedikit. Hal ini dikarenakan sampling design BPS dirancang untuk estimasi langsung tingkat area yang luas seperti nasional, provinsi, dan kabupaten/kota. Salah satu upaya untuk dapat melakukan estimasi hingga area kecil tanpa harus menambah jumlah sampel adalah Small Area Estimaton (SAE). Pada SAE dengan metode Empirical Based Linear Unbiased Prediction (EBLUP) berbasis area level serta menggunakan variabel penyerta mampu memberikan nilai estimasi yang lebih baik dibandingkan hasil estimasi langsung. Dari sampel yang tersedia, kecukupan presisi SAE dapat diketahui dengan melakukan simulasi bootstrap resampling pada ukuran sampel yang berbeda. Selanjutnya, dilakukan evaluasi dari simulasi yang telah dilakukan dengan melakukan penghitungan nilai relative efficiency sebagai perbandingan Mean Squared Error (MSE) dari SAE dengan estimasi langsung. Hasil penghitungan relative efficiency menunjukkan bahwa estimasi SAE metode EBLUP pada ukuran sampel 60 persen dari ukuran sampel Susenas sudah mampu menghasilkan presisi yang hampir sama dengan estimasi langsung dari sampel Susenas tersebut. Kata kunci: EBLUP, kemiskinan, MSE, relative efficiency, SAE]]>
