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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) FORUM STATISTIKA DAN KOMPUTASI Media Statistika Statistika JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Media Infotama Journal of the Indonesian Mathematical Society KEUNIS JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Informatika Pertanian Jurnal Penelitian Pertanian Tanaman Pangan BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) SINTECH (Science and Information Technology) Journal MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jambura Journal of Mathematics International Journal of Remote Sensing and Earth Sciences (IJReSES) Eksakta : Berkala Ilmiah Bidang MIPA Jurnal Aplikasi Statistika & Komputasi Statistik FIBONACCI: Jurnal Pendidikan Matematika dan Matematika Building of Informatics, Technology and Science ESTIMASI: Journal of Statistics and Its Application Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Natural Xplore: Journal of Statistics STATISTIKA Scientific Journal of Informatics Advance Sustainable Science, Engineering and Technology (ASSET) Indonesian Journal of Statistics and Its Applications Limits: Journal of Mathematics and Its Applications The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Anang Kurnia
School Of Data Science, Mathematics And Informatics, IPB University, Indonesia
Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Neuroscience Physics Transportation Other

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SENSITIFITAS MODEL GARCH UNTUK MENGATASI HETEROKEDASTIK PADA DATA DERET WAKTU Asep Saefuddin; Anang Kurnia; . Sutriyati
FORUM STATISTIKA DAN KOMPUTASI Vol. 10 No. 2 (2005)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

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Abstract

Data deret waktu pada bidang keuangan sering kali memiliki galat yang tidak homogen (heteroskedastik).  Hal ini bersifat alami terutama yang berhubungan dengan resiko memegang aset, dimana semakin besar resiko akan semakin besar pengembalian yang diterima dan sebaliknya. Metode yang cukup sederhana yang menggunakan informasi ragam galat sebelumnya untuk menghitung ragam galat saat ini adalah Model GARCH. Penelitian ini mencoba untuk mempelajari sensitifitas model GARCH dalam mengatasi heterokedastik pada data deret waktu.  Hasil penelitian menunjukkan bahwa kemunculan nilai ekstrim > 1% secara berurutan pada akhir periode, membuat pemodelan berbias untuk berbagai nilai T. Sedangkan apabila ekstrim menyebar secara acak di tengah periode pengamatan, menyebabkan penduga berbias pada T kecil (500). Untuk T=2000, penduga akan bias apabila terdapat nilai ekstrim lebih dari 10, sehingga untuk mendapatkan model yang kekar diperlukan jumlah data cukup besar (lebih dari 1000).  Adapun untuk T kecil, ketika mulai terdapat volatilitas yang besar maka model cenderung untuk bias.   Kata kunci : Heterokedastis, GARCH
PENDEKATAN GENERAL LINEAR MIXED MODEL PADA SMALL AREA ESTIMATION Khairil A. Notodiputro; Anang Kurnia
FORUM STATISTIKA DAN KOMPUTASI Vol. 10 No. 2 (2005)
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Abstract

Small area estimation is commonly used to describe smaller domain or sub-population. Small area estimation is an important measuring instrument to estimate parameter of smaller domain borrowing strength of population parameter estimate through statistical models with random influence. In this paper we showed the contribution of statistical methods in small area estimation using general linear mixed models.   Keywords :       small area estimation,  general linear mixed model
KLASIFIKASI SKOR PROPENSITAS DALAM PENDUGAAN SELANG KEPERCAYAAN BOOTSTRAP UNTUK PERBEDAAN NILAI TENGAH DUA POPULASI . Marzuki; Asep Saefuddin; Anang Kurnia
FORUM STATISTIKA DAN KOMPUTASI Vol. 10 No. 2 (2005)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

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Abstract

The comparison of mean of two populations assumes that there is no other variables influence (covariate) except the difference of the observed variable. In real data, this condition is often unfulfilled. Propensity score classification (PSC) is a method to overcome the case. In this research, we do simulation data to evaluate the method, and as the illustration we do the real data of first semester NMR of IPB postgraduate students in Statistics major. The simulation data is generated by covariates either with the same means or different ones to both groups, each with different parameter () 0,00, 0,25 and 0,50. The bootstrap confidence interval included a distribution which is built from propensity score estimations without the variance estimation.   The result shows that 95% bootstrap confidence interval with PSC method includes the parameter for the same and different covariate distribution respectively as 0,95 and 0,87. This method is suitable only when the sample sizes are larger. The illustration uses real data with covariate age, marital status, graduate (S-1) NMR and occupation as a lecturer or not, the result estimation of 95% bootstrap interval confidence to differentiate NMR of postgraduate Statistics students in IPB between those who came from the universities in Java and outside Java is between -0,13 and 0,72.   Keywords : propensity, bootstrap, covariates
KAJIAN METODE THURSTONE DALAM PENENTUAN ASPEK PENTING PADA SISTEM TRANSAKSI NON TUNAI Hari Wijayanto; Anang Kurnia; Ina Widayanty
FORUM STATISTIKA DAN KOMPUTASI Vol. 12 No. 2 (2007)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

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Abstract

Data persepsi sudah sangat umum diukur dalam skala ordinal.  Thurstone memperkenalkan metode untuk mengolah data ordinal, diantaranya adalah metode Thurstone, metode equal appearing intervals, dan metode successive intervals. Prinsip dasar metode-metode tersebut adalah mentransformasi data dari skala ordinal menjadi interval agar relevan dalam melakukan interpretasi. Selain itu, metode tersebut dapat menilai peringkat suatu atribut dan mengukur seberapa besar perbedaan kepentingan suatu atribut terhadap atribut lainnya. Pada kasus penilaian tingkat kepentingan responden dalam menggunakan transaksi non tunai, hasil uji kesesuaian model pada metode Thurstone dan metode successive intervals menyatakan bahwa model telah cukup baik menggambarkan kondisi data sebenarnya dengan tingkat ketidaksesuaian masing-masing sebesar 2.3% dan 4.5%.  Metode Thurstone relatif tidak sensitif terhadap perubahan bobot atau skala penilaian pada suatu atribut. Metode Thurstone hanya melihat bagaimana hasil penilaian berpasangan antara dua atribut, namun tidak mampu melihat perbedaan penilaian yang diberikan oleh responden terhadap atribut-atribut tersebut. Penilaian tingkat kepentingan dalam menggunakan transaksi non tunai memberikan hasil tiga peringkat tingkat kepentingan paling tinggi dalam melakukan transaksi non tunai secara berutut-turut adalah aspek tingkat kemudahan atau aksesibilitas, tingkat keamanan, dan kecepatan transaksi. Kenyamanan merupakan aspek yang tingkat kepentingannya paling rendah dibandingkan atribut lain. Kata kunci : Metode Thurstone, Transaksi Non Tunai
PENERAPAN RANTAI MARKOV PADA PENGEMBANGAN UJI KETERDUGAAN KUNCI (Markov Chain Technique in Key Predictability Test Development) Sari Agustini Hafman; Anang Kurnia; Agus Buono
FORUM STATISTIKA DAN KOMPUTASI Vol. 17 No. 1 (2012)
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Abstract

One Time Key (OTK) system with key from alphabetical sequences is one of symmetric encryption algorithm that used in Indonesia to protect secret information. Alphabetic sequences in OTK system must be cryptographically secure pseudorandom sequences.  OTK system in Indonesia only tested by overlapping m-tuple test developed by Marsaglia (2005). Overlapping m-tuple test doesn’t check the unpredictability of alphabetical sequences, it just tests distribution form and indpendency of alphabetical sequences. So, an alphabetical sequence in OTK system cannot be used in cryptography application by the reason of unpredictability sequence is unknown.  Because some of Pseudorandom Number Generator (PRNG) algorithm based on block cipher algorithm that has markovian properties, markov chain model used to detect predictability alphabetical sequences. Data in this study consists of two data sources i.e. simulation data that generated from four classes PRNG and OTK system keys in 2005 that used in three communication units of foreign ministry. Simulation data is used to develop key predictability test methodology by find predictability threshold value based on characteristic of match level.  OTK system keys will be predictability tested by comparing characteristic of match level with threshold value that is obtained from simulation data. The first result of this study shows the alphabetical sequence generated by first, second and fourth PRNG class can't be modeled with first-order markov chain until third-order. The third PRNG class, except PRNG LCG1, LCG2, coveyou, rand and randu, also can't be modeled with first order markov chain until third-order. Sequence generated by  LCG2, coveyou, rand and randu are not fit for use in cryptography because it has a high probability to be modeled by  high orders of markov chain (above the order of three). The second result obtains predictability threshold value  with markov chains based on the minimum and maximum match level on the second-order and third-order. The last result shows the size of training data must be greater than the size of the observation data with the best ratio between the size of training data with observational data is 100: 10. The results of testing using 10 times repeated shows that the match level average of the OTK system key match on the all of three-order less than  4.5 x 10-2, so the OTK system the is feasible to  secure information in three communication units. Keywords: One Time Key (OTK), markov chain, PRNG, probability transition, match level 
ESTIMATION OF UNEMPLOYMENT RATE USING SMALL AREA ESTIMATION MODEL BASED ON A ROTATING PANEL NATIONAL LABOR FORCE SURVEY Siti Muchlisoh; Anang Kurnia; Khairil Anwar Notodiputro; I Wayan Mangku
FORUM STATISTIKA DAN KOMPUTASI Vol. 20 No. 2 (2015)
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Abstract

In Indonesia, labor force participation data are collected by Sakernas (National Labor Force Survey). Sakernas is conducted based on a quarterly rotating panel survey. Because of the groups differ according to their time-in-panel and observation strategy, it is possible to the presence of a bias. Besides, there are insufficiency problem of sample size to obtain an adequate precision of direct estimation at the district level. It is necessary to study how to estimate parameter based on a rotating panel survey when sample size is insufficient. Currently, a small area estimation (SAE) model that accomodates the bias component due to the rotation still only assume the effect over time which follows a random walk process, so it is necessary to develop a model that is more general. We propose a SAE model for rotation group level, its combined idea of the time-series multi-level model and the Rao-Yu model. The model will applied to Sakernas data to estimate a quarterly unemployment rate at the district level.Key words : Sakernas, rotating panel survey, time-series multi-level model and Rao-Yu model
SURVIVAL ANALYSIS WITH EXTENDED COX MODEL ABOUT DURABILITY DEBTOR EFFORTS ON CREDIT RISK Iwan Kurniawan; Anang Kurnia; Bagus Sartono
FORUM STATISTIKA DAN KOMPUTASI Vol. 20 No. 2 (2015)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

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Abstract

The application of survival analysis on the data of credit motorcycle financing experiencing bad loans after the credit starts early, with sixteen covariates were considered. The model used in survival analysis is the Cox proportional hazard models. Cox models have the assumption that the proportional hazard assumption. Extended Cox models selected to improve cox proportional hazard models when one or more covariates did not meet the assumption of proportional hazards. Extended cox models is an extension of cox models that involve time-dependent variables. Covariates that do not meet the proportional hazards assumption in the Cox models diinteraksikan extended with functions appropriate time, in order to obtain time-dependent covariates. So on the model covariates that are not dependent on time and time dependent covariates. The parameters of these covariates estimated using partial maximum likelihood method. To determine whether the extended Cox model is a suitable model for the data in a particular case, likelihood ratio test was used. The results indicate that extended Cox models with functions time appropriate, provide the best model.Keywords : Credit Risk, Survival Analysis, Cox Proportional Hazard , Extended Cox Model
LAD-LASSO: SIMULATION STUDY OF ROBUST REGRESSION IN HIGH DIMENSIONAL DATA Septian Rahardiantoro; Anang Kurnia
FORUM STATISTIKA DAN KOMPUTASI Vol. 20 No. 2 (2015)
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Abstract

The common issues in regression, there are a lot of cases in the condition number of predictor variables more than number of observations ( ) called high dimensional data. The classical problem always lies in this case, that is multicolinearity. It would be worse when the datasets subject to heavy-tailed errors or outliers that may appear in the responses and/or the predictors. As this reason, Wang et al in 2007 developed combined methods from Least Absolute Deviation (LAD) regression that is useful for robust regression, and also LASSO that is popular choice for shrinkage estimation and variable selection, becoming LAD-LASSO. Extensive simulation studies demonstrate satisfactory using LAD-LASSO in high dimensional datasets that lies outliers better than using LASSO.Keywords: high dimensional data, LAD-LASSO, robust regression
SMALL AREA ESTIMATION FOR ESTIMATING THE NUMBER OF INFANT MORTALITY USING MIXED EFFECTS ZERO INFLATED POISSON MODEL Arie Anggreyani; _ Indahwati; Anang Kurnia
FORUM STATISTIKA DAN KOMPUTASI Vol. 20 No. 2 (2015)
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Abstract

Demographic and Health Survey Indonesia (DHSI) is a national designed survey to provide information regarding birth rate, mortality rate, family planning and health. DHSI was conducted by BPS in cooperation with National Population and Family Planning Institution (BKKBN), Indonesia Ministry of Health (KEMENKES) and USAID. Based on the publication of DHSI 2012, the infant mortality rate for a period of five years before survey conducted is 32 for 1000 birth lives. In this paper, Small Area Estimation (SAE) is used to estimate the number of infant mortality in districts of West Java. SAE is a special model of Generalized Linear Mixed Models (GLMM). In this case, the incidence of infant mortality is a Poisson distribution which has equdispersion assumption. The methods to handle overdispersion are binomial negative and quasi-likelihood model. Based on the analysis results, quasi-likelihood model is the best model to overcome overdispersion problem. However, after checking the residual assumptions, still resulted that residuals of model formed two normal distributions. So as to resolve the issue used Mixed Effect Zero Inflated Poisson (ZIP) Model. The basic model of the small area estimation used basic area level model. Mean square error (MSE) which based on bootstrap method is used to measure the accuracy of small area estimates.Keywords : SAE, GLMM, Mixed Effect ZIP Model, Bootstrap
MODEL AVERAGING, AN ALTERNATIVE APPROACH TO MODEL SELECTION IN HIGH DIMENSIONAL DATA ESTIMATION Deiby T. Salaki; Anang Kurnia; Arief Gusnanto; I Wayan Mangku; Bagus Sartono
FORUM STATISTIKA DAN KOMPUTASI Vol. 20 No. 2 (2015)
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Abstract

Model averaging is an alternative approach to classical model selection in model estimation. The model selection such as forward or stepwise regression, use certain criteria in choosing one best model fitted the data such as AIC and BIC. On the other hand, model averaging estimates one model whose parameters determined by weighted averaging the parameter of each approximation models. Instead of conducting inference and prediction only based one best chosen model, model averaging covering model uncertainty problem by including all possible model in determining prediction model. Some of its developments and applications also challenges will be described in this paper. Frequentist model averaging will be preferential described.Keywords : model selection, frequentist model averaging, high dimensional data
Co-Authors . Hanniva . Marzuki . Sutriyati Abdullah Ilman Fahmi Achmad Fauzan Achmad Fauzan, Achmad Agus Buono Agus M Soleh Agus Mohamad Soleh Ahmad Ansori Mattjik Ajeng Bita Alfira Aji Hamim Wigena Alkahfi, Cahya Amalia Pasaribu, Asysta Amin, Yudi Fathul Anik Djuraidah Ardiansyah, Muhlis Arie Anggreyani Arief Gusnanto ASEP SAEFUDDIN Astri Fatimah Azka Ubaidillah Bagus Sartono Bambang Sumantri Beny Trianjaya Budi Susetyo Budi Waryanto Cici Suhaeni Citra Jaya Dede Dirgahayu Dede Dirgahayu Deiby T Salaki Dewi Juliah Ratnaningsih Dhea Dewanti Dian Handayani Dian Kusumaningrum Dian Kusumaningrum Dian Kusumaningrum, Dwi Agustin Nuriani Sirodj Dwi Wahyu Triscowati Efriwati Efriwati Erfiani Erfiani Erfiani Erwan Setiawan, Erwan Farit Mochamad Afendi Farit Mohamad Afendi Fauzi, Fatkhurokhman Fauziah, Ghina Febryna Sembiring Fitri Dewi Shyntia Fitrianto, Anwar Fitriyani Sahamony, Nur Gerry Alfa Dito Hamid, Assyifa Lala Pratiwi Hamim Wigena, Aji Haq, Irvanal Hari Wijayanto Hari Wijayanto Hari Wijayanto Hestiani Wulandari Hidayat, Agus Sofian Eka Hidayat, Muhammad I Made Sumertajaya I Wayan Mangku Ikhlasul Amalia Rahmi Ina Widayanty Indah Herlawati Indahwati Indonesian Journal of Statistics and Its Applications IJSA Ita Wulandari Iwan Kurniawan Khairani, Fitri Khairil Anwar Notodiputro Kristuisno Martsuyanto Kapiluka Kusman Sadik Loly, Joao Ferreira Rendes Bean Matualage, Dariani Maulana Achiar, Anshari Luthfi Muhammad Nur Aidi Mulianto Raharjo Nashir, Husnun Newton Newton Nurul Hidayati Pardomuan Robinson Sihombing Pasaribu, Asysta Amalia Pingkan Awalia Pramana, Setia Purba, Widyo Pura Purwanto, Arie Putri, Christiana Anggraeni Rahardiantoro, Septian Rahma Anisa Rahma Anisa Rahman, Gusti Arviana Retsi Firda Maulina Ristiyanti Ristiyanti Rysda Rysda Ryska Putri Madyasari Sahamony, Nur Fitriyani Santoso, Andrianto Santoso, Zein Rizky Sari Agustini Hafman Septiani, Adeline Vinda Setyowati, Indah Rini Siregar, Jodi jhouranda Siskarossa Ika Oktora Siti Muchlisoh Suhaeni, Cici Suprayogi, Muhammad Azis Suprayogi, Muhammad Aziz Teguh Prasetyo Thooriq Ghaith Topan . Ruspayandi Triscowati, Dwi Wahyu Tyas, Maulida Fajrining Utami Dyah Syafitri Viarti Eminita Widiyanto, Rhendy K. P. Widoretno, Widoretno Yani Nurhadryani Yenni Angraini Yenni Kurniawati Yudistira Yudistira Yully Sofyah Waode