PROSEDUR PENAKSIRAN PARAMETER MODEL MULTILEVEL MENGGUNAKAN TWO STAGE LEAST SQUARE DAN ITERATIVE GENERALIZED LEAST SQUARE

Dalam pemodelan untuk data hirarki salah satu model yang digunakan yaitu model intersep acak atau biasa disebut juga model efek acak. Penaksiran untuk model intersep acak tidak dapat menggunakan metode kuadrat terkecil biasa. Metode kuadrat terkecil dua tahap (Two Stage Least Square) dapat digunakan untuk mengatsi masalah tersebut (Ringdal 1992). Pendekatan lain yang dapat digunakan adalah metode Generalized Least Square yang memerlukan prosedur iteratif dalam penaksirannya sehingga disebut Iterative Generalized Least Square. Suatu simulasi digunakan untuk membandingkan kedua metode tersebut untuk mencari metode yang terbaik. Kata kunci: Model Regresi Multilevel, Two Stage Least Square, RIGL

PENDEKATAN MODEL MULTILEVEL UNTUK DATA REPEATED MEASURES

Data yang diperoleh dari pengukuran berulang (repeated measures) memiliki struktur data longitudinal. Umumnya data dari pengukuran berulang dianalisis menggunakan ANOVA. Data pengukuran berulang dapat dipandang sebagai data hirarki dua level. Waktu pengukuran didefinisikan sebagai Level 1 dan individu didefinisikan sebagai Level 2. Kemudian model multilevel dapat digunakan untuk data ini. Kelebihan model multilevel untuk data longitudinal adalah model multilevel tetap dapat digunakan pada struktur data yang tidak seimbang (unbalance). Studi simulasi digunakan untuk menunjukkan berbagai keuntungan penggunaan model multilevel pada data pengukuran berulang. Kata kunci: repeated measures, model multileve

Pelanggaran Asumsi Normalitas Model Multilevel Pada Galat Level yang Lebih Tinggi

Secara umum model multilevel digunakan pada populasi yang memiliki struktur hierarki. Dalam data berstruktur hierarki pengamatan-pengamatan diperoleh melalui sampling multistage akibatnya pengamatan-pengamatan tersebut tidaklah benar-benar saling bebas. Analisis multilevel dapat menanggulangi masalah ini dengan menyertakan level yang lebih tinggi ke dalam model. Salah satu asumsi yang digunakan dalam model regresi multilevel, sebut saja 2 level, yaitu galat level 2 berdistribusi normal. Dalam makalah ini dijelaskan secara numerik bagaimana penaksir dari parameter tetap maupun parameter acak dalam model multilevel apabila asumsi normalitas galat level 2 tidak terpenuhi. Kata-kata kunci: Model Regresi Multilevel, intersep acak, metoda kemungkinan maksimum

PENDEKATAN ANALISIS MULTILEVEL RESPON BINER DALAM MENENTUKAN FAKTOR-FAKTOR YANG MEMENGARUHI IMUNISASI LENGKAP

Dalam suatu penelitian survei, terutama yang ukuran populasinya besar, data yang digunakan biasanya merupakan data berjenjang (hierarchy) atau data yang sifatnya tersarang (nested). Salah satu analisis yang bisa digunakan untuk data tersebut adalah Analisis Data Multilevel. Apabila resopn data tersebut biner maka model multilevel yang digunakan model multilevel logistik. Salah satu metode pendugaan untuk model multilevel logistik adalah penalized quasi likelihood. Permasalahan kelengkapan imunisasi anak selain dipengaruhi oleh faktor-faktor pada tingkat keluarga juga dipengaruhi oleh faktor-faktor pada tingkat yang lebih tinggi. Pendekatan analisis multilevel dapat digunakan untuk menyelesaikan permasalahan ini. Kata-kata kunci: model intersep-acak, komponen ragam, penalized quasi likelihood

MCMC Algorithm for Bayesian Heterogeneous Coefficients of Panel Data Model

Panel data models have been applied widely in many subject areas related to economic, social, and epidemiology. In some cases (e.g. epidemiology studies), the phenomena encountered have a complex relationship structured. The risk factors such as house index, healthy behaviour index, rainfall and the other risk factors of particular infectious disease may have different effect on the outcome due to the heterogeneity of cross-section units. The effect of the covariates on outcome could vary over individual and time units. This condition is called as a non-stationary or instability relationship problem. This problem leads to bias and inefficient of the estimators. It is important to examine the heterogeneous coefficients model for avoiding inefficient estimator. We present in detail a statistical estimation procedure of the heterogeneous coefficients for fixed effect panel data model by means of the hierarchical Bayesian estimation approach. The challenges of the Bayesian approaches are finding the joint posterior distribution and developing the algorithm for estimating the parameters of interest. We find that the joint posterior distribution of the heterogeneous coefficients fixed effect panel data model does not follow any standard known distribution form. Consequently, the analytical solution cannot be applied and simulation approach of Markov Chain Monte Carlo (MCMC) was used. We present the MCMC procedure covering the derivation of the full conditional distribution of the parameters model and present step-by-step the Gibbs sampling algorithm. The idea of this preliminary research can be applied in various fields to overcome the nonstationary proble

PEMILIHAN MODEL REGRESI LINIER MULTILEVEL TERBAIK

Linear regression models is used to describe relationship between dependent variable and independent variables. In a survey research, data was used often have hierarchical structure or nested structure. In this research, independent variables can be defined at any level of the hierarchy but dependent variable can only be defined at the lowest level of the hierarchy. Multilevel regression models is one of the methods can be used to analyze this data. Some authors purpose many models can be used to analyze data with hierarchical structures. Deviance as -2 log likelihood was defined as the measure goodness of fit. The difference of the deviance for two nested models was a method for comparing that two models

Analisis Sentimen Ulasan Pengguna Aplikasi E-Samsat Provinsi Jawa Barat Menggunakan Metode BiGRU

Organizing the facilitation of local revenue tasks and public services is one of the main tasks, functions, detailed unit tasks, and work procedures of the West Java Provincial Revenue Agency. One of the public services for the community in improving service to the West Java community is to launch an e-samsat innovation in providing annual Motor Vehicle Tax (PKB) payment services and updating ownership status through an Android-based smartphone application called Samsat Mobile Jawa Barat (SAMBARA) and can be downloaded for free on the Google Play Store. Service satisfaction is an important aspect in service development, therefore research was conducted. This study analyzes the sentiment of the Samsat Mobile Jawa Barat (SAMBARA) application on the Google Play Store by categorizing user reviews into three groups: Positive, Negative, and Neutral. The method chosen is the Bidirectional Gated Recurrent Unit (BiGRU). BiGRU is able to predict user reviews with an accuracy of up to 87.37%, which is considered good and can be used to help the development of service applications in West Java

METODE BAYESIAN DALAM PENAKSIRAN MODEL SPATIAL AUTOREGRESSIVE (SAR) (STUDI KASUS PEMODELAN PENYAKIT TB PARU DI KOTA BANDUNG)

Aplikasi pemodelan spatial ekonometrik dalam berbagai bidang ilmu semakin banyak khususnya dalam ruang lingkup spatial regional dan spatial epidemiologi. Metode ini berkembang karena kemampuan metode ini mengakomodasi adanya ketergantungan spatial dalam data. Analisis ekonometrik biasa tidak mampu memberikan hasil yang baik pada saat data tidak berdistribusi independen. Metode Maksimum likelihood adalah metode yang umumnya digunakan untuk menaksir parameter model spatial econometrics. Namun metode ini tidak cukup baik dalam mengestimasi parameter model pada saat unit spatialnya sangat banyak. Metode alternative Bayesian diperkenalkan untuk mengatasi masalah tersebut. Penelitian ini mengkaji pendekatan metode Bayesian pada model Spatial Autoregresive (SAR). Model SAR merupakan satu dari delapan model spatial ecokometrik yang paling banyak digunakan. Pendekatan Bayesian akan diaplikasikan pada pemodelan kasus TB Paru di Kota BandungKata kunci: Bayesian, Model SAR, Maximum Likelihood, Spatia

Global gold prices forecasting using Bayesian nonparametric quantile generalized additive model

Gold is one of the most attractive commodities and popular investments. Investment experts often recommend investing in gold because gold is one of the safest investments. It is a stable classic hedge, although the conditions of currency volatility or global markets are depreciated. However, the gold price fluctuations can be influenced by some other factors, such as the USD Index, which reflect and measure the strength of the US Dollar currency, and the Index of Dow Jones Industrial Average (DJIA) or a reflection of the political and economic conditions of the stock market. In this study, we conduct a global gold price forecast (USD) based on the USD Index, the DJIA Index, and the influence of time trends. Based on the data's characteristics, we face the fact that the data is nonlinear, contains outliers, and its pattern is not easy to specify parametrically. Due to the complexity of the model, we then propose a more flexible, robust modeling technique called the Bayesian Nonparametric Quantile Generalized Additive Model method. According to the results for the median case, the proposed method shows an accurate forecasting category due to the value of the Mean Absolute Percentage Error, MAPE less than 10 percent

PENGELOMPOKAN RUMAH TANGGA MISKIN DI KECAMATAN TABIR BARAT MENGGUNAKAN METODE LATENT CLASS CLUSTER ANALYSIS

Poverty is one of the problems that becomes concern in all countries. In Indonesia, one of the provinces that has high poverty rates is Jambi (9.12% in 2015).Result of coordination meeting of all Camat in Jambi Province, reported that the Tabir Barat is the poorest sub-district. The condition is caused mostly by inadequate household infrastructure. Therefore it is necessary for grouping households based on the household infrastructure condition to find the household groups which should be prioritized in the development of poverty alleviation. To describe the poverty variable based on household infrastructure, Bappeda uses 9 indicators, that are residential building status, the widest type of floor, the widest type of wall, the widest type of roof, drinking water source, defecation facility, stool drainage, main lighting and cooking fuel. Because of the folowing reasons: the poverty is an unmeasurable latent variable, and indicators of poverty are categorial variables, the Latent Class Cluster analysis were used in this research as a grouping method. The result shows that there are 5 clusters / latent classeswith their respective characteristics of the household in the Tabir Barat