Forecasts with SPR Model Using Bootstrap-Reversible Jump MCMC
Suparman 1,*, Eviana Hikamudin 2, Hery Suharna 3, Aryanti 2, In Hi Abdullah 3, Rina Heryani 2
Jurnal Mathematics and Statistics Vol. 12(2), pp. 167 - 174 Bulan Maret Tahun 2024
Abstract
Polynomial regression (PR) is a stochastic model that has been widely used in forecasting in various fields. Stationary stochastic models play a very important role in forecasting. Generally, PR model parameter estimation methods have been developed for non-stationary PR models. This article aims to develop an algorithm to estimate the parameters of a stationary polynomial regression (SPR) model. The SPR model parameters are estimated using the Bayesian method. The Bayes estimator cannot be determined analytically because the posterior distribution for the SPR model parameters has a complex structure. The complexity of the posterior distribution is caused by the SPR model parameters which have a variable dimensional space. Therefore, this article uses the reversible jump MCMC algorithm which is suitable for estimating the parameters of variable-dimensional models. Applying the reversible jump MCMC algorithm to big data requires many iterations. To reduce the number of iterations, the reversible jump MCMC algorithm is combined with the Bootstrap algorithm via the resampling method. The performance of the Bootstrap-reversible jump MCMC algorithm is validated using 2 simulated data sets. These findings show that the Bootstrap-reversible jump MCMC algorithm can estimate the SPR model parameters well. These findings contribute to the development of SPR models and SPR model parameter estimation methods. In addition, these findings contribute to big data modeling. Further research can be done by replacing Gaussian noise in SPR with non-Gaussian noise.
KEYWORDS: Big Data, Bootstrap, Reversible Jump MCMC, Stationary Polynomial Regression
Analisis Kompetensi Guru dalam Memahami Konsep dan Praktik Penilaian dalam Pembelajaran di Sekolah
Eviana Hikamudin, Aryanti, Dian Peniasiani, Rusdiono Muryanto, Burhan Kurniansyah (Universitas Pendidikan Indonesia)
Jurnal Ideas
Volume: 9 Nomor: 4 Bulan: November Tahun: 2023
Abstract
Teachers' understanding of assessment concepts and practices is an important element in measuring of student learning outcomes, but in reality there are teachers not understand in assessment concept and practice it well. The purpose of this study was to measure the level of teacher understanding of assessment concepts and practicing it in learning. The method used in this study is descriptive analytics. The study sample was teachers from 3 elementary schools in Bandung Regency and surrounding areas. The results showed that as many as 57% of respondents understood the concept of assessment well and 57% of respondents could practice assessment well. The implication is the need to strengthen the understanding of concepts and assessment practices for teachers to improve their competence in learning. In addition, it is necessary to monitor and evaluate by the principal to improve the quality of learning in schools.
Keywords: Assessment concept, assessment practice, learning quality
Pengembangan Bahan Ajar Literasi Finansial untuk Siswa Sekolah Dasar
Suprananto (Universitas Singaperbangsa), Eviana Hikamudin (Universitas Pendidikan Indonesia)
Jurnal Ideas
Volume: 9 Nomor: 3 Bulan: Agustus Tahun: 2023
Abstract
Financial literacy is one of the competencies needed by elementary school students today, but in reality there are not many financial literacy teaching materials available for elementary schools. The purpose of this study is to develop a game-based learning application that is able to improve the competence of elementary school students in financial literacy. The method used in this study is the instrument analysis method by applying the ADDIE model (Analysis, Design, Development, Implementation, Evaluation). The results obtained from this study are an android-based application that can improve student competence in financial literacy called QVICI Pratama which is suitable for grade IV, V, and VI elementary school students. The implication of the results of this study is the need to collect information from users, students and teachers further as feedback for the evaluation and development of the instrument. In addition, it is necessary to expand financial literacy materials for the next level.
Keywords: Financial literacy, learning material, game-based learning
Improving Elementary School Students' Understanding of Literacy and Numeracy Through Digital Applications
Eviana Hikamudin, Arie Rakhmat Riyadi, Aryanti, Dian Peniasiani, Pupun Nuryani, Ridwan Gofur
Mimbar PGSD Undiksha
Volume 11, Number 3, Tahun 2023, pp. 462-467
P-ISSN : 2614-4727, E-ISSN : 2614-4735
ABSTRACT
The challenges of changing times require individuals to have adaptive life skills. Literacy and numeracy skills are two general skills that students need to have. The research aims to analyze elementary school (SD) students' understanding of literacy and numeracy through the use of digital applications in learning. Data collection was carried out through survey techniques using questionnaires, observations, and interviews. The participants in this study were 177 grade 4 (four) elementary school students, four teachers, and two school principals. Processing and analysis of data using descriptive quantitative analysis by combining the results of interviews and observations using a comprehensive analysis technique. The results showed that students' understanding of literacy material reached 39.32, and numeration material reached 34.81. On other aspects, based on the observation of the implementation of learning, it was found that 91% of teachers had delivered literacy and numeracy material in the excellent category. Based on the interviews and field observations, data was obtained that all sample schools had literacy and numeracy strengthening programs and carried them out regularly at school. Strengthening literacy and numeracy using digital application assistance in assessments in schools is currently unable to increase students' understanding of literacy and numeracy significantly.
Keywords: Learning, Numeracy Literacy, Digital Applications
DATA MODELING WITH AUTOREGRESSIVE BASED ON REVERSIBLE JUMP MCMC SIMULATION: COMPARING GAUSSIAN AND LAPLACIAN NOISE
Suparman (UAD), Mahyudin Ritonga (USU), Ahmad Muhammad Diponegoro (UAD), Mohamed Nor Azhari Azman (UPSI), Eviana Hikamudin (UPI)
International Journal of GEOMATE, March, 2022, Vol.22, Issue 91, pp.38-45
ISSN: 2186-2982 (P), 2186-2990 (O), Japan,
ABSTRACT: The autoregressive model (AR) is one of the stochastic models in the time series that is used for forecasting. The AR model is affected by noise which has a distribution. The accuracy in choosing the noise distribution has an impact on the fit of the AR model to the data. This paper presents an AR model in which the noise has a Laplace distribution. And also, the Laplacian AR model is compared with the Gaussian AR model. The Bayesian approach was adopted to estimate the AR model parameters. The Binomial distribution was chosen as the prior distribution for the older model, the uniform distribution was chosen as the prior distribution for the AR model coefficients. The Bayesian estimator for the AR model parameters is calculated based on the posterior distribution with the help of the reversible jump algorithm Markov Chain Monte Carlo (MCMC). The results in this paper indicate that the reversible jump MCMC algorithm is categorized as valid in estimating the parameters of the AR model. Based on a simulation study, this paper shows that the Laplacian AR model can be used as an alternative to approximate an AR model that contains non-Gaussian noise. To support this finding, the research can be studied further from a theoretical point of view. With the help of the reversible jump MCMC algorithm, the Bayesian estimator for the AR model parameters is computed based on the posterior distribution. According to the findings of this paper, the reversible jump MCMC algorithm is suitable for estimating the parameters of the AR model. This research illustrates that the Laplacian AR model can be utilized as an alternative to approximate an AR model with non-Gaussian noise, based on a simulation analysis. The findings can be investigated further from a theoretical standpoint to support this finding.
Keywords: Autoregressive processes, Bayes methods, Gaussian noise, Laplacian noise, Monte Carlo methods
BAYESIAN DETECTION OF SIGNAL UNDER RAYLEIGH MULTIPLICATIVE NOISE BASED ON REVERSIBLE JUMP MCMC
Suparman (UAD), Mohammad Toifur (UAD), Asnul Dahar Minghat (UTM-Malaysia), Eviana Hikamudin (UPI), Mohd Saifullah Rusiman (UTH-Malaysia)
International Journal of GEOMATE, Jan., 2022, Vol.22, Issue 89, pp.24-31
ABSTRACT: Piecewise constant models have been used in signal processing. The signal contains noise so that noise needs to be eliminated. Several research results have used the assumption that noise has a normal, gamma, or laplace distribution. However, the signal may have noise with other distributions. This study aims to propose a piecewise constant model in which noise is assumed to have a Rayleigh distribution. This study also proposes a method for estimating the parameters of a piecewise constant model that contains Rayleigh noise. The parameters of the piecewise constant model were estimated in the Bayesian framework by adopting the reversible jump Markov Chain Monte Carlo (MCMC) method. This research shows that the dimension of the parameter space is a combination of several spaces with different dimensions. Bayes estimators for the parameters of the piecewise constant model cannot be stated explicitly. The reversible jump MCMC method is used to calculate the Bayes estimator. The results of this study have a significant contribution in providing Rayleigh noise as an alternative noise in signal processing. This research has a novelty, namely: the use of Rayleigh noise in the piecewise constant model and the hierarchical Bayesian procedure to estimate the parameters of the piecewise constant model. Further research can be extended to the estimation procedure of the piecewise constant with Weibull noise.
Keywords: Bayesian, Piecewise constant, Rayleigh noise, Reversible jump MCMC, Signal detection
Analisis Kondisi Status Sosial Ekonomi Keluarga Dalam Menunjang Pemenuhan Kebutuhan Pendidikan Anak
Eviana Hikamudin (UPI) Hasan Bisri (UNIDA), Rahman Wahid (UPI)
Edusifa: Jurnal Pendidikan Islam
Volume 7 Nomor 1 (2022) 79 - 87 P-ISSN 2580-0582 E-ISSN 2829-8322
ABSTRACT
Education is an urgent and necessary thing for every individual. As for children, education is a basic need that will support the development of children's mindset, character, and skills. Meeting the educational needs of children is the responsibility of the family, especially parents because the family is the primary and first educational institution for a child. However, in meeting children's educational needs, the condition of the family's socioeconomic status can become a problem in itself. The method used in this research is library research. The study aims to describe the condition of the family's socioeconomic status in supporting the fulfillment of children's education. The results of the study show that the socioeconomic status of the family can have an impact on meeting the educational Needs of children.
Keyword: Education, Status socio economi, Family Education.
