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All Journal International Journal of Evaluation and Research in Education (IJERE) Cakrawala Pendidikan JURNAL PENELITIAN ILMU PENDIDIKAN MATEMATIKA DAN PEMBELAJARAN Indiktika : Jurnal Inovasi Pendidikan Matematika Teorema: Teori dan Riset Matematika SJME (Supremum Journal of Mathematics Education) Guru Tua : Jurnal Pendidikan dan Pembelajaran Equals : Jurnal Ilmiah Pendidikan Matematika MATHEMA: JURNAL PENDIDIKAN MATEMATIKA Alifmatika: Jurnal Pendidikan dan Pembelajaran Matematika Koordinat : Jurnal Pembelajaran Matematika dan Sains Aksioma Jurnal Pendidikan Kognitif: Jurnal Riset HOTS Pendidikan Matematika Jurnal Teknik Sipil Pedagogy : Jurnal Pendidikan Matematika SWARNA Journal of Maternal and Child Health Science Indonesian Journal of Education (INJOE) Journal International Journal of Teaching and Learning (INJOTEL) Sciencestatistics: Journal of Statistics, Probability, and Its Application Jurnal Pendidikan MIPA
Suciati, Indah
Universitas Alkhairaat Palu
Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Education Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Nursing Physics Public Health Social Sciences Other

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Journal : Sciencestatistics: Journal of Statistics, Probability, and Its Application

 1 
Analysis of Linear Log Models on Covid-19 Data in Indonesia Suciati, Indah; Warsono, Warsono; Usman, Mustofa
Sciencestatistics: Journal of Statistics, Probability, and Its Application Vol. 1 No. 1 (2023): JANUARY
Publisher : Universitas Muhammadiyah Metro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/sciencestatistics.v1i1.3163

Abstract

Covid-19 is still a concern of the world, including Indonesia. The transmission of Covid-19 is very fast and has a wide impact on all people around the world, especially Indonesia. In everyday life, we find a lot of data that looks into a certain category. Categorical analysis of data can be done using the log linear model. The log linear model is used to analyze the relationship between categorical variables that form a contingency table of arbitrary dimensions. The analysis used in this study is to make descriptive statistics and three-way contingency tables, then perform the analysis with the help of SPSS 25.0 software where the goodness of fit test is used to see which models can be used or suitable. The purpose of this study is to analyze a log linear model, so that a log linear model is obtained that is suitable for Covid-19 data based on gender, province, and age group. The conclusion of this study is that of the 9 models used, the model is the most suitable model to be used, with a value of 18,885 and the equation of the log linear model is , which means that there is a relationship between the two factors for the variables gender and province, gender and age group and province and age group in Covid-19 cases in Covid-19 in Indonesia by gender, province, and age group.
Bayesian Structural Time Series Model for Forecasting the Composite Stock Price Index in Indonesia Suciati, Indah; Usman, Mustofa
Sciencestatistics: Journal of Statistics, Probability, and Its Application Vol. 1 No. 2 (2023): JULY
Publisher : Universitas Muhammadiyah Metro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/sciencestatistics.v1i2.5023

Abstract

One of the models that can be used to predict time series data is the Bayesian Structural Time Series (BSTS) model. The BSTS model is a more modern model and can handle data movement better. In the BSTS model, the Markov Chain Monte Carlo (MCMC) sampling algorithm is used to simulate the posterior distribution, which smoothes the forecasting results over a large number of potential models using Bayesian averaging models. The purpose of this study was to obtain the best BSTS model for Composite Stock Price Index (CSPI) data in Indonesia based on the state component and the number of MCMC iterations, and obtain forecasting results for CSPI value in Indonesia for the next 24 months, namely the period July 2023 to June 2024. The results obtained are based on a comparison of the R-square values in the model, the BSTS model with local linear trend and seasonal state components, and the number of MCMC iterations n = 5 00 is the best BSTS model that can be used for forecasting the CSPI value in Indonesia with an R-square value of 99.96%. The results of forecasting the CSPI value in Indonesia for the period July 2023 to June 2024 range from 6589 to 6760, with the lowest forecasting value in October 2023 and the highest in March 2023.
Growth Model Study Using a Comparison of Gompertz, Logistic, and Weibull Models Suciati, Indah; Vina Nurmadani; Yoga Aji Sukma; Linda Rassiyanti
Sciencestatistics: Journal of Statistics, Probability, and Its Application Vol. 3 No. 2 (2025): JULY
Publisher : Universitas Muhammadiyah Metro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/sciencestatistics.v3i2.9423

Abstract

Coronavirus Disease or COVID-19 has been a concern for the world, including Indonesia. The very rapid transmission of COVID-19 has had a wide impact on all communities around the world, especially Indonesia. To see the transmission of COVID-19 cases, which continues to increase rapidly, we can use a growth model. The growth model is a non-linear regression model that is used to describe growth behavior. These models can be exponential, sigmoidal, or S-shaped curves. The purpose of this study was to determine the growth curve model of positive COVID-19 cases in Indonesia using the Gompertz, Logistic, and Weibull models. After that, the model evaluation will be carried out using the coefficient of determination as a parameter, so that the best model will be obtained that can predict more accurately the growth of positive COVID-19 cases in Indonesia. The best model that can predict the growth of positive COVID-19 cases in Indonesia is the Gompertz model, with a coefficient of determination is 0.99064.
Co-Authors ABDUL MANAF Abdul Manaf Afadil Agus Leo Handoko Al-Afandi Al-Afandi Al-Afandi, Al-Afandi Alfisyahra Anggrainy, Rita Aprilina, Aprilina Ary Analisa Rahma Asmiati Asrullah Asrullah, Asrullah Ayu Anggreni, Made Ayulinansyah, Sri Badjeber, Rafiq Dewi Sri Wahyuni Dewi Sri Wahyuni Dewi Sri Wahyuni Dewi Sri Wahyuni, Dewi Sri Dian Kurniasari Fahrul Basir Gamar Abdullah Hajerina Hajerina Hajerina Hajerina Hajerina Hajerina Hajerina Hajerina Hajerina Hajerina, Hajerina Idrus Idrus Iis Hartati Ismail, Ayu Kasmudin Mustapa Khadijah Khaerani Khaerani Lilies N Tangge Linda Rassiyanti Mailili, Wahyuni H. Marina Marina Mustofa Usman Nasim Taha Nasim Taha Notiragayu Nurhalida Sartika Nursupiamin Nursupiamin, Nursupiamin Okzarima, Wenty Pasandaran, Rio Fabrika Putu Satya Narayanti Sari Wahyuni Sartika, Nurhalida Siti Hadija Alaydrus Sutamrin, Sutamrin Sutji Rochaminah Vina Nurmadani Wahyuni H Mailili Wahyuni H. Mailili Wahyuni H. Mailili Warsono Warsono Warsono Widiarti Windra Windra WINDRA, WINDRA Wulandari Wulandari Yoga Aji Sukma