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All Journal Media Statistika CAUCHY: Jurnal Matematika Murni dan Aplikasi Journal of Innovation and Applied Technology BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika)
Ani Budi Astuti
Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Brawijaya, Malang
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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Bayesian Hurdle Poisson Regression for Assumption Violation Sa'diyah, Nur Kamilah; Astuti, Ani Budi; Mitakda, Maria Bernadetha T.
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 7, No 3 (2022): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ca.v7i3.15549

Abstract

Violation of the Poisson regression assumption can cause the model formed will produce an unbiased estimator. There is a good method for estimating parameters on small sample sizes and on all distributions, namely the Bayesian method. The number of death from chronic Filariasis data violates the Poisson regression assumption, so it is modeled with the Bayesian Hurdle Poisson Regression. With the Bayesian method, convergence is fullfilled when 300000 iterations and 7 thin are performed. The results showed that in the logit model only one predictor variable had a significant effect on the number of cases of death due to chronic Filiariasis in 34 Provinces in Indonesia . The Truncated Poisson model resulted in all predictor variables having a significant effect on the number of cases of death due to chronic Filariasis.
Community Empowerment of Ngingit Village, Tumpang District, Malang Regency through Suweg Processed Products in the Framework of Raising the Existence of Local Food Ingredients Towards a Food Self-Sufficiency Village Pratikno, Mochammad Yosi; Astuti, Ani Budi; Akrimah, Yasma Aziza Ul; Seftyaningtyas, Endryana; Alvia, Siva Nur; Putro, Bayu Hangga Trio Eko
Journal of Innovation and Applied Technology Vol 8, No 2 (2022)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jiat.2022.008.02.15

Abstract

The program carried out to overcome food problems is CAMPA. The CAMPA program provides training on the processing of local food ingredients, namely suweg into several preparations such as noodles, meatballs, cookies, and cereals. The method used in this study is the Participatory Action Research (PAR) method, a method that involves the dominant role of the community in the concept of empowerment
Sicad: Smart Information System For Village Administration As An Empowering Ngadiluwih Village Kediri In Improving Community Services Astuti, Ani Budi; Nugroho, Waego Hadi; Sumarminingsih, Eni; Rotchildi, Gusti Ayu Putu Rawi; Sa'diyah, Nur Kamilah; Kalangi, Olyvia Maria; Ibnu, Muhammad
Journal of Innovation and Applied Technology Vol 9, No 2 (2023)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jiat.2023.9.2.01

Abstract

The Ngadiluwih Village Government, Kediri Regency, East Java Province also really needs an Android-based application so that the reach of access is wide in an effort to digitize villages to improve village administration services online. The purpose of this community service activity is to build and develop the Ngadiluwih Village Government Smart Information System application, which is abbreviated as Ngadiluwih SICAD in the context of empowering Ngadiluwih Village in an effort to improve online village administration services to the community. The socialization, implementation, and assistance were also carried out to village officials and the community regarding the Ngadiluwih SICAD application product. The results of this activity show that the Ngadiluwih SICAD that has been built is in accordance with the expectations and needs of Ngadiluwih Village and the community with 14 types of letter facilities.
SPATIAL PANEL MODELING OF PROVINCIAL INFLATION IN INDONESIA TO MITIGATE ECONOMIC IMPACTS OF HEALTH CRISES Astuti, Ani Budi; Pramoedyo, Henny; Astutik, Suci; Setiarini, An Nisa Dwi
MEDIA STATISTIKA Vol 17, No 1 (2024): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.17.1.105-116

Abstract

Probabilistic statistical modeling simplifies complex issues, including economic and health challenges, by applying inductive statistics. Spatial panel modeling, using Queen Contiguity weighting, has proven to be essential for analyzing inflation expenditure patterns during health crises, such as COVID-19 in Indonesia. This study highlights the impact of inflation on national economic stability and explores the inter-provincial relationships that influence inflation dynamics across expenditure groups. The purpose of this study is to develop a spatial panel model to address this gap, offering insights for policy and recovery strategies. The results reveal significant spatial interdependence in provincial inflation data, underscoring the role of spatial factors in economic analysis. Two models are identified: Spatial Autoregressive Model with Random Effects (SAR-RE) before the crisis and Spatial Error Model with Random Effects (SEM-RE) during the crisis. Transportation facilities consistently affect inflation, demonstrating the effectiveness of spatial panel modeling in guiding policies for economic stability and recovery.
An Informative Prior of Bayesian Kriging Approach for Monthly Rainfall Interpolation in East Java Damayanti, Rismania Hartanti Putri Yulianing; Astutik, Suci; Astuti, Ani Budi
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 3 (2025): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i3.31027

Abstract

In spatial data analysis, interpolation is used to estimate values at unobserved locations, but often faces challenges in capturing complex spatial patterns and estimation uncertainty. One of the main obstacles is the small sample size, which makes the empirical variogram difficult to define well in conventional Kriging methods. The Bayesian Kriging approach overcomes this problem by integrating prior information, so it can still produce stable estimates despite limited data. This study is a quantitative, spatial-based research aimed at interpolating monthly rainfall in East Java Province using the Bayesian Kriging approach. The data consist of monthly rainfall measurements from 11 rain gauge stations distributed across East Java, obtained from the Indonesian Agency for Meteorology, Climatology, and Geophysics (BMKG) for the period of January to April 2024. The entire analysis was conducted using R software. A spherical semivariogram model was selected due to its superior fit to the spatial characteristics of the rainfall data in the study area with the smallest RMSE 37.17. This study demonstrates the effectiveness of Bayesian Kriging for rainfall interpolation in tropical regions with sparse data, providing more stable and accurate estimates compared to conventional methods. The scientific contribution of this research lies in showcasing how the integration of informative priors and Bayesian inference enhances interpolation accuracy in data-limited tropical environments. The resulting interpolated maps can inform land-use planning and flood risk mitigation by identifying areas of high rainfall for improved water infrastructure and lower-rainfall regions for targeted irrigation planning. 
GENERALIZED CONFIRMATORY FACTOR ANALYSIS FOR KNOWING IMPACT OF KNOWLEDGE, ATTITUDES, AND BEHAVIORAL FACTORS HIV/AIDS IN INDONESIA Rahmi, Nur Silviyah; Astutik, Suci; Astuti, Ani Budi; Muhammad, Alifiandi Rafi; Maisaroh, Ulfah; Handayani, Sri
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss2pp0695-0706

Abstract

The cumulative number of detected HIV/AIDS cases in the January – March 2021 period is 9,327, consisting of 7,650 HIV and 1,677 AIDS reported by 498 districts and cities from 514 districts and cities in Indonesia. Human Immunodeficiency Virus (HIV) is the virus that causes Acquired Immunodeficiency Syndrome (AIDS). Several factors that influence the spread of HIV/AIDS include knowledge, attitudes and behavior about HIV/AIDS. Someone who gains knowledge about HIV/AIDS will have high self-confidence and a positive outlook on life and be more optimistic in taking HIV/AIDS prevention actions. The main objective of this study is to determine the influence of external factors which include demographic, social and economic aspects, as well as internal factors which include knowledge, attitudes and behavior to the level of transmission of HIV/AIDS. By using the CFA approach, it can be seen which indicators have the greatest influence on the latent variables of knowledge, attitudes, and behavior or called loading factors. The data used is secondary data from a 5-year survey from the Central Statistics Agency, namely the 2017 Indonesian Demographic and Health Survey (IDHS) published at the end of 2018. The CFA results show that the P11 variable (about known infections) has the largest loading factor value, which is 0.613 in the variable. . hidden. knowledge. In the latent variable of attitude, the S1 variable (about identifying how the respondent knows someone is infected with HIV-AIDS) has the largest loading factor value of 0.514. While the behavioral latent variable, the variable R8 (whether men have been infected with sexually transmitted diseases (STI) with symptoms) has the largest loading factor value, which is 0.954.
CLUSTER FAST DOUBLE BOOTSTRAP APPROACH WITH RANDOM EFFECT SPATIAL MODELING Ngabu, Wigbertus; Fitriani, Rahma; Pramoedyo, Henny; Astuti, Ani Budi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss2pp0945-0954

Abstract

Panel data is a combination of cross-sectional and time series data. Spatial panel analysis is an analysis to obtain information based on observations affected by the space or location effects. The effect of location effects on spatial analysis is presented in the form of weighting. The use of panel data in spatial regression provides a number of advantages, however, the spatial dependence test and parameter estimators generated in the spatial regression of data panel will be inaccurate when applied to areas with a small number of spatial units. One method to overcome the problem of small spatial unit size is the bootstrap method. This study used the fast double bootstrap (FDB) method by modeling the poverty rate in the Flores islands. The data used in the study was sourced from the BPS NTT Province website. The results of Hausman test show that the right model is Random effect. The spatial dependence test concludes that there is a spatial dependence and the poverty modeling in the Flores islands tends to use the SAR model. SAR random effect model R2 shows the value of 77.38 percent and it does not meet the assumption of normality. Spatial Autoregressive Random effect model with the Fast Double Bootstrap approach is able to explain the diversity of poverty rate in the Flores Island by 99.83 percent and fulfilling the assumption of residual normality. The results of the analysis using the FDB approach on the spatial panel show better results than the common spatial panel.
NON HIERARCHICAL K-MEANS ANALYSIS TO CLUSTERING PRIORITY DISTRIBUTION OF FUEL SUBSIDIES IN INDONESIA Astuti, Ani Budi; Guci, Abdi Negara; Alim, Viky Iqbal Azizul; Azizah, Laila Nur; Putri, Meirida Karisma; Ngabu, Wigbertus
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss3pp1663-1672

Abstract

The growth rate of inflation in Indonesia continues to increase from day to day. The inflation rate in Indonesia reached 1.17% in September 2022 which is the highest inflation rate in the last seven years. One of the causes of high inflation is caused by the increasing demand for motor vehicle fuel. Therefore, there is a need for appropriate action from the government in determining related policies. K-Means multivariate cluster analysis is a non-hierarchical cluster method that is popularly used, one of which is used in Machine Learning algorithms, especially Unsupervised Learning. The purpose of this research is to clustering that are priority distribution of subsidies in Indonesia based on the characteristics formed. The data in this study consist of the percentage of poverty, the percentage of total transportation, the percentage of transportation use, and the percentage of area. Data were analyzed using multivariate cluster analysis with the K-Means method. Based on the research results, information was obtained that the data fulfilled a representative sample with value of KMO >50%. In addition, there are 4 optimal clusters which are the results of the calculation of the Elbow and Silhoutte methods, so 4 provincial clusters are formed with their respective characteristics. Cluster 1 is a province that is highly prioritized to receive fuel subsidies, Cluster 2 is a province that is not highly prioritized for fuel subsidies, Cluster 3 is a province that is prioritized to receive fuel subsidies, and Cluster 4 is a province that is not prioritized to receive fuel subsidies.
A STATISTICAL ANALYTICS OF MIGRATION USING BINARY BAYESIAN LOGISTIC REGRESSION Rohmah, Devi Azarina Manzilir; Astuti, Ani Budi; Efendi, Achmad
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss3pp1725-1738

Abstract

Binary logistic regression is utilized in research to understand the relationship between multiple independent variables and a binary response variable. In logistic regression modelling, parameter estimation is regarded as a vital stage. The performance of this estimation is often affected by the sample size and data characteristics, and to deal with this problem, the Bayesian method can be employed as an estimation. This research aims to use Regression Logistic with Bayesian estimation to figure out the determinant of recent in-migrants status in Special Region of Yogyakarta 2021, where Yogyakarta’s recent in-migrants in 2021 took the first position in Indonesia, whereas this city has the lowest regional minimum wage in Indonesia. The Bayesian method was used in this study to obtain a better estimate than previous studies using maximum likelihood estimation, because Bayesian is unbiased for unbalanced cases which are often found in logistic regression. This research results show that particular variables such as resident age, resident marital status, resident main activities, resident latest education, and resident homeownership have significant effect on resident migrating to Special Region of Yogyakarta, Indonesia
Digital Based Administration Service in Ngrendeng and Banjarsari Villages, Selorejo District, Blitar Dewi, Candra; Astuti, Ani Budi; Nuh, Mohammad; Rifan, Mohamad
Journal of Innovation and Applied Technology Vol 11, No 1 (2025)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In facing the challenges of the digital era, Ngrendeng and Banjarsari villages need innovative approaches to improve the efficiency of public services. This activity aims to increase the understanding and ability of village officials and village residents about digital-based village administration services. The application was built by utilizing some technologies that are WhatsApp Chatbot, Google Drive and Google Form. The needs analysis shows that there are differences in service facilities between the two villages, where Banjarsari only focuses on providing information regarding the requirements for submitting certificates, while Ngrendeng allows for digital processing of letters at the same time. The evaluation of the questionnaire shows that the application developed is very appropriate to needs. This activity is published in national mass media Radar Malang, Prasetya Online UB, and Academiamu. In addition, the training module has been registered Intellectual Property Rights to the Indonesian Ministry of Law and Human Rights.
Co-Authors Achmad Efendi Akrimah, Yasma Aziza Ul Alim, Viky Iqbal Azizul Alvia, Siva Nur Azizah, Laila Nur Candra Dewi Damayanti, Rismania Hartanti Putri Yulianing Elfrida Ratnawati Eni Sumarminingsih Guci, Abdi Negara Handayani, Sri Henny Pramoedyo Kalangi, Olyvia Maria Maisaroh, Ulfah Mitakda, Maria Bernadetha T. Mohammad Nuh Muhammad, Alifiandi Rafi Pratikno, Mochammad Yosi Putri, Meirida Karisma Putro, Bayu Hangga Trio Eko Rahma Fitriani Rahmi, Nur Silviyah Rifan, Mohamad Rohmah, Devi Azarina Manzilir Rotchildi, Gusti Ayu Putu Rawi Sa'diyah, Nur Kamilah Seftyaningtyas, Endryana Setiarini, An Nisa Dwi Suci Astutik Waego Hadi Nugroho Wigbertus Ngabu