Article Per Year (5 Year)
p-Index From 2021 - 2026
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This Author published in this journals
All Journal Journal of Innovation and Applied Technology ComTech: Computer, Mathematics and Engineering Applications Jambura Journal of Biomathematics (JJBM)
Ani Budi Astuti
Brawijaya University
Computer Science & IT Decision Sciences, Operations Research & Management Engineering Mathematics

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Smart Village: A Means of Empowering the Krisik Village Community through an Intelligent Information System Based on Online Administration Service Solutions Muhammad Teguh Prayoga; Ani Budi Astuti; Gusti Ayu Putu Rawi Rotchildi; Olyvia Maria Kalangi; Muhammad Ariq Deriz Putra; Muhammad Ibnu
Journal of Innovation and Applied Technology Vol 9, No 1 (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.2022.009.01.2

Abstract

Administration is a fundamental need of society. The implementation is still not practical and simple results in a domino effect that can have an impact on other sectors such as the economy. The demographic condition of Krisik Village shows that time inefficiency will result in a lot of losses. Moreover, the absorption of existing village funds shows that the use of paper for administration is still very large which is not in accordance with the 13th point of the Sustainable Development Goals, coupled with the COVID-19 pandemic which has exacerbated the situation with the imposition of various restrictions on sectors in society. Krisik Village needs a solution to facilitate the administrative process in terms of distribution delivery and management in order to create a flexible and efficient system. Thus Smart Village, an application that can accommodate administrative processes at the village level using the Android system, become a solution.
Spatial Modeling of Fixed Effect and Random Effect with Fast Double Bootstrap Approach Wigbertus Ngabu; Henny Pramoedyo; Rahma Fitriani; Ani Budi Astuti
ComTech: Computer, Mathematics and Engineering Applications Vol. 14 No. 1 (2023): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v14i1.8033

Abstract

The use of panel data on spatial regression has many advantages. However, testing the spatial dependency and parameter presumption generated in spatial regression of panel data becomes inaccurate when applied to regions with large numbers of small spatial units. One method of overcoming problems of small spatial unit sizes is the bootstrap method. The research aimed to combine cross-section and time-series panel data. The analysis was performed to extract information based on observations modified by the influences of space or location, known as spatial analysis of panels. The influence of location effects on spatial analysis was presented in the form of weighting. The research applied the Fast Double Bootstrap (FDB) method by modeling poverty rates on Flores Island. The results of the Hausman test show the right model, which is a random effect. Meanwhile, spatial dependency testing concludes spatial dependence and poverty modeling in Flores Island, which is more likely to be the Spatial Autoregressive Random (SAR) model. SAR random effect in modeling value has R2 of 77,38% and does not meet the normality assumption. SAR effect in modeling the FDB approach can explain the diversity of poverty rate in the Flores Island with 88,64% and meets residual normality assumptions. The analysis with the FDB approach on spatial panels shows better results than the common spatial panels.
Geographically Weighted Poisson Regression Modeling Using Adaptive Gaussian Kernel Weighting For Mapping Maternal Mortality Rates In East Java Inayati Ngoro; Henny Pramoedyo; Ani Budi Astuti
Jambura Journal of Biomathematics (JJBM) Volume 6, Issue 4: December 2025
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjbm.v6i4.30411

Abstract

Maternal Mortality Rate (MMR) is a key public health indicator that reflects spatial variation across districts in East Java.  This study aims to model the spatial distribution of MMR using Geographically Weighted Poisson Regression (GWPR) with an Adaptive Gaussian Kernel weighting function. Secondary data were obtained from the 2022 East Java Provincial Health Profile, covering 38 districts and municipalities. The results indicate that GWPR outperforms the classical Poisson regression. The intercept β=2.889 (exp=17.95) suggests an average of 18 maternal deaths in the absence of predictor effects. The coverage of the fourth antenatal care visit (K4) has a significant negative effect ( β=-0.027; exp = 0.973), indicating that a 1% increase in K4 coverage reduces MMR by approximately 2.7%. Conversely, obstetric complications managed by midwives show a significant positive effect (β= = 0.0173; exp = 1.017), meaning that a 1% increase in complications raises MMR by 1.7%. Other predictorsfirst antenatal care visit (K1), ironfolic acid (IFA) supplementation, and number of health workersare not statistically significant. This study underscores the importance of expanding K4 coverage and strengthening complication management as priority strategies to reduce maternal mortality.  Furthermore, GWPR-based mapping enables more targeted maternal health interventions tailored to local characteristics.
Co-Authors Gusti Ayu Putu Rawi Rotchildi Henny Pramoedyo Inayati Ngoro Muhammad Ariq Deriz Putra Muhammad Ibnu Muhammad Teguh Prayoga Olyvia Maria Kalangi Rahma Fitriani Wigbertus Ngabu