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Modeling Factors Influencing Covid-19 Cases in South Sulawesi Using Bayesian Conditional Autoregressive Localised Yassar, La Ode Salman; Shanty, Meyrna Vidya; Mahadtir, Muhamad; Aswi, Aswi; Annas, Suwardi
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 13, No 1 (2024): Maret
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat131606362024

Abstract

South Sulawesi Province is listed as the province with the highest number of Covid-19 cases in the Sulawes island. Research on Covid-19 modeling has been carried out by many researchers, but until now, there has been no research using the Bayesian spatial Conditional Autoregressive Localized model which involves a combination of factors such as distance to the provincial capital, population density, and the number of elderly people in each district in South Sulawesi Province. The aim of this research is to get the best Bayesian Conditional Autoregressive Localized model. The best model is based on four criteria, namely: Deviance Information Criteria, Watanabe Akaike Information Criteria, residuals from Modified Moran's I, and the number of areas included in a group. It was found that model with G=3 by including population density covariates was the best model. A significant factor influencing the increase in Covid-19 cases is the population density factor which has a positive effect. This shows that the more densely populated an area is, the greater the chance of being infected with Covid-19. Makassar has the highest relative risk value for Covid-19 followed by Toraja district and Pare-Pare City. Meanwhile, Bone district has the lowest relative risk value for Covid-19, followed by Wajo district and Enrekang district.
Statistical Modeling and Factors Influencing School Dropout in Indonesia: A Review Shanty, Meyrna Vidya; Mahadtir, Muhamad; Awaluddin, Awaluddin; Natalia, Derliani; Ramadani, Reski Aulia; Aswi, Aswi
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 13, No 1 (2024): Maret
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat131608032024

Abstract

The education enrollment rate is crucial for Indonesia to improve its human resources and sustain its economic development. In reality, the dropout student rate is still relatively high. Previous research has highlighted several factors and models related to the dropout student rate in Indonesia. The purpose of the study is to identify the most popular statistical modeling and factors influencing school dropout in Indonesia. We searched in February 2023 using ScienceDirect, ProQuest, and Google Scholar. The search was restricted to refereed journal articles published in English from January 2013 to December 2022. This study underwent four stages: identification, screening, eligibility, and inclusion. The study finds that the most popular statistical modeling is the Logistic Regression Model, and the most significant factor increasing the school dropout rate in Indonesia is family and economic factors. The findings suggest that children who were not attending school came from families with lower levels of education. The well-being of these families was directly linked to their children's educational status. The primary reasons for young students dropping out of elementary and junior schools include an inability to pay school fees and a desire to work on farms to support their parents.
Pelatihan Penulisan Artikel Ilmiah dan Manajemen Referensi bagi Dosen Institut Ilmu Kesehatan Pelamonia Poewanto, Bobby; Aswi, Aswi; Fahmuddin, Muhammad; Sukarna, Sukarna
ADMA : Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol 3 No 2 (2023): ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/adma.v3i2.2516

Abstract

In Indonesia, one of the benchmarks for lecturer performance can be noticed from their publications. Therefore, it is important for lecturers to continue improving their knowledge and skills in writing a scientific article such as reference management skills. Prior to the service activities, an analysis of problems related to writing a scientific article was carried out. The service activity began with a pre-test to measure the extent of the participants' understanding in writing a scientific article and reference management. Furthermore, two trainings namely scientific article writing training and reference management training were presented by the speakers. After the training, a discussion session was held between the participants and team. The activity ends with a post-test to measure the extent to which the participants' knowledge and skills have increased in scientific article writing and reference management. Reflection on the implementation of this program is carried out by team leader and team to review all the benefits and weakness of this program and its implementation. Partners in this service are Lecturers of Institut Ilmu Kesehatan Pelamonia with 46 participants. The results achieved in this service are: before the presentation of the material, 75% of the participants still lacked in understanding regarding the writing a scientific article in Reputable International Journals. After the presentation of the material, 93.5% of the participants had understood the writing a scientific article in Reputable International Journals.
Pemberdayaan Masyarakat Sekolah melalui Pelatihan Literasi Data dan Infografis dalam Menciptakan Generasi Melek Data Aswi, Aswi; Poewanto, Bobby; Fakhri, M. Miftach
ADMA : Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol 4 No 2 (2024): ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/adma.v4i2.3351

Abstract

This activity aims to improve data literacy competencies so that participants are able to process data and turn it into information, as well as being able to create infographics from the processed data. There were 19 training participants in this activity consisting of 15 students and 4 teachers who taught crafts at Sekolah Menengah Atas Negeri 8 Gowa. The method of this activity consists of 3 main activities, namely the first is online data collection training which aims to find out tools that can help in data collection and how to arrange question items on the instrument. The second main activity is training in simple data processing using various kinds of diagrams available in Microsoft Excel as well as material on descriptive statistics which includes measures of central symptoms and measures of data spread. Finally, the participants were given infographic design training using Canva with the aim of simplifying the results of data processing that was previously carried out into infographics that were more interesting to look at. The results obtained were that the majority of participants felt that there had been great progress from this activity and that this activity was also in accordance with the current competency requirements.
Pemberdayaan Masyarakat Sekolah Melalui Pelatihan Pemanfaatan Data Tracer Study sebagai Upaya Mempercepat Keterserapan Alumni Poerwanto, Bobby; Aswi, Aswi; Rahmat, Abdul
ADMA : Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol 5 No 2 (2025): ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/adma.v5i2.4339

Abstract

Kegiatan ini bertujuan untuk meningkatkan kompetensi literasi data untuk memanfaatkan data tracer study sehingga dapat dijadikan dasar penyusunan program kerja sehingga dapat mempercepat penyerapan alumni di dunia industri, selain itu kegiatan ini juga bertujuan untuk membantu alumni dan mahasiswa tingkat akhir untuk mempersiapkan diri menghadapi tes wawancara kerja. Peserta pelatihan pada kegiatan ini berjumlah 20 orang guru dan tenaga kependidikan, serta 20 orang mahasiswa tingkat akhir dan alumni. Materi yang diberikan merupakan standar pelaksanaan dan pemanfaatan data tracer study, pengolahan data dan persiapan wawancara kerja. Hasil diukur dari respon peserta berupa kesesuaian materi dengan kebutuhan peserta, tingkat kesulitan materi yang diterima, sistematika narasumber dalam menjelaskan, dan tingkat penguasaan materi oleh narasumber. Hasilnya, mayoritas memberikan respon sangat jelas. Dari kegiatan ini, pihak sekolah sudah mengetahui standar pelaksanaan tracer study, sudah mampu mengolah data tracer study menjadi informasi untuk membuat program kerja, dan sudah mampu membuat laporan pelaksanaan tracer study untuk kebutuhan akreditasi.
Negative Binomial Regression Analysis of Factors Influencing Stunting Cases in Central Lombok Regency Putri Ananda, Elma Yulia; Annas, Suwardi; Ihsan, Hisyam; Sukarna, Sukarna; Aswi, Aswi
Inferensi Vol 7, No 3 (2024)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v7i3.21436

Abstract

Poisson regression is commonly used to model count data, relying on the crucial assumption of equidispersion, where the mean and variance are equal. However, this assumption is often violated in real-world data, which can exhibit overdispersion or underdispersion. When this occurs, the standard Poisson model becomes unsuitable, leading to biased and inaccurate parameter estimates. To address overdispersion in count data, Negative Binomial Regression (NBR) is a viable alternative, as it incorporates an additional parameter to account for variability greater than the mean. Stunting, a condition characterized by significantly impaired growth in infants, has been a primary concern for the Indonesian government during the 2019-2024 period, particularly in Central Lombok district. Reducing stunting rates is critical to ensuring an optimal quality of life for future generations. Despite extensive research on stunting, the application of NBR to analyze factors influencing stunting cases in Central Lombok Regency has not yet been explored. This study aims to implement the NBR model to identify the determinants of stunting in Central Lombok. Data were collected from 29 community health centers (PUSKESMAS) in Central Lombok. The findings indicate that an increase in the number of malnourished toddlers is associated with a corresponding rise in stunting cases. Similarly, a higher prevalence of low-birth-weight infants is linked to an elevated incidence of stunting.
CONWAY-MAXWELL POISSON REGRESSION MODELING OF INFANT MORTALITY IN SOUTH SULAWESI Oktaviana, Oktaviana; Sanusi, Wahidah; Aswi, Aswi; Sukarna, Sukarna; Folorunso, Serifat Adedamola
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.17.1.45-56

Abstract

Overdispersion is a common problem in count data that can lead to inaccurate parameter estimates in Poisson regression models. Quasi-Poisson and negative binomial regressions are often used to address overdispersion but have limitations, especially with small samples. The Conway-Maxwell Poisson (CMP) regression model, an extension of the Poisson distribution, effectively addresses both overdispersion and underdispersion, even with limited data, due to additional parameters that better control data dispersion. The Infant Mortality Rate (IMR) is a critical public health indicator, reflecting healthcare quality and broader social, economic, and environmental factors. Accurate IMR estimation is essential for evaluating health policies. This study aims to (1) identify overdispersion in IMR data from South Sulawesi, (2) model IMR using CMP regression, and (3) identify factors influencing IMR. The dataset includes IMR, Low Birth Weight (LBW), diarrhea, asphyxia, pneumonia, and exclusive breastfeeding. Analysis showed significant overdispersion with a ratio of 4.639, making CMP the optimal model with an AIC of 186.845. Significant factors identified were LBW, asphyxia, pneumonia, and exclusive breastfeeding. These findings advance statistical methodologies for count data analysis and offer a more accurate approach to evaluating public health policies, supporting efforts to reduce infant mortality in South Sulawesi Province.
Pelatihan Penulisan Artikel Ilmiah Internasional dan Tata Kelola Referensi dengan Mendeley Aswi, Aswi; Tiro, Muhammad Arif; Poerwanto, Bobby
SMART: Jurnal Pengabdian Kepada Masyarakat Vol 4, No 2 (2024): Oktober
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/smart.v4i2.63563

Abstract

Tujuan dari kegiatan ini adalah untuk meningkatkan pengetahuan dosen dan mahasiswa STIKES Fatima Parepare dalam menyusun artikel ilmiah untuk jurnal internasional, dan meningkatkan keterampilan dalam menggunakan Mendeley sebagai alat pengelolaan referensi. Kegiatan ini diikuti oleh 27 orang yang berasal dari dosen dan mahasiswa. Pelaksanaan kegiatan ini dimulai dari observasi, identifikasi kebutuhan, pelatihan, pendampingan, serta monitoring dan evaluasi. Hasil dari kegiatan ini adalah peningkatan pengetahuan dan keterampilan pada topik yang dibahas. Selain itu, sekitar 66,6% peserta merasakan pengetahuan dan keterampilannya meningkat secara signifikan. Artinya kegiatan yang dilakukan memberikan dampak kepada peserta sehingga setelah narasumber meninggalkan lokasi kegiatan terjadi sharing ilmu antar peserta sehingga peserta yang belum banyak berkembang juga dapat memahami dan mengimplementasikan materi yang telah diberikan. Peningkatan keterampilan ini diharapkan dapat membantu dosen dan mahasiswa dalam penyusunan artikel ilmiah internasional, proposal penelitian, proposal bantuan pendanaan seperti hibah penelitian dan pengabdian DRTPM, hibah PKM mahasiswa, PPK Ormawa, P2MW atau proposal tugas akhir mahasiswa.Kata Kunci: Artikel Ilmiah, Jurnal Internasional, Mendeley
Metode Geographically Weighted Lasso dalam Pemodelan Tingkat Pengangguran Terbuka di Sulawesi Selatan Isnaini, Wulan Maulia; Aswi, Aswi; Sudarmin, Sudarmin
ESTIMASI: Journal of Statistics and Its Application Vol. 6, No. 1, Januari, 2025 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v6i1.30863

Abstract

The Open Unemployment Rate (TPT) in South Sulawesi which reached 6.07% in 2020 has an impact on the economy and welfare levels. TPT data in South Sulawesi has spatial diversity. To overcome spatial diversity in data analysis, the Geographically Weighted Regression (GWR) method can be used. However, GWR is less than optimal if multicollinearity occurs, so the Geographically Weighted Lasso (GWL) method is more appropriate. Research related to GWL on TPT in South Sulawesi has not been conducted. This study aims to obtain a GWL model with a spatial weighting matrix using a fixed exponential kernel weighting function and identify factors that influence TPT. The data used are TPT, population growth rate, literacy rate, illiteracy rate, average length of schooling, job vacancies, and job seekers. The results of the study showed that the factors influencing TPT were population growth rate, illiteracy rate, average length of schooling, and job vacancies in several districts/cities with an R2 value of 89.4%.
Mapping the Relative Risk of Tuberculosis in Indonesia Using the Bayesian Spatial Conditional Autoregressive Leroux Model Aswi, Aswi; Nurhikmawati, Nurhikmawati; Shanty, Meyrna Vidya; Herman, Nur Taj Alya’; Sukarna, Sukarna
Journal of Mathematics, Computations and Statistics Vol. 8 No. 1 (2025): Volume 08 Nomor 01 (April 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i1.6814

Abstract

Tuberculosis (TB) is an infectious disease caused by infection with the Mycobacterium Tuberculosis bacteria. Indonesia ranks second globally in terms of the number of TB cases, after India, followed by China. Modeling is needed to evaluate the relative risk (RR) of TB cases in Indonesia to identify areas that have a high RR of being infected with the bacteria. One approach used to estimate the RR of TB in Indonesia is Bayesian Conditional Autoregressive (CAR). This research aims to identify the RR rate of TB cases in Indonesia using the Bayesian spatial CAR Leroux approach based on TB case data from 2021 to 2022. The best model selection is based on Deviance Information Criteria values, the Watanabe Akaike Information, and residuals from Modified Moran's I. Analysis results shows that in 2021, the Bayesian spatial CAR Leroux Model with Inverse Gamma prior (0.5; 0.5) is the best model. DKI Jakarta Province has the highest while Bali Province has the lowest RR. In 2022, the Bayesian spatial CAR Leroux Model with Inverse Gamma prior (1;0.01) is the best model, with DKI Jakarta Province still having the highest RR, while Bali still has the lowest RR.