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All Journal SAINSMAT JAM : Jurnal Aplikasi Manajemen JOIV : International Journal on Informatics Visualization Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) Jurnal PAJAR (Pendidikan dan Pengajaran) Jurnal Varian Proximal: Jurnal Penelitian Matematika dan Pendidikan Matematika Panrannuangku Jurnal Pengabdian Masyarakat ARRUS Journal of Mathematics and Applied Science SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam VARIANSI: Journal of Statistics and Its Application on Teaching and Research Indonesian Journal of Fundamental Sciences Venn: Journal of Sustainable Innovation on Education, Mathematics and Natural Sciences ARRUS Jurnal Pengabdian Kepada Masyarakat Jurnal Pendidikan Matematika Parameter: Jurnal Matematika, Statistika dan Terapannya Abdi Kimia : Jurnal Pengabdian Masyarakat Journal of Mathematics, Computation and Statistics (JMATHCOS) International Journal of Accounting and Management Information Systems
Suwardi Annas
STKIP Pembangunan Indonesia Makassar Universitas Negeri Makassar
Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Other

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Analisis Support Vector Regression (SVR) untuk meramalkan Indeks Kualitas Udara di Kota Makassar Rahmat, Rahmat Wahyudi; Annas, Suwardi; Rais, Zulkifli
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 5 No. 03 (2023)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm107

Abstract

Polusi udara merupakan salah satu permasalahan yang belum terselesaikan sampai saat ini terutama di kota besar di Indonesia. Kondisi ini tentu sangat mengkhawatirkan mengingat polutan yang dikeluarkan oleh kendaraan bermotor seperti karbon monoksida (CO), partikulat matter (PM), nitrogen oksida ( ), sulfur dioksida ), dan karbon dioksida ( ) sangat berbahaya bagi kesehatan manusia. Oleh karena itu perlu dilakukan penelitian untuk mengetahui peramalan indeks kualitas udara dimasa mendatang. Maka pada penelitian ini digunakan metode SVR untuk meramalkan indeks kualitas udara di Kota Makassar. SVR merupakan pengembangan Support Vector Machine (SVM) untuk kasus regresi. Dalam penelitian ini metode SVR digunakan dengan kernel terbaik sebagai bantuan penyelesaian masalah non-linier, metode Min – Max Normalization untuk normalisasi data, pembagian data training dan data testing yang digunakan yakni 80%:20%, pemilihan model terbaik dengan Grid Search Optimization. Hasil peramalan yang didapatkan bahwa kelima variabel indeks kualitas udara di kota makassar tergolong baik dengan nilai RMSE yaitu Partikulat (PM10) 0,12352, Sulfur Dioksida ( ) 0,11502, Ozon ( ) 0,13561, Nitrogen dioksida ( ) 0,11380, Karbon Monoksida (CO) 0,00699 artinya kemampuan model dapat mengikuti pola data dengan baik.
Pendekatan Geographically Weighted Regression (GWR) untuk Menganalisis Hubungan PDRB Sektor Pertanian, Kehutanan, dan Perikanan dengan Faktor Pencemaran Lingkungan di Jawa Timur Bakri, Nurul Aulya; Annas, Suwardi; Aidid, Muhammad Kasim
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 6 No. 01 (2024)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm194

Abstract

The Geographically Weighted Regression (GWR) method is a method used to analyze spatial heterogeneity, where the same independent variable gives unequal responses at different locations in a research area. The purpose of this study was to determine the environmental pollution factors that affect GRDP in the agricultural, forestry and fisheries sectors in East Java. The data used in this study are the GRDP of the Agriculture, Forestry and Fisheries sectors in East Java in 2020 along with the environmental pollution factors that are thought to influence it. The results of this study obtained a different model for each district/city. The GWR model shows better results than the multiple linear regression model, as seen from the smallest AIC value and the largest R2
TREND ANALYSIS OF EARLY MARRIAGE CASES IN SOUTH SULAWESI USING VECTOR AUTOREGRESSIVE FOR STUNTING SOLUTION Astuti, Astuti; Sanusi, Wahidah; Annas, Suwardi
Parameter: Jurnal Matematika, Statistika dan Terapannya Vol 4 No 1 (2025): Parameter: Jurnal Matematika, Statistika dan Terapannya
Publisher : Jurusan Matematika FMIPA Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/parameterv4i1pp153-166

Abstract

The purpose of this study is to use the VARmodel to predict and project the number of early marriage cases in South Sulawesi for the upcoming year. The data used in this analysis comes from the Dinas Pemberdayaan, Perlindungan Perempuan dan Anak, and the Pengadilan Tinggi Agama Makassar, covering the period from January 2017 to September 2024. The results indicate that the VAR(2) model is the best choice according to the AIC for determining the optimal lag length. To examine the relationships between variables, a Granger causality test was conducted for each district and city. The findings reveal significant causal relationships in most districts, suggesting that changes in one district can influence early marriage trends in others. The MAE method was used to calculate the prediction error. Some regions, such as Sengkang, Pangkajene, and Pare-Pare, showed an increasing trend in the projected number of early marriage cases from October 2024 to September 2025. In contrast, Barru and Masamba experienced a decline in these cases. Reducing early marriages could help lower rates of stunting, as early marriage is often linked to maternal and child health issues as well as malnutrition. These findings are valuable for developing effective policies aimed at reducing early marriage and its associated consequences for the people of South Sulawesi.
Pendekatan Regresi Nonparametrik Spline Truncated untuk Mengidentifikasi Determinan Angka Kematian Ibu di Indonesia Hidayat, Rahmat; Annas, Suwardi; Aswi, Aswi; Putri, Siti Choiratun Aisyah; Vivianti, Vivianti
Indonesian Journal of Fundamental Sciences Vol 11, No 2 (2025)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26858/ijfs.v11i2.77643

Abstract

Kualitas kesehatan maternal di suatu negara umumnya diukur melalui indikator utama berupa Angka Kematian Ibu (AKI). Penelitian ini menganalisis pengaruh tiga faktor penting terhadap AKI di Indonesia, yaitu persentase perempuan usia 15–49 tahun yang pernah menikah dan memiliki anak hidup, persentase rumah tangga dengan akses sanitasi layak, serta rata-rata lama sekolah. Untuk mengidentifikasi pola hubungan nonlinier antara variabel-variabel tersebut yang tidak dapat dijelaskan secara optimal oleh model regresi parametrik, digunakan pendekatan regresi nonparametrik Spline Truncated. Model ini mampu menangani data dengan pola acak. Hasil estimasi menunjukkan bahwa model terbaik diperoleh dengan nilai Generalized Cross Validation (GCV) minimum sebesar 1,023 dan koefisien determinasi (R²) sebesar 0,9012. Temuan ini mengindikasikan bahwa ketiga variabel prediktor berpengaruh signifikan terhadap AKI dengan bentuk hubungan yang tidak sepenuhnya linier. Hasil penelitian diharapkan dapat menjadi dasar dalam perumusan kebijakan kesehatan yang lebih efektif dan berbasis data untuk menekan angka kematian ibu di Indonesia
Workshop on Student Graduation Decisions Using Statistical Methods at Takalar State Senior High School 7 Annas, Suwardi; Ahmar, Ansari Saleh; Rais, Zulkifli; H.S, Rahmat; Tri Utomo, Agung
ARRUS Jurnal Pengabdian Kepada Masyarakat Vol. 4 No. 2 (2025)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.abdiku4458

Abstract

This community service program was conducted at SMA Negeri 7 Takalar to enhance teachers’ ability to utilize statistical methods specifically logistic regression to support data-driven graduation decisions. The training addressed challenges related to manual graduation assessment processes that often lack objective analytical support. Participants were introduced to the basic concepts of logistic regression, followed by hands-on practice using an interactive R Shiny dashboard to analyze student data and estimate graduation probabilities. The results indicate that teachers were able to understand and apply statistical analysis procedures, interpret logistic regression outputs, and recognize the importance of evidence-based decision-making. This activity not only improved teachers’ data literacy but also supported digital transformation efforts in education and strengthened collaboration between Universitas Negeri Makassar and SMA Negeri 7 Takalar. The program is expected to contribute to more accurate, transparent, and data-informed graduation assessments in the future.
Predicting the Welfare Cost of Premature Deaths Based on Unsafe Sanitation Risk using SutteARIMA and Comparison with Neural Network Time Series and Holt-Winters Annas, Suwardi; Saleh Ahmar, Ansari; Hidayat, Rahmat
JOIV : International Journal on Informatics Visualization Vol 7, No 1 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.1.1685

Abstract

Unhealthy and unsafe sanitation will make it easier for various diseases to attack the body. In addition, unsafe sanitation will also affect a country's economy, including declining welfare, tourism losses, and environmental losses due to the loss of productive land. The research aimed to estimate the welfare cost of premature deaths based on unsafe sanitation risks using the SutteARIMA, Neural Network Time Series, and Holt-Winters. The study analyzed estimates and projections of the welfare cost of premature deaths based on the risks of unsafe sanitation of BRICS countries (Brazil, Russia, Indonesia, China, and South Africa). The data in this research used secondary data. Secondary time series data was taken from the Environment Database of the OECD. Stat. (Mortality and welfare cost from exposure to environmental risks). The data on the study was based on variables: welfare cost of premature deaths, % GDP equivalent, risk: unsafe sanitation, age: all, sex: both, unit: percentage, and data from 2005 to 2019. The three forecasting methods (SutteARIMA, Neural Network Time Series, and Holt-Winters) were juxtaposed in fitting data to see the forecasting methods' reliability and accuracy. The accuracy of forecasting results was compared based on MAPE and MSE values. The results of the research showed that the SutteARIMA and NNAR(1,1) methods were best used to predict the welfare cost of premature deaths in view of unsafe sanitation risks for BRICS countries.
Co-Authors Abdul Rahman Ahmar, Ansari Saleh Aidid, Muhammad Kasim Asfar Astuti - Aswi, Aswi Aswi, Aswi Bakri, Nurul Aulya Bundu, Patta Devilla, Rego Fahmuddin S, Muhammad Fahmuddin, Muh. H.S, Rahmat Hastuty Musa Heriyah, Heriyah Hisyam Ihsan Irwan Irwan Irwan Istiqfar, Istiqfar Ivan, Zhalsa Larasati Jajang Jajang Kaito, Nurlaila Khairana, Nadiyah Mahadtir, Muhamad Maksar, Adie Mar’ah, Zakiyah Muh. Idris Muhammad Arif Tiro, Muhammad Arif Muhammad Refaldy Muhammad Yahya nurismi, Nur ismi Nurrahmah Nurrahmah, Nurrahmah Nusrang, Muhammad Pandjajangi, Andi Muhammad Ridho Yusuf Sainon Andi Putri, Siti Choiratun Aisyah Rahmat Hidayat Rahmat, Rahmat Wahyudi Rais, Zulkifli Refaldy, Muhammad Rudi Ruliana Ruliana Ruliana, Ruliana Sainon Andi Pandjajangi, Andi Muhammad Ridho Yusuf Saleh Ahmar, Ansari Sapinah Shanty, Meyrna Vidya Sriwahyuni, Andi Ayu Syafruddin Side Tri Utomo, Agung Vivianti Wahidah Sanusi Yassar, La Ode Salman Zulkifli Rais