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All Journal Media Statistika SAINSMAT Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) Jurnal Matematika Sains dan Teknologi Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) MATAPPA: Jurnal Pengabdian Kepada Masyarakat Jurnal Varian Inferensi ESTIMASI: Journal of Statistics and Its Application Jurnal Statistika dan Matematika (Statmat) Variansi : Journal of Statistics and Its Application on Teaching and Research Amaliah: Jurnal Pengabdian Masyarakat SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam VARIANSI: Journal of Statistics and Its Application on Teaching and Research Indonesian Journal of Fundamental Sciences Seminar Nasional Hasil Penelitian LP2M UNM SMART: Jurnal Pengabdian Kepada Masyarakat Journal of Mathematics, Computation and Statistics (JMATHCOS) Indonesian Journal of Statistics and Its Applications
Aswi, Aswi
Prodi Statistika, FMIPA, Universitas Negeri Makassar
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ESTIMATING AND FORECASTING COVID-19 CASES IN SULAWESI ISLAND USING GENERALIZED SPACE-TIME AUTOREGRESSIVE INTEGRATED MOVING AVERAGE MODEL Sukarna Sukarna; Nurul Fadilah Syahrul; Wahidah Sanusi; Aswi Aswi; Muhammad Abdy; Irwan Irwan
MEDIA STATISTIKA Vol 15, No 2 (2022): 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.15.2.186-197

Abstract

A range of spatio-temporal models has been used to model Covid-19 cases. However, there is only a small amount of literature on the analysis of estimating and forecasting Covid-19 cases using the Generalized Space-Time Autoregressive Integrated Moving Average (GSTARIMA) model. This model is a development of the GSTARMA model which has non-stationary data. This paper aims to estimate and forecast the daily number of Covid-19 cases in Sulawesi Island using GSTARIMA models. We compared two models namely GSTARI and GSTIMA considering the root mean square error (RMSE). Data on a daily number of Covid-19 cases (from April 10, 2020, to May 07, 2021) were used. The location weight used is the inverse distance weight based on the distance between airports in the capital cities of each province. The appropriate models obtained based on the data are the GSTARIMA (1;0;1;1) model and the GSTARIMA (1;1;1;0) model. The results showed that the forecast for the number of new Covid-19 cases is accurate and reliable only for the short term.
Perbandingan Model Bayesian Spasial Conditional Autoregressive (CAR): Kasus Covid-19 di Kota Makassar, Indonesia Muhammad Arif Tiro; Aswi Aswi; Zulkifli Rais
Seminar Nasional LP2M UNM SEMINAR NASIONAL 2021 : PROSIDING EDISI 5
Publisher : Seminar Nasional LP2M UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (848.202 KB)

Abstract

Abstrak. Jumlah pasien positif penyakit Coronavirus-2019 (Covid-19) meningkat secara tajam mengikuti sebaran eksponensial. Salah satu Provinsi di Indonesia di luar Pulau Jawa yang memiliki jumlah kasus Covid-19 tertinggi adalah Provinsi Sulawesi Selatan. Diantara 24 Kabupaten/Kota di Provinsi Sulawesi Selatan, Kota Makassar sebagai ibukota provinsi Sulawesi Selatan memiliki kasus terkonfirmasi positif Covid-19 tertinggi. Penelitian ini bertujuan untuk membandingkan model Bayesian spasial Conditional Autoregressive (CAR) dalam mengestimasi risiko relative (RR) kasus Covid-19 di Makassar. Beberapa model model Bayesian spasial CAR yang digunakan adalah CAR BYM, CAR Leroux, CAR localised dan model Independent. Data yang digunakan pada penelitiaan ini adalah data jumlah kasus terkonfirmasi positif Covid-19 (20 Maret 2020 - 30 Agustus 2021) dan data jumlah penduduk pada 15 kecamatan di Kota Makassar. Pemilihan model terbaik didasarkan pada beberapa ukuran kecocokan model yaitu Deviance Information Criteria (DIC), Watanabe Akaike Information Criteria (WAIC). Berdasarkan nilai DIC dan WAIC yang terkecil, dapat disimpulkan bahwa Bayesian spasial CAR localised merupakan model yang terbaik dalam memodelkan kasus terkonfirmasi Covid-19 di kota Makassar. Berdasarkan Bayesian spasial CAR localised tersebut, diperoleh bahwa Ujung Pandang memiliki RR Covid-19 tertinggi (RR=1,70) sedangkan Kabupaten Sangkarrang memiliki RR Covid-19 terendah (RR=0,09). Hasil ini dapat membantu para pembuat kebijakan dalam pengambilan keputusan.Kata Kunci: Bayesian, Conditional Autoregressive priors, Leroux, BYM, Localised
EVALUASI MODEL-MODEL BAYESIAN SPASIAL CONDITIONAL AUTOREGRESSIVE UNTUK PEMODELAN KASUS KEMATIAN CORONA VIRUS DISEASE (COVID-19) DI INDONESIA Andi Feriansyah; Aswi Aswi; Ruliana
Jurnal Matematika Sains dan Teknologi Vol. 24 No. 1 (2023)
Publisher : LPPM Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33830/jmst.v24i1.4864.2023

Abstract

Covid-19 cases in Indonesia occurred for the first time on 2 March 2020. By 30 September 2022, Indonesia had 158,173 Covid-19 deaths. Several studies have been done in modelling Covid-19 cases. However, research in modelling the number of Covid-19 deaths using the Bayesian Spatial Conditional Autoregressive (CAR) model is still rare. The Bayesian spatial CAR model has high flexibility in relative risk (RR) modeling. CAR models can include various types of spatial effects and can include covariates in the model. RR represents the ratio of the risk of outcome (Covid-19) in the exposed group compared to the population average (the unexposed group). This study aims to evaluate the BYM, Leroux, and Localised models with five hyperpriors, to obtain the best model for estimating the RR of Covid-19 deaths in Indonesia and to create RR maps. This study used aggregate data on Covid-19 deaths (2 March 2020 - 30 September 2022). Data on the total population and population density of each province in 2021 were also used. The best model selection is based on the lowest Watanabe Akaike Information Criterion (WAIC) and Deviance Information Criterion (DIC) values, and Modified Moran's I (MMI) residual values. The result showed that the CAR BYM model with covariates and with Inverse-Gamma IG(0.5; 0.0005) prior distribution had the lowest DIC and WAIC. As the BYM model does not converge, the model cannot be used in determining the RR of Covid-19 deaths in Indonesia. From the other three models that converge, the Bayesian CAR Leroux model without covariate with IG(0,5;0,0005) has the lowest DIC(393,76), and WAIC(400,12), and its MMI value (-0,26) is approximate to zero. Therefore, the Bayesian CAR Leroux model without covariate with IG(0,5;0,0005) is preferred. The province with the highest RR (2,76) and the lowest RR (0,22) are Yogyakarta and Papua, respectively.
The NADI Mathematical Model on the Danger Level of the Bili-Bili Dam Sukarna Sukarna; Andi Muhammad Ridho Yusuf Sainon Andin P; Syafruddin Side; Aswi Aswi; Supriadi Yusuf
Jurnal Varian Vol 6 No 2 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v6i2.2237

Abstract

The research discusses the NADI mathematical model due to the overflow of the Bili-Bili dam, using secondary data obtained through online literature review by collecting various information related to the Bili-Bili Dam, starting from the Jeberang River Scheme, the chronology of floods, normal or dry conditions, and dam operation patterns. The aim of this study is to predict the level of danger of Bili-bili dam overflow over time, considering extreme weather factors and standard operating procedures performed by humans. The research uses analytical and computational methods. The study obtained the NADI mathematical model due to the overflow of the Bili-Bili dam, with two equilibrium points: (1) the equilibrium point free of disaster, (2) the disaster equilibrium point, and a basic disaster reproduction number of R0 = 1.219. This indicates that the water discharge from the dam is high and has an impact on the overflowing water for communities around the Jeneberang river. Therefore, it can be concluded that the NADI model can be used to simulate the Bili-bili dam process based on extreme weather and dam SOP, and predict the level of danger of Bili-bili dam overflow, which is also a novelty that has not been done in previous studies.
Pemetaan Risiko Relatif Kasus Demam Berdarah Dengue di Kota Makassar Menggunakan Model Bayesian Spasial Andi Feriansyah; Idul Fitri Abdullah; Siti Choirotun Aisyah Putri; Mardatunnisa Isnaini; Aswi Aswi
Inferensi Vol 6, No 2 (2023)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v6i2.15931

Abstract

Dengue Hemorrhagic Fever (DHF) is a disease that is still a main problem in public health in Indonesia. This study aims to map the relative risk (RR) of dengue cases in Makassar City using the Spatial Conditional Autoregressive (CAR) model with Bayesian approaches: Besag-York-Molliѐ (BYM) and Leroux models. The data used in this study is DHF case data from 2016 to 2018 for 15 sub-districts in Makassar City. The best model was based on the model fit criteria, namely Watanabe Akaike Information Criteria (WAIC) and Deviance Information Criteria (DIC). The results indicate that the best model used to map the RR for DHF cases in 2016 and 2017 is the BYM CAR model, while the best model for 2018 is the Leroux CAR model. Based on the results of the analysis, it was concluded that in 2016 the area with the highest RR was Manggala District and the lowest RR was Tamalate District. In 2017, the area with the highest RR was Ujung Pandang District and the lowest RR was Biringkanaya District. Meanwhile, in 2018, the area with the highest dan the lowest RR was Ujung Tanah and Tamalate Districts, respectively. The results of this study are expected to be able to assist the government in implementing the program to control dengue fever in Makassar City effectively and efficiently.Keywords⎯ Dengue Hemorrhagic Fever, Relative Risk Mapping, CAR BYM, CAR Leroux.
Forecasting Consumer Price Index Expenditure Inflation for Food Ingredients Using Singular Spectrum Analysis Nur Aziza S; Aswi Aswi; Muhammad Fahmuddin S; Asrirawan
Jurnal Matematika Sains dan Teknologi Vol. 24 No. 2 (2023)
Publisher : LPPM Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33830/jmst.v24i2.4868.2023

Abstract

Inflation is an economic problem that significantly impacts the macro economy and people's real income if it occurs continuously. South Sulawesi Province often experienced significant inflation fluctuations during 2005-2019. In 2015, inflation in South Sulawesi reached 3.32%, ranking the highest in Eastern Indonesia. Ten food ingredients played an essential role in influencing inflation that year. However, until now, research on forecasting Consumer Price Index expenditure inflation for food ingredients in South Sulawesi using the Singular Spectrum Analysis method has never been carried out. The novelty in this research lies in using the Singular Spectrum Analysis method, which provides a new contribution to forecasting inflation trends in South Sulawesi and deepens understanding of regional inflation problems. This research aims to forecast consumer price index expenditure inflation for food ingredients in South Sulawesi using the Singular Spectrum Analysis method. This research used CPI expenditure inflation data for food ingredients from the official website of the Central Statistics Agency of South Sulawesi for the monthly period from January 2014 - June 2022. The forecasting results show that the lowest inflation rate is predicted to occur in December 2022 at -0,12%, while the highest level is expected to be reached in May 2023 at 0.43%. Furthermore, the mean absolute percentage error value of 3.54% indicates that the forecasting model has a very good level of accuracy. The results of this forecasting have the potential to be used by economic policymakers in South Sulawesi in designing more effective policies to overcome the problem of inflation, especially in the food ingredients and its impact on society. The practical implications of this research can help improve regional economic stability and community welfare.
Peningkatan Pengetahuan Penyusunan Artikel Ilmiah Bagi Guru SMAN 4 Kabupaten Pinrang Melalui Pelatihan Penyusunan Karya Tulis Ilmiah A. Aswi; Zulkifli Rais; Muhammad Fahmuddin
SMART: Jurnal Pengabdian Kepada Masyarakat Vol 1, No 1 (2021): 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.v1i1.26120

Abstract

Mitra Program Kemitraan Masyarakat (PKM) ini adalah guru di SMAN 4 Kabupaten Pinrang, yang memiliki masalah kurangnya artikel ilmiah yang diterbitkan oleh guru. Salah satu penyebab guru tidak menerbitkan artikel ilmiah yaitu sebagian besar guru belum memahami tata cara penulisan artikel yang baik. Metode yang digunakan adalah: memberikan workshop pemahaman penulisan artikel ilmiah. Hasil yang dicapai adalah guru memahami teknik-teknik penulisan karya tulis ilmiah pada bidang pendidikan dan mendapat gambaran mengenai teknik pengolahan data dengan menggunakan metode statisika yang baik dan benar.
Pelatihan Mendeley dalam Upaya Merangsang Motivasi Menulis Mahasiswa Angkatan 2020 Prodi Matematika FMIPA Universitas Negeri Makassar Sukarna Sukarna; Aswi Aswi; Nurhilaliyah Nurhilaliyah
SMART: Jurnal Pengabdian Kepada Masyarakat Vol 2, No 2 (2022): 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.v2i2.38487

Abstract

Pelatihan ini berawal dari diskusi singkat dengan mahasiswa angkatan 2020 Program Studi Matematika FMIPA UNM secara lepas mengenai kiat mereka menulis, baik menulis untuk keperluan lomba-lomba ataupun proposal skripsi. Diskusi ini berlanjut santai dan mengerucut dengan menawarkan mereka untuk berkolaborasi melaksanakan pelatihan Mendeley. Pelatihan ini bertujuan untuk mengatasi permasalahan atau keluhan mahasiswa mengenai teknik mempermudah menulis sitasi dan daftar pustaka (bibliography) dengan kriteria atau template yang beragam, seperti style Harvard, APA, IEEE, Vancouver, dan IOP SciNotes. Hal lain yang akan dituntaskan adalah memanfaatkan aplikasi Mendeley untuk menyimpan atau mengarsipkan berkas jurnal, buku, ataupun referensi lain untuk mempermudah mencari kembali dan menyusun bibliography-nya. Sehingga, secara detail dapat dituliskan tujuan pelatihan ini adalah untuk (1) meningkatkan pengetahuan mahasiswa Prodi Matematika Angkatan 2020 dalam menggunakan Mendeley; (2) meningkatkan kesadaran peserta tentang pentingnya Mendeley dalam penulisan sitasi dan bibliography; (3) meningkatkan wawasan, kemampuan, dan keterampilan peserta dalam mengoperasikan Mendelay sebagai aplikasi yang lebih informatif dan inovatif; dan (4) mengurangi jumlah mahasiswa Prodi Matematika yang menuliskan sitasi dan bibliography secara manual. Metode yang digunakan adalah direct interactive cooperative training. Peserta yang mengikuti pelatihan ini adalah 24 orang. Hasil survey google-form menunjukkan bahwa pelatihan ini sangat baru dan dibutuhkan bagi peserta. Mereka merasa terbantukan untuk mengenal dan mencoba menggunakan Mendeley untuk selanjutnya sebagai aplikasi yang membantu menulis sitasi dan bibliography.
Pelatihan Merancang Sitasi dan Membuat Bibliography melalui Mendeley Desktop sebagai Upaya Mempercepat Penyelesaian Studi Mahasiswa Magister Pendidikan Kimia PPs UNM Sukarna Sukarna; Aswi Aswi; Halimah Husain; Awi Awi; Nurhilaliyah Nurhilaliyah
SMART: Jurnal Pengabdian Kepada Masyarakat Vol 4, No 1 (2024): April
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/smart.v4i1.61303

Abstract

Program Pascasarjana (PPs) adalah program setara fakultas di Universitas Negeri Makassar (UNM) yang melingkupi 11 program doktor dan 24 program magister. Program Pascasarjana Studi Pendidikan Kimia berada di bawah pengelolaan PPs UNM. Hasil survei awal dari ketua program studi menunjukkan bahwa peserta pelatihan pada umumnya belum mengenal software referensi, seperti Mendeley, Zotero, ataupun Endnote. Oleh karena itu, penting untuk meningkatkan pemahaman dan keterampilan mahasiswa program Magister Pendidikan Kimia PPs UNM dalam menyusun sitasi dan bibliografi menggunakan aplikasi Mendeley. Tujuan utama dari workshop ini adalah meningkatkan pemahaman dan keterampilan mahasiswa Magister Pendidikan Kimia PPs UNM dalam menyusun sitasi dan bibliografi dengan menggunakan Mendeley, yang sangat penting dalam penulisan tesis untuk mendapatkan gelar Magister Pendidikan Kimia. Metode pelatihan yang digunakan adalah hybrid classical teaching and training, menggabungkan dua tahap pelatihan (teaching dan training) secara hybrid menggunakan ruang kelas dan Zoom. Workshop Mendeley ini dilaksanakan pada tanggal 10 Januari 2024, diikuti oleh 30 peserta dan narasumber. Survei pasca-pelatihan menunjukkan hasil yang sangat positif; peserta memperoleh pemahaman yang memadai dan merasa puas dengan pelaksanaan workshop. Rekomendasi peserta menunjukkan kebutuhan untuk workshop serupa guna mencapai kemahiran dalam membuat karya ilmiah.
Application of teh Hybrid Singular Spectrum Analysis – ARIMA Model for Indonesia's Inflation Rate (2018-2023) Sri Rahayu; Aswi Aswi; Muhammad Fahmuddin Sudding
Jurnal Matematika Sains dan Teknologi Vol. 25 No. 2 (2024): September (in Progress)
Publisher : LPPM Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33830/jmst.v25i2.7982.2024

Abstract

This research aims to determine the results and accuracy of forecasting inflation rates in Indonesia using Hybrid Singular Spectrum Analysis (SSA) – Autoregressive Integrated Moving Average (ARIMA). Hybrid SSA-ARIMA combines two time series methods to increase forecasting accuracy, especially for economic data that contains trend and seasonal components. The data used is data on the national consumer price inflation rate (Y-on-Y) for the period January 2018 to December 2023. The forecast accuracy obtained by the MAPE value for Singular Spectrum Analysis was 56.26797%, and Hybrid SSA-ARIMA was 18.88851%. This shows that Hybrid SSA-ARIMA has better forecasting capabilities than Singular Spectrum Analysis in predicting the inflation rate in Indonesia.
Co-Authors A. Nurul Amalia AA Sudharmawan, AA Abdul Rahman Aidid, Muhammad Kasim Andi Feriansyah Andi Feriansyah Andi Gagah Palarungi Taufik Andi Muhammad Ridho Yusuf Sainon Andin P Andi Shahifah Muthahharah Ankaz As Sikib Annas, Suwardi Asrirawan Awaluddin Awaluddin Awi Awi Bobby Poerwanto Bobby Poerwanto Bobby Poerwanto Bustan, Muhammad Nadjib Fahmuddin, Muhammad Halimah Husain Hammado, Nurussyariah Hisyam Ihsan Idul Fitri Abdullah Irwan Irwan Isnaini, Mardatunnisa Kaito, Nurlaila M Nadjib Bustan Mahadtir, Muhamad Mardatunnisa Isnaini Mauliyana, Andi Muhammad Abdy Muhammad Abdy Muhammad Abdy Muhammad Abdy Muhammad Ammar Naufal Muhammad Arif Tiro Muhammad Arif Tiro Muhammad Arif Tiro Muhammad Arif Tiro Muhammad Arif Tiro Muhammad Arif Tiro, Muhammad Arif Muhammad Fahmuddin Muhammad Fahmuddin Muhammad Fahmuddin Sudding Muhammad Kasim Aidid Mutmainnah Mutmainnah Natalia, Derliani Nini Harnikayani Hasa Nur Aziza S Nurhilaliyah Nurhilaliyah Nurhilaliyah Nurhilaliyah Nurhilaliyah Nurhilaliyah, Nurhilaliyah Nurkaila Kaito Nurul Fadilah Syahrul Nurul Ilmi Nusrang, Muhammad Oktaviana Oktaviana Poerwanto, Bobby Putri, Siti Choirotun Aisyah Rahma, Ina Rahman, Abdul Rahmawati Rahmawati Ramadani, Reski Aulia Rezki Amalia Idrus Ruliana Ruliana Ruliana Ruliana Ruliana Ruliana, Ruliana Sahlan Sidjara Salsabila, Afifah Sapriani Shanty, Meyrna Vidya Siti Choirotun Aisyah Putri Sri Ayu Astuti Sri Rahayu Suardi, Shafira Suci Amaliah Sudarmin Sudarmin Sudarmin Sudarmin Sudarmin Sudarmin Sukarna Sukarna Sukarna Sukarna Sukarna Sukarna Sukarna Sukarna Sukarna Supriadi Yusuf Susanna Cramb Suwardi Annas Suwardi Annas Syafruddin Side Wahidah Sanusi Wea, Maria Dominggo Yassar, La Ode Salman Zulhijrah Zulhijrah Zulhijrah Zulkifli Rais