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All Journal Natural Science: Journal of Science and Technology Media Statistika SAINSMAT Indonesian Journal of Educational Studies Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) BAREKENG: Jurnal Ilmu Matematika dan Terapan JURNAL PengaMAS EDUKATIF : JURNAL ILMU PENDIDIKAN Jurnal Varian Inferensi Jurnal Statistika dan Matematika (Statmat) LOSARI: Jurnal Pengabdian Kepada Masyarakat ARRUS Journal of Mathematics and Applied Science ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat SAINSMAT: Journal of Applied Sciences, Mathematics, and Its Education Issues in Mathematics Education (IMED) Amaliah: Jurnal Pengabdian Masyarakat SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam Indonesian Journal of Fundamental Sciences SMART: Jurnal Pengabdian Kepada Masyarakat Journal of Mathematics, Computation and Statistics (JMATHCOS)

Sukarna Sukarna

Universitas Negeri Makassar

Author-ID : 3103948

Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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APLIKASI ANALISIS RANTAI MARKOV UNTUK MEMPREDIKSI STATUS PASIEN RUMAH SAKIT UMUM DAERAH KABUPATEN BARRU S, Syafruddin; S, Irma; Sukarna, Sukarna
Natural Science: Journal of Science and Technology Vol 3, No 3 (2014): Volume 3 Number 3 (December 2014)
Publisher : Univ. Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (725.802 KB)

Penelitian ini menjelaskan aplikasi rantai Markov dan bertujuan untukmemprediksi status pasien pada RSUD Barru dengan menggunakan proses stokastik.Pengambilan data penelitian dilakukan dengan melakukan observasi di RSUD Barru bulan Januari 2014.Selanjutnya dilakukan analisis data dengan menggunakan rantai Markov untukforecasting status pasien. Data yang digunakan merupakan data sekunder. Proses perhitungan dilakukan dengan membuatprogram basis data untuk melengkapi Sistem Informasi Manajemen pasien pada rumah sakit, kemudian membuat program untuk mempermudah dalam menentukan nilai perkalian matriksmenggunakan software Visual Basic 6.0.Data status pasien terlebih dahulu diubah menjadi data probabilitas kemudian dibentuk kedalam matriks probabilitas transisi. Hasil yang diperoleh untuk status pasien setelah dilakukan analisis rantai markovadalah perkiraan pada bulan Februari 2015yaitu 67,2 % pasien yang keluar dari rumah sakit dalam keadaan sehat, 19,1 % pasien yang keluar dari rumah sakit dalam keadaan sakit biasa, dan 13,6 % pasien yang keluar dari rumah sakit dalam keadaan sakit parah. Hasil prediksi tersebut menyimpulkan bahwa pasien yang masuk ke rumah sakit dengan keadaan sakit parah menjadi sehat mempunyai peluang yang lebih besar dibandingkan periode sebelumnya.

Assessment tools PKM Model Involving Scaffolding Metacognitive Based on Revised Bloom's Taxonomy Awi, Awi; Sukarna, Sukarna
Indonesian Journal of Educational Studies Vol 14, No 1 (2013)
Publisher : Universitas Negeri Makassar

This research aims to develop software process assessment and the results of applying the model statistics PKM-BC material. The study was designed with the development of the Model Plomp. The test device of assessment will be conducted at SMAN 11 and SMAN 3 Makassar.Untuk achieve the objectives of this study used a method of development of Plomp (1997), which consists of five phases. Based on research, the resulting asesen valid, practical, and effective. The resulting assessment device includes four dimensions of knowledge, that is faktual, konseptuap, procedural, and metacognitive.

MODEL BAYESIAN SPASIAL CAR LOCALISED: STUDI KASUS DEMAM BERDARAH DENGUE DI KOTA MAKASSAR Aswi, Aswi; Sukarna, Sukarna
Prosiding Seminar Nasional Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika (VARIANSI) Vol 2 (2020)
Publisher : Program Studi Statistika, FMIPA, Universitas Negeri Makassar

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

Berbagai model Bayesian telah digunakan untuk menggambarkan pola spasial untuk data area. Dalam tulisan ini, kami mengaplikasikan model Bayesian spasial Conditional Autoregressive (CAR) localised yang memungkinkan untuk pembentukan pengelompokkan risiko relatif suatu kasus penyakit dalam hal ini kasus Demam Berdarah Dengue (DBD). Data yang digunakan adalah data kasus DBD tahun 2013-2015 untuk 14 wilayah kecamatan di Kota Makassar. Formula model Bayesian spasial CAR localised yang berbeda beda dibandingkan dengan menggunakan beberapa kriteria kecocokan model yaitu Deviance Information Criteria, Watanabe Akaike Information Criteria, residu dari Modified Moranâ€™s I dan banyaknya wilayah yang termasuk dalam suatu kelompok. Penggunaan model Bayesian spasial CAR localised direkomendasikan jika rata rata dan variansi peubah terikat antar wilayah relatif besar karena dapat mengidentifikasi kelompok area yang berisiko tinggi, sedang dan rendah. Jika nilai rata rata dan variansi antar wilayah relatif besar, pembentukan kelompok dan anggotanya dipengaruhi juga oleh pemilihan hyperprior pada deviasi standar. Kecamatan Rappocini, Manggala dan Tamalanrea merupakan kecamatan yang memiliki risiko relatif yang tinggi untuk terjangkit DBD. Hasil ini dapat dijadikan rujukan pagi para pengambil kebijakan khususnya di bidang kesehatan.Â Kata Kunci: Conditional Autoregressive, Demam berdarah Dengue, Pengelompokan, Risiko Relatif

Improved Exponential Approach Method in Determining Optimum Solutions for Transportation Problems Rusli; Sukarna; Wahyudin
ARRUS Journal of Mathematics and Applied Science Vol. 2 No. 2 (2022)
Publisher : Lembaga Penelitian dan Pengembangan Teknologi dan Rekayasa, Yayasan Ahmar Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/mathscience744

This study describes the transportation methods that regulate and distribute resources that provide products where they are needed to achieve efficient transportation costs. Solve a transportation problem in this thesis using the Improved Exponential Approach method, then using the NWC (Northwest) method to test its optimization. The purpose of this research is to get more optimal results as initial consideration to increase the distribution cost savings in the Bread Company. Costs incurred by the company before the study amounted to Rp.3,218,000. The results of this study found that the application of the transportation method using the Improved Exponential Approach method is effectively used compared to the NWC method which has a comparison of transportation costs of Rp. 2,612,500 and Rp. 2,785,000, Optimization test results obtained from the Improved Exponential Approach method amounted to Rp2,612,500. And the Improved Exponential Approach method used by researchers can be applied to the Gardenia company.

Factors Affecting the Covid-19 Risk in South Sulawesi Province, Indonesia: A Bayesian Spatial Model Aswi Aswi; Sukarna Sukarna
Inferensi Vol 5, No 1 (2022): Inferensi
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v5i1.12527

The transmission of Coronavirus diseases 2019 (Covid-19) grows continuously around the world. Although a number of researches of modelling Covid-19 cases have been conducted, there was limited research implementing the Bayesian Spatial Conditional Autoregressive (CAR) model. Factors affecting the Covid-19 risk especially population density and distance to the capital city have been studied, but the results are inconsistent and limited research has been done in Indonesia. This study aims to assess the most appropriate Bayesian spatial CAR Leroux models and examine factors that affect the risk of Covid-19 in South Sulawesi Province. Data on the number of Covid-19 cases (19 March 2020 - 31 January 2022), population density, and distance to the capital city were used for every 24 districts. Several criteria were used in choosing the most appropriate model. The results depict that Bayesian spatial CAR Leroux with hyperprior IG (1, 0.01) model with the inclusion of population density were preferred. It is concluded that a factor that significantly affects the number of Covid-19 cases is population density. There was a positive correlation between the population density and Covid-19 risk. Makassar city has the highest relative risk (RR) among other districts while Bone has the lowest RR of Covid-19.

Pemetaan Risiko Relatif Kasus Stunting di Provinsi Sulawesi Selatan Aswi Aswi; Sukarna Sukarna; Nurhilaliyah Nurhilaliyah
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 11, No 1 (2022): Maret
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat111325202022

Indonesia merupakan negara dengan prevalensi balita stunting tertinggi ketiga di regional Asia Tenggara. Provinsi Sulawesi Selatan sebagai salah satu provinsi di Indonesia memiliki kasus stunting yang cukup tinggi. Pengimplementasian model Bayesian spasial Conditional Autoregressive (CAR) dalam menaksir risiko relatif (RR) kasus stunting belum dilakukan di Indonesia, khususnya di Provinsi Sulawesi Selatan. Penelitian ini bertujuan untuk mengetahui RR kasus stunting dengan menggunakan model Bayesian spasial CAR Leroux serta membangun peta tematik RR kasus stunting di seluruh kabupaten/kota di Provinsi Sulawesi Selatan. Model Bayesian spasial CAR Leroux dengan hyperprior IG(0,5; 0,0005) merupakan model terbaik dalam pemodelan RR kasus balita stunting di Provinsi Sulawesi Selatan. Kabupaten Toraja, Kota Parepare, dan Kabupaten Enrekang merupakan tiga kabupaten/kota dengan RR stunting tertinggi. Sebaliknya, Kabupaten Gowa, Kota Makassar dan Kabupaten Pinrang merupakan tiga wilayah dengan RR stunting terendah.

Pemodelan Jalur pada Faktor yang Mempengaruhi Kriminalitas di Sulawesi Selatan Tahun 2021 Sukarna; Ahmad Zaki; Muh. Ilham
Jurnal MSA ( Matematika dan Statistika serta Aplikasinya) Vol 10 No 1 (2022): VOLUME 10 NOMOR 1 TAHUN 2022
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v10i1.28243

South Sulawesi has many diverse track records in criminal acts, including theft. The causal factors of crime should be detected and found scientifically to assist professionally and academically all parties in reducing or avoiding the consequences or increasing crime. The study purpose is to create the model crime (especially theft) in South Sulawesi based on the factors that influence it. The model is path analysis which is able to determine direct and indirect effects. Data obtained from BPS South Sulawesi in the form of population, education, poverty, unemployment, crime. Two models are presented to provide recommended solutions that the population, education, poverty and unemployment affect the crime rate. The dominant variable that directly affects crime is the population of 2,149 and the smallest influence is education of 0.158 Keywords: Path analysis, population, unemployment, crime

PEMODELAN BAYESIAN SPASIAL CONDITIONAL AUTOREGRESSIVE (CAR) PADA KASUS DEMAM BERDARAH DENGUE DI INDONESIA Aswi; Sukarna
Jurnal MSA ( Matematika dan Statistika serta Aplikasinya) Vol 10 No 1 (2022): VOLUME 10 NOMOR 1 TAHUN 2022
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v10i1.29113

Demam Berdarah Dengue (DBD) merupakan salah satu penyakit menular yang masih merupakan masalah utama dalam kesehatan masyarakat di Indonesia. Total kasus DBD di Indonesia pada tahun 2020 masih cukup tinggi yaitu 108.303 kasus. Beberapa penelitian terkait pemodelan DBD telah menggunakan metode Bayesian spasial. Akan tetapi, penelitian tersebut masih fokus pada salah satu provinsi yang ada di Indonesia. Penelitian ini bertujuan untuk memodelkan risiko relatif (RR) kasus DBD tahun 2020 di Indonesia dengan 34 provinsi dan menghasilkan peta tematik RR. Data yang digunakan data kasus DBD serta data jumlah penduduk di Indonesia tahun 2020 yang diperoleh dari Publikasi Kementerian Kesehatan Republik Indonesia 2021. Model Bayesian spasial Conditional Autoregressive (CAR) Leroux digunakan dengan pemilihan model terbaik didasarkan pada Deviance Information Criteria (DIC), Watanabe Akaike Information Criteria (WAIC), dan Modifikasi Moran’s I (MMI) untuk residual. Hasil yang diperoleh menunjukkan bahwa model Bayesian spasial CAR Leroux dengan hyperprior IG(1; 0,1) merupakan model terbaik dalam pemodelan kasus DBD tahun 2020 di Indonesia. Sekitar 53% provinsi yang ada di Indonesia merupakan wilayah dengan RR tinggi, dimana Provinsi Bali memiliki nilai RR tertinggi (6,84), diikuti oleh Provinsi Nusa Tenggara Timur (RR=2,70), dan Daerah Istimewa Yogyakarta (RR=2,33). Sebaliknya, provinsi dengan RR terendah adalah Provinsi Maluku (RR=0,11), diikuti oleh Provinsi Papua (RR = 0,13), dan Provinsi Kalimantan Barat (RR =0,38).

THE INTERPLAY BETWEEN CLUSTERS, COVARIATES, AND SPATIAL PRIORS IN SPATIAL MODELLING OF COVID-19 IN SOUTH SULAWESI PROVINCE, INDONESIA Aswi Aswi; Muhammad Arif Tiro; Sudarmin Sudarmin; Sukarna Sukarna; Susanna Cramb
MEDIA STATISTIKA Vol 15, No 1 (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.15.1.48-59

A number of previous studies on Covid-19 have used Bayesian spatial Conditional Autoregressive (CAR) models. However, basic CAR models are at risk of over-smoothing if adjacent areas genuinely differ in risk. More complex forms, such as localised CAR models, allow for sudden disparities, but have rarely been applied to modelling Covid-19, and never with covariates. This study aims to evaluate the most suitable Bayesian spatial CAR localised models in modelling the number of Covid-19 cases with and without covariates, examine the impact of covariates and spatial priors on the identified clusters and which factors affect the Covid-19 risk in South Sulawesi Province. Data on the number of confirmed cases of Covid-19 (19 March 2020 -25 February 2022) were analyzed using the Bayesian spatial CAR localised model with a different number of clusters and priors. The results show that the Bayesian spatial CAR localised model with population density included fits the data better than a corresponding model without covariates. There was a positive correlation between the Covid-19 risk and population density. The interplay between covariates, spatial priors, and clustering structure influenced the performance of models. Makassar city and Bone have the highest and the lowest relative risk (RR) of Covid-19 respectively.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat111325202022

Co-Authors Abdul Rahman Ahmad Zaki Aleytha Ilahnugrah Kurnadipare Alimuddin Tampa Andi Muhammad Ridho Yusuf Sainon Andin P Anggi Ananda Putri Aswi, Aswi Awi Awi Awi Awi Awi, Awi Bagus Sartono Bobby Poewanto Elma Selviana Darwis Farah Putri Firdausa Gita Tri Asfarina Hafilah Hardiono Harpiani Harpiani Hisyam Ihsan Irham Aryandi Basir Irma S Irwan Irwan J. Jusriadi Maya Sari Wahyuni Muh Nahdi Alim Asyhari Muh Tawil Muh. Hidayatullah Dwi Putra Muh. Ilham Muh. Irham Rosadi Muh. Irham Rosadi Muhammad Abdy Muhammad Abdy Muhammad Abdy Muhammad Abdy Muhammad Ammar Naufal Muhammad Arif Tiro Muhammad Arif Tiro Muhammad Fahmuddin N Nurwakia N. Nurhilaliyah N. Nurmah Nasrullah Nasrullah Nur Harisahani Nur Ridiawati Nur Wahidin Ashari Nurhilaliyah Nurhilaliyah Nurhilaliyah Nurhilaliyah Nurhilaliyah Nurkaila Kaito Nurmah Nurmah Nurul Fadilah Syahrul Nurwan Nurwan Oktaviana Oktaviana R. Rahmat R. Rusli Rahmah Abubakar Rahman, Abdul Rahmat Syam Rahmat Syam Raihana Nurfitrah Rusli Sahlan Sidjara Serly Diliyanti Restu Ningsih Sitti Hasna Sudarmin Sudarmin Sudarmin Sudarmin Supriadi Yusuf Susanna Cramb Susanna Cramb Sutamrin Sutamrin Syafruddin s Syafruddin Side Syamsuddin Mas'ud Wahidah Sanusi Wahidah Sanusi Wahyudin Wahyudin Wahyudin

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