Article Per Year (5 Year)
p-Index From 2020 - 2025
3.016
P-Index
This Author published in this journals
All Journal Natural Science: Journal of Science and Technology Media Statistika SAINSMAT Indonesian Journal of Educational Studies Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) Jurnal Varian Inferensi Jurnal Statistika dan Matematika (Statmat) ARRUS Journal of Mathematics and Applied Science 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
Sukarna Sukarna
Universitas Negeri Makassar
Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Social Sciences Other

Published : 16 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 16 Documents
Search

 1   2 
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)

Abstract

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (200.451 KB) | DOI: 10.26858/ijes.v14i1.3982

Abstract

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

Abstract

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 Moran’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. 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

Abstract

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

Abstract

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

Abstract

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.
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

Abstract

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.
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

Abstract

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 ARIMAX KASUS COVID-19 DIKAITKAN DENGAN CURAH HUJAN DI KOTA MAKASSAR Sukarna Sukarna; Sahlan Sidjara; Aswi Aswi; Oktaviana Oktaviana
STATMAT : JURNAL STATISTIKA DAN MATEMATIKA Vol 4, No 2 (2022)
Publisher : Math Program, Math and Science faculty, Pamulang University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/sm.v4i2.25556

Abstract

ABSTRACT This research applies a quantitative modelling approach and focuses on ARIMAX modelling in the Covid-19 case associated with rainfall in Makassar City. Data were obtained from the government's official website for daily confirmed case data of Covid-19 and rainfall (from June 25, 2020 to January 15, 2022). Rainfall is measured in mm which is the independent variable ( ), and confirmed Covid-19 as the dependent variable ( ). This research objective is to obtain the best ARIMAX model that informs the effect of rainfall intensity ( ) on the number of confirmed cases of Covid-19 ( ). This best model used the criteria that all parameters are significant, the residuals involved the white noise assumption and the best criteria measured from the smallest value of Akaike Information Criterion (AIC). The best model in this study is ARIMAX(3,0,5), with the smallest AIC value of 7,220,96. The results of this study indicate that rainfall ( ) has no significant effect on the number of confirmed Covid-19 ( ) in Makassar City. Keywords: ARIMAX, Covid-19, rainfall, Makassar. ABSTRAK Penelitian ini menerapkan pendekatan pemodelan kuantitatif (quantitative modelling approach) dan membahas pemodelan ARIMAX pada kasus Covid-19 dikaitkan dengan curan hujan di Kota Makassar. Data diperoleh dari website resmi pemerintah untuk data kasus terkonfirmasi harian Covid-19 dan juga curah hujan (mulai Tanggal 25 Juni 2020 s/d 15 Januari 2022). Curah Hujan diukur dalam mm yang merupakan variabel bebas ( , dan terkonfirmasi Covid-19 sebagai variabel terikat ( . Penelitian ini bertujuan untuk mendapatkan model ARIMAX terbaik yang menginformasikan pengaruh intensitas curah hujan (  terhadap jumlah kasus terkonfirmasi Covid-19 ( . Model terbaik ini memenuhi kriteria bahwa semua parameter signifikan, residual memenuhi asumsi white noise dan kriteria terbaiknya menggunakan nilai Akaike Information Criterion (AIC). Model terbaik yang diperoleh dalam penelitian ini adalah ARIMAX(3,0,5), dengan nilai AIC terkecil sebesar 7.220,96. Hasil penelitian ini menunjukkan bahwa Curah Hujan (  tidak berpengaruh signifikan terhadap jumlah terkonfirmasi Covid-19 (  di Kota Makassar. Kata kunci: ARIMAX, Covid-19, Curah hujan, Makassar
PEMODELAN TIME SERIES UNTUK NILAI TUKAR RUPIAH DI MASA PANDEMI COVID-19 Hisyam Ihsan; Abdul Rahman; Sukarna Sukarna; Aswi Aswi; Muhammad Ammar Naufal
STATMAT : JURNAL STATISTIKA DAN MATEMATIKA Vol 4, No 2 (2022)
Publisher : Math Program, Math and Science faculty, Pamulang University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/sm.v4i2.26100

Abstract

Abstract: Covid-19 is an international disaster with a long occurrence interval. The research divides this disaster into four phases, namely before the Covid-19 pandemic (1 January 2019 to 31 March 2020), the implementation of PSBB (1 April 2020 to 20 January 2021), the performance of PPKM & Micro-Lockdown (21 January 2021 to 23 July 2021), and after Covid-19 is reduced (24 July 2021 to 30 June 2022). Data on IDR to USD exchange rates were obtained from the official website from 1 January 2019 to 30 June 2022. Comparing the ARIMA temporal model for the four phases was proposed in this study as an inferential and descriptive way to compare exchange rates. The results showed that the IDR exchange rate against the USD closed at IDR 14,155.63 (before the pandemic), IDR 15,581.83 (PSBB period), IDR 14,362.84 (PPKM period), and IDR 14,368.16 (after the pandemic). According to the smallest AIC or parsimony considerations, the most effective ARIMA model is ARIMA(2,1,0) for the stage before the pandemic, ARIMA(0,2,1) for the stage during PSBB, ARIMA(3,1,0) for the stage during PPKM & micro-lockdown, and ARIMA(2,1,0) for the stage after the pandemic.ABSTRAK: Pandemi Covid-19 merupakan bencana internasional yang sangat panjang interval kejadiannya. Penelitian ini membagi bencana ini menjadi 4 fase, yaitu sebelum pandemi Covid-19 (1 januari 2019 s/d 31 Maret 2020), pemberlakuan PSBB (1 April 2020 s/d 20 Januari 2021), pemberlakuan PPKM & Micro-Lockdown (21 Januari 2021 s/d 23 Juli 2021), dan setelah Covid-19 berkurang (24 Juli 2021 s/d 30 Juni 2022). Data nilai tukar IDR ke USD diambil dari situs resmi mulai 1 Januari 2019 s/d 30 Juni 2022. Tujuan penelitian ini adalah membandingkan nilai tukar secara deskriptif dan inferensial dengan membandingkan model temporal ARIMA untuk keempat fase tersebut. Hasil penelitian menunjukan bahwa nilai tukar IDR terhadap USD ditutup pada Rp 14.155,63 (sebelum pandemi), Rp 15.581,83 (masa PSBB), Rp 14.362,84 (masa PPKM), dan Rp 14.368,16 (setelah pandemi). Model ARIMA terbaik berdasarkan AIC terkecil atau pertimbangan parsimony untuk tiap fase adalah ARIMA(2,1,0) sebelum pandemi, ARIMA(0,2,1) dimasa PSBB, ARIMA(3,1,0) dimasa PPKM & micro-lockdown, dan ARIMA(2,1,0) setelah masa pandemi.Kata kunci: covid-19, nilai tukar rupiah, model temporal, ARIMA.
Co-Authors Abdul Rahman Andi Muhammad Ridho Yusuf Sainon Andin P Anggi Ananda Putri Aswi, Aswi Awi, Awi Elma Selviana Darwis Gita Tri Asfarina Hafilah Hardiono Hisyam Ihsan Irham Aryandi Basir Irma S Irwan Irwan J, Jusriadi Muh Nahdi Alim Asyhari Muh. Hidayatullah Dwi Putra Muh. Irham Rosadi Muhammad Abdy Muhammad Abdy Muhammad Abdy Muhammad Abdy Muhammad Ammar Naufal Muhammad Arif Tiro N Nurwakia N. Nurmah Nasrullah Nasrullah Nur Ridiawati Nurhilaliyah Nurhilaliyah Nurhilaliyah Nurhilaliyah Nurkaila Kaito Nurul Fadilah Syahrul Oktaviana Oktaviana R. Rahmat Rahmah Abubakar Rahman, Abdul Rahmat Syam Raihana Nurfitrah Rusli Sahlan Sidjara Serly Diliyanti Restu Ningsih Sitti Hasna Sudarmin Sudarmin Supriadi Yusuf Susanna Cramb Syafruddin s Syafruddin Side Wahidah Sanusi Wahyudin Wahyuni, Maya Sari