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All Journal Media Statistika Jurnal Ilmiah Pena: Sains dan Ilmu Pendidikan MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jambura Journal of Mathematics Jurnal Varian Variansi : Journal of Statistics and Its Application on Teaching and Research Seminar Nasional Pengabdian Kepada Masyarakat VARIANSI: Journal of Statistics and Its Application on Teaching and Research Indonesian Journal of Fundamental Sciences Pinisi: Journal of Teacher Proffesional Indonesian Journal of Statistics and Its Applications

Annas, Suwardi

Fakultas Matematika Dan Ilmu Pengetahuan Alam, Universitas Negeri Makassar

Author-ID : 3496066

Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Immunology & microbiology Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Other

Published : 21 Documents Claim Missing Document

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Using k-Means and Self Organizing Maps in Clustering Air Pollution Distribution in Makassar City, Indonesia Suwardi Annas; Uca Uca; Irwan Irwan; Rahmat Hesha Safei; Zulkifli Rais
Jambura Journal of Mathematics Vol 4, No 1: January 2022
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Air pollution is an important environmental problem for specific areas, including Makassar City, Indonesia. The increase should be monitored and evaluated, especially in urban areas that are dense with vehicles and factories. This is a challenge for local governments in urban planning and policy-making to fulfill the information about the impact of air pollution. The clustering of starting points for the distribution areas can ease the government to determine policies and prevent the impact. The k-Means initial clustering method was used while the Self-Organizing Maps (SOM) visualized the clustering results. Furthermore, the Geographic Information System (GIS) visualized the results of regional clustering on a map of Makassar City. The air quality parameters used are Suspended Particles (TSP), Sulfur Dioxide (SO2), Nitrogen Dioxide (NO2), Carbon Monoxide (CO), Surface Ozone (O3), and Lead (Pb) which are measured during the day and at night. The results showed that the air contains more CO, and at night, the levels are reduced in some areas. Therefore, the density of traffic, industry and construction work contributes significantly to the spread of CO. Air conditions vary, such as high CO levels during the day and TSP at night. Also, there is a phenomenon at night that a group does not have SO2 and O3 simultaneously. The results also show that the integration of k-Means and SOM for regional clustering can be appropriately mapped through GIS visualization.

Using SAPR Model for Solution of Social Poverty Problem Due to Covid-19 in Makassar City Suwardi Annas; Syafruddin Side; Andi Muhammad Ridho Yusuf Sainon Andi Pandjajangi; Nurul Fadhilah Syahrul; Luthfiah Arradiah
Jurnal Varian Vol 5 No 1 (2021)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v5i1.1399

This study aims to build an SAPR model on the problem of poverty, analyze the model, predict the number of poverty rates in the city of Makassar, and determine the parameters that affect the decrease in the number of poverty rates due to Covid-19 in the city of Makassar. This research is quantitative. The population of this study is the number of people in Makassar City who are affected by the spread of COVID-19, while the sample of this study is 400 people. The research stages are: Building the SAPR model on the level of social poverty, determining and analyzing the stability of the equilibrium point, determining the value of the basic reproduction number (R0), conducting model simulations using Maple. The results shown that the mathematical model of SAPR which is a non-linear system of differential equations can be a reference model for the problem of poverty; The results also shown that the analysis of the social poverty level of the population finds two equilibrium points, namely the free equilibrium point for the poor and the poor; the stability of the equilibrium point is free-poor and poor; The basic reproduction number R0 = 0.426 indicates that the poverty level of the social population can be controlled even though it has increased. Based on the model simulation, it was found that the parameter in the form of business funding assistance from the government could reduce the poverty rate due to the Covid-19 pandemic in Makassar city.

K-Prototypes Algorithm for Clustering The Tectonic Earthquake in Sulawesi Island Suwardi Annas; Irwan Irwan; Rahmat H Safei; Zulkifli Rais
Jurnal Varian Vol 5 No 2 (2022)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v5i2.1908

Natural disasters that had occurred in Indonesia consist of hydro-meteorology: floods, droughts, and landslides, geophysical: volcanic earthquakes and volcanic eruptions, and biological: epidemics. Regarding the tectonic earthquake on Sulawesi Island, there are at least 2 earthquake disasters that became national disasters, namely in Central Sulawesi and West Sulawesi in the range of 2017 to 2021. This study aims to cluster tectonic earthquakes on Sulawesi Island, from 2017 to 2020, as the basis for formulating disaster mitigation plans. This study used tectonic earthquake data from 2017 to 2020 obtained from BMKG Gowa, Indonesia. The variables used are magnitude, depth, and distance category. Because they are mixed variables, this study used a k-prototype algorithm. There are four clusters in 2017, six clusters in 2018, five clusters in 2019, and six clusters in 2020 based on the ratio of within-cluster distance against between-cluster distance. It can be related to the active fault on Sulawesi Island. The characteristics of clusters form each year are the greater magnitude of the earthquake, the deeper of deep and the category distance is dominated by the regional level.

ANALISIS SURVIVAL DENGAN PEMODELAN REGRESI COX PROPORTIONAL HAZARD MENGGUNAKAN PENDEKATAN BAYESIAN (Studi Kasus: Pasien Rawat Inap Penderita Demam Tifoid di RSUD Haji Makassar) Adi Rahmat Faisal; Muhammad Nadjib Bustan; Suwardi Annas
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol 2, No 2 (2020)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm14629

Abstrak. Analisis survival merupakan metode statistika yang digunakan untuk menganalisis data dimana peubah yang diperhatikan adalah waktu sampai terjadinya suatu event. Waktu dapat dinyatakan dalam tahun, bulan, minggu, atau hari dari awal mula dilakukan pengamatan pada seorang individu sampai suatu peristiwa terjadi pada individu. Salah satu tujuan analisis survival adalah untuk mengetahui hubungan antara waktu kejadian dan peubah bebas yang terukur pada saat dilakukan penelitian. Salah satu pendekatan metode regersi yang bisa digunakan adalah regresi Cox Proportional Hazard. Data yang digunakan dalam penelitian ini adalah data pasien penderita demam tifoid di RSUD Haji Makassar. Data demam tifoid memiliki karakteristik yang memungkinkan untuk dilakukan analisis dengan menggunakan regresi Cox Proportional Hazard. Adapun analisisnya menggunakan pendugaan parameter Bayesian, diperoleh faktor yang signifikan berpengaruh terhadap laju kesembuhan pasien adalah nyeri ulu hati. Nilai hazard ratio peubah nyeri ulu hati sebesar 0,63. Nilai tersebut <1 sehingga dapat dikatakan bahwa pasien yang mengalami nyeri ulu hati memiliki laju kesembuhan 0,63 kali dibandingkan yang tidak mengalami nyeri ulu hati.Kata Kunci: Survival Analysis, Regression Cox Proportional Hazard, Thyfoid Fever

Pemodelan dengan Spatial Autoregressive (SAR) pada Angka Putus Sekolah Bagi Anak Usia Wajib Belajar di Provinsi Sulawesi Selatan Rika Nasir; Suwardi Annas; Muhammad Nusrang
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol 3, No 1 (2021)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm9358

Abstract. Regresi spasial merupakan pengembangan dari regresi klasik. Pengembangan ini berdasarkan adanya pengaruh tempat atau spasial dari data yang dianalisis. Beberapa model regresi spasial adalah Spatial Autoregressive (SAR), Spatial Error Model (SEM) dan Spatial Moving Average (SARMA). Penelitian ini menggunakan analisis model SAR terhadap angka putus sekolah di Sulawesi Selatan. Data yang digunakan merupakan data sekunder dari Badan Pusat Statistik Provinsi Sulawesi Selatan tahun 2018. Penelitian ini dilakukan untuk mengetahui model Spatial Autoregressive (SAR) pada data banyaknya angka putus sekolah yang terjadi di Provinsi Sulawesi Selatan, serta mengenalisis faktor-faktor yang memberikan pengaruh signifikan terhadap pertumbuhan angka putus sekolah. Hasil penelitian ini memperoleh model yaitu ; sehingga faktor-faktor yang berpengaruh secara signifikan terhadap angka putus sekolah di Sulawesi Selatan adalah pengeluaran per kapita, rasio murid terhadap sekolah dan jumlah penduduk miskin.Keywords: Regresi Spasial, Spatial Autoregressive Model (SAR), Angka Putus Sekolah

APLIKASI METODE BAYESIAN MODEL AVERAGING (BMA) DENGAN PENDEKATAN MARKOV CHAIN MONTE CARLO (MCMC) UNTUK PERAMALAN CURAH HUJAN DI STASIUN METEOROLOGI KOTA MAKASSAR P. Paramita; Suwardi Annas; Muhammad Kasim Aidid
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol 2, No 3 (2020)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm14642

Abstrak. Curah hujan yang turun dapat mempengaruhi produksi dari beberapa jenis pekerjaan tertentu dan dapat mengganggu aktifitas manusia. Peramalan curah hujan dalam hal ini sangat penting untuk dilakukan. Metode peramalan yang sering dilakukan yaitu metode ensemble. Namun, metode ini cenderung mengalami overdispersive atau underdispersive. Maka dilakukan suatu proses kalibrasi yaitu Bayesian Model Averaging (BMA). Metode ini mampu menggeser nilai rata-rata dan variansi agar mendekati nilai observasi. Penaksiran parameter BMA dilakukan dengan pendekatan Markov Chain Monte Carlo (MCMC) yang mampu mengatasi variasi pada distribusi BMA dan memberikan hasil informasi penting mengenai bobot dan variansi. Metode ini diaplikasikan pada Curah Hujan Bulanan Kota Makassar. Hasil analisis memberikan kesimpulan bahwa metode ensemble tidak ada yang mampu yang menangkap nilai observasi sedangkan metode BMA dengan menggunakan training window 5 mampu menangkap nilai observasi curah hujan bulan Februari, Maret, Mei, Juni, Juli, dan Agustus 2018. Nilai observasi curah hujan bulan Juni yaitu 121 mm. Hasil peramalan dari metode ensemble untuk bulan Juni yaitu 130,6 mm, sedangkan pada metode BMA diperoleh interval ramalan untuk bulan Juni yaitu (-61,02-156,41) mm. Nilai Continous Ranked Probability Score (CRPS) yang diperoleh untuk metode ensemble yaitu 62,07 dan metode BMA yaitu 25,24. Sehingga, metode BMA lebih baik dari metode ensemble karena nilai CRPS yang dihasilkan lebih kecil, sehingga interval yang dihasilkan dari peramalan BMA lebih banyak menangkap nilai observasi.Kata Kunci: Curah Hujan, Ensemble, BMA, MCMC, CRPS.

METODE KAPLAN MEIER UNTUK ANALISIS KETAHANAN HIDUP PENDERITA KANKER PAYUDARA DI RSUD KOTA MAKASSAR Mahrani Mahrani; Muh.Nadjib Bustan; Suwardi Annas
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol 3, No 2 (2021)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm23853

this research, using survival analysis with the Kaplan Meier method. The purpose of this research is to know the life resistance of breast cancer survivors in the Regional General Hospital of Makassar city based on the age group of patients, cancer stage group of patients, and measures chemotherapy group of patients. The results of this research show that (i) the survival rate of breast cancer patients (with a sample size of 74 patients over a period of three years) is more than 354 days with a probability of 0.285 or 28.5%. (ii) When viewed from an early age infected the survival rate for 45 years of age is 1 or 100 for 45 years of an age exceeding 354 days with a probability of 0.229 or 22.9%. The probability of survival for breast cancer patients based on stage level variables, namely stage II of 1 or 100%, survival of stage III breast cancer patients exceeding 21 days with a probability of 0.929 or 92.9%, and survival of stage IV breast cancer patients exceeding 354 days with a probability of 0. The survival of patients following chemotherapy exceeded 354 days with a probability of 0.292 and the survival of patients who did not follow chemotherapy exceeded 17 days with a probability of 0.727

Implementation of K-Means Clustering on Poverty Indicators in Indonesia Suwardi Annas; Bobby Poerwanto; Sapriani Sapriani; Muhammad Fahmuddin S
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 21 No 2 (2022)
Publisher : LPPM Universitas Bumigora

This study aims to cluster all districts/cities in Indonesia related to poverty indicators. The attributes used are poverty gap index and poverty severity index. The data used comes from BPS. The method used is K-Means clustering, and the results show that by using the elbow and silhouette index methods, the optimal number of clusters is 2, where for cluster 1, it can be defined as a cluster with an area with a high poverty gap index and poverty severity index compared to cluster 2. As a result, cluster 1 has 42 districts/cities, and 472 for cluster 2.

PENERAPAN MODEL PEMBELAJARAN KOOPERATIF TIPE EXPLICIT INSTRUCTION DALAM MENINGKATKAN HASIL BELAJAR IPS PADA SISWA KELAS IX SMP NEGERI 2 BONTORAMBA KABUPATEN JENEPONTO TAHUN PELAJARAN 2017/2018 Ridawati Ridawati; Suwardi Annas; Saripuddin D; Muh Yahya
Jurnal Ilmiah Pena: Sains dan Ilmu Pendidikan Vol 10, No 2 (2018): Jurnal Ilmiah Pena Volume 10 Nomor 2 November 2018
Publisher : STKIP Pembangunan Indonesia Makassar

The research examines on the improvement of Social Science Learning Result through the implementation of cooperative learning model of Explicit Instruction type to class IX.3 Students at SMP Negeri 2 Bontoramba in Jeneponto District. The objectives of the research are to discover : (1) The description of Social Science Learning Result of the students in class IX.3 at SMP Negeri 2 Bontoramba in Jeneponto District after implementin cooperative Learning model of Explicit Instruction type. (2) The description activiti students in class IX.3 at SMP Negeri 2 Bontoramba subdistrict of Jeneponto district in following learning Social Science by using of cooperative Learning Model of Explicit Instruction. (3) The description activities teacher in The Implementation of cooperative Learning Model of Explicit Instruction. The research was classroom action research which conducted in two cycles. Each cycle consistedof four stages, namely : (1) planning,(2) action, (3) observation, and (4) reflection. The subjects of the research were one teacher and students in class IX.3 Students at SMP Negeri 2 Bontoramba Subdistrict of Jeneponto District with the total of 26 persons. The instruments of the research were observation sheets for the teachers and students, learning result test, and documentation. Data analysis technique used is quantitatively descriptive with percentage. The result of the first cycle test reveals that the average score achieves 69,69 which is in medium category. Out of 26 students,16 students (61,5%) had successfully reached the learning completeness and 10 students (38,5%) had not completed. The result of the secon cycle test indicates that the average score achieves 79,04 which is in very high category. Out of 26 students, 26 students (100%) had successfully achieved the learning completeness. The results of the research showed that there was an increase in the results of learning Social Sciences of Class IX.3 student at SMP Negeri 2 Bontoramba in Jeneponto District after implementedCooperative Learning Model of Explicit Instruction Type.Keywords : learning outcomes, student activities, teacher activities.Cooperative Learning Model of Explicit Instruction Type.

ANALISIS FAKTOR-FAKTOR KESULITAN BELAJAR MATA PELAJARAN ILMU PENGETAHUAN SOSIAL PADA SISWA KELAS V DI SD INPRES BERTINGKAT MAMAJANG II KOTA MAKASSAR Sri Hastuti; Suwardi Annas; Alin Liana
Jurnal Ilmiah Pena: Sains dan Ilmu Pendidikan Vol 12, No 2 (2021): Jurnal Ilmiah Pena Volume 12 Nomor 2 November 2021
Publisher : STKIP Pembangunan Indonesia Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51336/jip.v15i2.281

This study aims to 1) determine the factors of learning difficulties in social studies subjects, 2) determine the solutions that can be given in dealing with learning difficulties in social studies subjects. This research is a qualitative research conducted at SD Inpres Bertingkat Mamajang II with the subject of the research is class V with high, medium and low social studies ability categories. The data were collected by using in-depth interviews, observation and documentation. The data analysis technique uses descriptive analysis techniques through data reduction, data display and data verification, while the validity of the data uses credibility, time triangulation, transperability, dependability, and confirmability. The results obtained were 1) Internal factors difficulty in learning come from student interest, motivation, and intelligence; External factors difficulty in learning are including the learning process and inadequate facilities / infrastructure. 2) Solutions to overcome student learning difficulties by increasing student interest and motivation in learning, carrying out a creative learning process, providing adequate supporting facilities / infrastructure for social studies learning. Keywords: Difficulty Learning Social Sciences

Co-Authors Adi Rahmat Faisal Ahmad Fudhail Majid Alakbar Akbar Alin Liana Andi Muhammad Ridho Yusuf Sainon Andi Pandjajangi Asdar Ahmad Aswi, Aswi BAKHRANI RAUF Bobby Poerwanto Bobby Poerwanto Fajar Arwadi Fithriyah Azzahrah Hastuti Hastuti Irwan Irwan Irwan Irwan Irwan Irwan Irwan Irwan Laksono Trisnantoro Luthfiah Arradiah Mahrani Mahrani Muh Yahya Muh.Nadjib Bustan Muhammad Abdy Muhammad Fahmuddin Muhammad Fahmuddin Muhammad Kasim Aidid Muhammad Kasim Aidid Muhammad Nadjib Bustan Muharram Muharram Nur Aisyah Nur Isra Nurhamidah Mursyidin Nurul Fadhilah Syahrul Nurul Imania Kalla Nusrang, Muhammad P. Paramita Rahmat Hesha Safei Ridawati Ridawati Rika Nasir Ruliana Sapriani Sapriani Saripuddin D Sitti Faika Syafruddin Side Uca Sideng Wahidah Sanusi Zulkifli Rais

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