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All Journal Media Statistika Jurnal Ilmiah Pena: Sains dan Ilmu Pendidikan Indonesian Journal of Statistics and Its Applications Matrik : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jambura Journal of Mathematics Jurnal Varian Uniqbu Journal of Social Sciences Variansi : Journal of Statistics and Its Application on Teaching and Research ARRUS Journal of Mathematics and Applied Science 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
Annas, Suwardi
Fakultas Matematika Dan Ilmu Pengetahuan Alam, Universitas Negeri Makassar
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Binary Logistic Regression Model of Stroke Patients: A Case Study of Stroke Centre Hospital in Makassar Suwardi Annas; Aswi Aswi; Muhammad Abdy; Bobby Poerwanto
Indonesian Journal of Statistics and Applications Vol 6 No 1 (2022)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v6i1p161-169

Abstract

This paper aimed to determine factors that affect significantly types of stroke for stroke patients in Dadi Stroke Center Hospital. The binary logistic regression model was used to analyze the association between the types of stroke and some covariates namely age, sex, total cholesterol, blood sugar level, and history of diseases (hypertension/stroke/diabetes mellitus). Maximum Likelihood Estimation was used to estimate parameters. Combinations of covariates were compared using goodness-of-fit measures. Comparisons were made in the context of a case study, namely stroke patients (2017-2020). The results showed that a binary logistic model combining the history of diseases and blood sugar level provided the most suitable model as it has the smallest AIC and covariates included are statistically significant. The coefficient estimation of the history of diseases variable is -0.92402 with an odds ratio value exp(-0.92402)=0.4. This means that stroke patients who have a history of diseases experience a reduction of 60% in the odds of having a hemorrhagic stroke compared to stroke patients that do not have a history of diseases. In other words, stroke patients who have a history of diseases tend to have a non-hemorrhagic stroke. Furthermore, the coefficient estimation of blood sugar level is 0.74395 with an odds ratio value exp(0.74395)=2. It means that stroke patients who do not have normal blood sugar levels tend to have a hemorrhagic stroke 2 times greater than stroke patients with normal blood sugar levels. A history of diseases and blood sugar level were factors that significantly affect the types of stroke.
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1378.14 KB) | DOI: 10.34312/jjom.v4i1.11883

Abstract

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

Abstract

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

Abstract

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.
PERAN KEPEMIMPINAN KEPALA SEKOLAH DALAM MENERAPKAN MANAJEMEN MUTU PENDIDIKAN: (The Leadership Role of the Principal in Implementing Education Quality Management) Alakbar Akbar; Hastuti Hastuti; Suwardi Annas
Uniqbu Journal of Social Sciences Vol. 2 No. 3 (2021): Uniqbu Journal of Social Sciences (UJSS)
Publisher : LPPM UNIQBU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47323/ujss.v2i3.154

Abstract

Penelitian ini bertujuan untuk mendeskripsikan: 1) Peran kepala sekolah dalam menerapkan manajemen mutu pendidikan di SMP Negeri 2 Arungkeke, Kabupaten Jeneponto, 2) Faktor pendukung dan penghambat kepala sekolah dalam menerapkan manajemen mutu pendidikan di SMP Negeri 2 Arungkeke, Kabupaten Jeneponto. Jenis penelitian yang digunakan adalah penelitian deskriptif kualitatif. Penelitian kualitatif adalah suatu pendekatan penelitian yang mengungkap situasi sosial tertentu dengan mendeskripsikan kenyataan secara benar, dibentuk oleh kata-kata berdasarkan teknik pengumpulan dan analisis data yang relevan yang diperoleh dari situasi yang alamiah. Sumber data pada penelitian ini, yaitu data yang menunjukkan kualitas atau mutu dari sesuatu yang ada, berupa keadaan, proses, kejadian atau peristiwa dan lain-lain yang dinyatakan dalam bentuk perkataan. Informan dalam penelitian adalah kepala sekolah, guru IPS kelas IX, dan Guru IPS kelas VII/VIII, guru Bahasa Inggris dan Staft SMP Negeri 2 Arungkeke. Teknik penentuan informan dilakukan secara purposive yakni berdasarkan kapasitas yang memberikan kemudahan dan kesediaan dalam wawancara. Hasil penelitian ini menunjukkan bahwa 1) peran kepemimpinan kepala sekolah dalam menerapkan manajemen mutu pendidikan di SMP Negeri 2 Arungkeke,  yaitu : (a) kepala sekolah harus memiliki strategi yang tepat dan (b) menerapkan manajemen kepemimpinan. 2) Faktor pendukung dan penghambat kepala sekolah dalam menerapkan manajemen mutu pendidikan di SMP Negeri 2 Arungkeke yaitu : faktor pendukung (a) gotong royong dan kekeluargaan (b) memberikan kesempatan kepada guru dalam kegiatan diklat penerapan profesi (c) memfasilitasi segala kegiatan sekolah, faktor penghambat (a) kurangnya motivasi dan semangat kepala sekolah (b) kurangnya kemampuan kepemimpinan kepala sekolah (c) kurangnya sarana dan prasarana dan (d) rendahnya sikap mental.
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

Abstract

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

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

Abstract

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

Abstract

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (411.441 KB) | DOI: 10.30812/matrik.v21i2.1289

Abstract

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