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All Journal Media Statistika Jurnal Matematika Sains dan Teknologi Jurnal Varian Variansi : Journal of Statistics and Its Application on Teaching and Research JINAV: Journal of Information and Visualization Jurnal Dedikasi Panrannuangku Jurnal Pengabdian Masyarakat ARRUS Journal of Mathematics and Applied Science SAINSMAT: Journal of Applied Sciences, Mathematics, and Its Education VARIANSI: Journal of Statistics and Its Application on Teaching and Research
Ruliana
Department Of Statistics, Universitas Negeri Makassar, Makassar, 90223, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Immunology & microbiology Library & Information Science Mathematics Physics Public Health Social Sciences Other

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Ordinary Least Square Method in Multiple Regression Analysis to Estimating Coefficients of Factors Affecting Human Development Index Ogi Suhendra; Muhammad Arif Tiro; Ruliana
ARRUS Journal of Mathematics and Applied Science Vol. 2 No. 1 (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/mathscience632

Abstract

Analisis Regresi merupakan suatu analisis data yang memperhatikan hubungan antara suatu peubah respon (response variable) dengan satu atau lebih peubah penjelas (explanatory variables). Penelitian ini menggunakan metode Ordinari Least Square (OLS). Metode OLS merupkan metode dasar yang digunakan untuk menyelesaikan suatu masalah data dengan penyelesaian berbentuk model regresi linier. Hasil pemodelan menunjukkan pengaruh variabel Angka Harapan Hidup, Harapan Lama Sekolah, Rata-Rata Lama Sekolah, dan Pengeluaran Perkapita terhadap Indeks Pembangunan Manusia Provinsi Sulawesi Selatan dilihat dari nilai R-Square sebesar 99.63%. menunjukkan bahwa besar persentase variasi Indeks Pembangunan Manusia yang bisa dijelaskan oleh keempat variabel bebas yaitu Angka Harapan Hidup, Harapan Lama Sekolah, Rata-rata Lama Sekolah, dan Pengeluaran Perkapita, sebesar 99.63% sedangkan sisanya sebesar 0.37 dijelaskan oleh variabel-variabel lain diluar penelitian. Artinya semua variabel bebas berpengaruh signifikan terhadap variabel terikat dengan taraf signifikan 5%.
Development of R Package for Regression Analysis with User Friendly Interface Arfan Shalihin Amir; Muhammad Arif Tiro; Ruliana
ARRUS Journal of Mathematics and Applied Science Vol. 2 No. 1 (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/mathscience728

Abstract

The use of pirated software in Indonesia is quite high compared to other countries in the world. One of the efforts made to reduce the level of software piracy is to develop publicly licensed software such as R software which is open source software. The preparation of this package uses the R software and other additional packages, especially packages for regression analysis. Making this package can make it easier for users to perform regression analysis easily and legally. This package is named SLR App (Simple Linear Regression App) and MLR App (Multiple Linear Regression) which are regression analysis packages that have a user friendly interface. From the tests carried out that this package has similarities from the results of the analysis between the SLR App and MLR App.
Spatial Regression Analysis to See Factors Affecting Food Security at District Level in South Sulawesi Province Irma Yani Safitri; Muhammad Arif Tiro; Ruliana
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/mathscience740

Abstract

Spatial regression is a development of classical linear regression which is based on the influence of place or location. To determine the location/spatial effect, a spatial dependency test was performed using the Moran Index, and the Lagrange Multiplier (LM) test was used to determine a significant spatial regression model. In this study, spatial regression was applied to the case of food security in each district in South Sulawesi Province. The results of the analysis show that there is a negative spatial autocorrelation, meaning that the spatial effect does not affect the level of food security. The significant spatial regression model is the SEM (Spatial Error Model) model. The equation of the SEM model produces variables that have a significant effect, namely the ratio of normative consumption per capita to net availability, percentage of population living below the poverty line, percentage of households with a proportion of expenditure on food more than 65 percent of total expenditure, percentage of households without access to electricity, percentage of households without access to clean water, life expectancy at birth, ratio of population per health worker to the level of population density, the average length of schooling for women above 15 years, and the percentage of children under five with height below standard (stunting). Thus, the resulting distribution pattern is a uniform data pattern. This means that each adjacent district tends to have different characteristics.
Comparison of k-Nearest Neighbor (k-NN) and Support Vector Machine (SVM) Methods for Classification of Poverty Data in Papua Fauziah; Muhammad Arif Tiro; Ruliana
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/mathscience741

Abstract

Classification is a job of assessing data objects to include them in a particular class from a number of available classes. The classification method used is the k-Nearest Neighbor (k-NN) and Support Vector Machine (SVM) methods. The data used in this study is data on poverty in Papua with the category of the number of low/high level poor people. Of the 29 regencies/cities that were sampled, 15 regencies/cities represent the number of low-level poor people and 14 districts/cities are the number of high-level poor people. The results of the analysis obtained are the k-Nearest Neighbor (k-NN) method with a value of k=15 producing an accuracy of 58.62%, while the Support Vector Machine (SVM) method with Parameter cost = 1 using the RBF kernel produces an accuracy value. by 93.1%. The classification criteria to find the best method is to look at the Root Mean Square Error (RMSE) which states that the Support Vector Machine (SVM) method is better than the k-Nearest Neighbor (k-NN) method.
Manajemen Referensi dengan Aplikasi Zotero Muhammad Kasim Aidid; M. Nadjib Bustan; Ruliana Ruliana
DEDIKASI Vol 22, No 2 (2020): Jurnal Dedikasi
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26858/dedikasi.v22i2.16120

Abstract

Based on the situation analysis, a Community Partnership Program (PKM) activity is proposed to train the use of reference management software for teachers in which SMA Negeri 4 Pinrang Regency is the partner. The identified problems are: (1) Lack of skills in using reference manager software, (2) Zotero as open source software is unknown, (3) The need for the ability to use reference manager software that can be applied in writing scientific papers. The material is presented through zoom meetings in plenary and in groups according to the schedule. In the plenary presentation of the material, material on basic concepts in research and writing of scientific papers was presented then continued with the provision of material on the use of Zotero in writing scientific articles. Some of the requirements to become a participant are: (1) having an interest in learning the basic concepts of reference management, (2) having never attended a similar training. (3) must attend all training activities. From the PKM activities that have been carried out as well as the team's internal survey, it can be concluded that in the implementation of this activity: (1) Participants become literate and skilled in operating the Zotero software, (2) The Zotero menu is well known to PKM participants, (3) Participants have the ability to use Zotero in writing scientific articles.
PENDEKATAN MARKOV CHAIN UNTUK MENGANALISIS PERENCANAAN SUMBER DAYA MANUSIA DI KEPOLISIAN SEKTOR TAMALATE KOTA MAKASSAR Suhartin M; Ruliana Ruliana; Muhammad Kasim Aidid
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/variansiunm23856

Abstract

this research, an analysis of Human Resources planning in the Makassar City Tamalate Police Sector uses Markov Chain. The data used are sourced from secondary data in the Makassar City Tamalate Police Sector from the last two years period, from 2018 to 2019. The Markov Chain is used to find out transfers that occur between police positions with the first process being determining states, calculating inter-state probability values, forming a transition probability matrix, and predicting the number of police officers for the next six years. Based on the research conducted, it can be concluded that five states were formed, the ranks of the Second Police Brigadiers up to the Chief Police Brigadier are classified as Non-Commissioned Officers positions, state two the ranks of Second Police Inspector Adjutant up to First Pollice Inspector Adjutant are clarified as Warrant Officers position, state three Second Police Inspector up to Police Commissioner Adjutant are clarified Low-Rank Officers, four state Pollice Coommisioner are clarified of Mid Rank Officer, state five additional and reduction of Police Members. Based on the results of forecasting, the probability for the most Police Members in the year 2020 to 2025 is a member domiciled as a Non-Commissioned Officers, the probability of a large number of Non-Commissioned Officers is relatively stable at 0.54 from 2020 to 2024 and will decrease by 0.01 in 2025. Probabilities the number of Warrant Officers has increased quite dramatically, in 2020 amounting to 0.35 continues to increase until 2025 which is equal to 0.42. Whereas the probability for the number of Police Members to be Low-Rank Officers has decreased every year from 2020 to 0.08 to 0.03 in 2025. Then for Mid Rank Officers the probability for the number of Police Members to remain stable every year is 0.01. The probability of the number of Police officers in 2020 is 0.02 and in 2025 it is 0.01
Pemodelan Faktor-Faktor yang Mempengaruhi Jenis Kanker Payudara Menggunakan Regresi Logistik Biner (Kasus : Pasien Penderita Kanker Payudara di RSUP Dr. Wahidin Sudirohusodo tahun 2016). Titi Kurnianti HR; Muhammad Nadjib Bustan; R. Ruliana
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol 1, No 3 (2019)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm12898

Abstract

Abstrak Regresi logistik adalah suatu metode analisis statistik yang diterapkan untuk memodelkan variabel dependen yang memiliki dua kategori atau lebih dengan satu atau lebih variabel independen. Regresi Logistik biner merupakan suatu analisis statistika yang digunakan untuk menganalisis hubungan antara satu atau lebih peubah bebas dengan peubah respon yang bersifat biner atau  dichotomous. Peubah bebas pada regresi logistik dapat berupa peubah skala kategorik maupun peubah yang skala kontinu sedangkan peubah respon berupa peubah berskala kategorik. Regresi Logistik Biner dapat diterapkan pada kasus kesehatan, khususnya pada penelitian ini yaitu mengenai kanker payudara. Sesuai uraian diatas maka penulis bermaksud untuk mengkaji dan melakukan penelitian  tentang Pemodelan Faktor-Faktor yang Mempengaruhi Jenis Kanker Payudara Menggunakan Regresi Logistik Biner (Kasus : Pasien Penderita Kanker Payudara di Rumah Sakit Umum Pusat Dr. Wahidin Sudirohusodo). Dari hasil analisis didapatkan bahwa peubah penjelas yang berpengaruh nyata terhadap jenis keganasan kanker terhadap pasien penderita kanker payudara adalah peubah Kemoterapi (X2) dan peubah Metastase (X5) yang masing-masing memiliki nilai odds rasio sebesar 0,17 dan 6,16.  Kata kunci : Kanker Payudara, Regresi Logistik, Regresi Logistik Biner. Abstract Logistic regression is a method of statistical analysis that is applied to model the dependent variable which has two or more categories with one or more independent variables. Binary Logistic Regression is a statistical analysis that is used to analyze the relationship between one or more independent variables with variable binary or dichotomous responses. The free variables in logistic regression can be either categorical scale or continuous scale variables while the response variables are categorical scale variables. Binary Logistic Regression can be applied to health cases, especially in this study, namely breast cancer. In accordance with the description above, the author intends to study and conduct research on Modeling Factors Affecting Types of Breast Cancer Using Binary Logistic Regression (Case: Patients with Breast Cancer Patients at Dr. Wahidin Sudirohusodo Central General Hospital). From the results of the analysis it was found that the explanatory variables that significantly affected the type of cancer malignancy in patients with breast cancer were Chemotherapy variables (X2) and Metastase variables (X5), each of which had odds ratio values of 0.17 and 6.16. Keywords: Breast Cancer, Logistic Regression, Binary Logistic Regression.
ANALISIS PELUANG PENYEBARAN COVID-19 MENGGUNAKAN RANTAI MARKOV DI SULAWESI SELATAN M. Nadjib Bustan; Ruliana Ruliana; Muhammad Kasim Aidid
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/variansiunm25170

Abstract

Virus Corona sudah menyebar ke seluruh negera termasuk salah satunya di Indonesia. Karena transmisi Covid-19 dari manusia ke manusia telah dikonfirmasi dan mobilitas manusia juga merupakan faktor penguat persebaran Covid-19, sehingga diperlukan suatu informasi yaitu data harian Covid-19 yang berguna untuk melihat laju persebaran Covid-19. Oleh karena itu, diperlukan suatu pendekatan untuk menganalisis peluang penyebaran covid-19 di setiap wilayah sehingga pengambilan keputusan menjadi tepat. Pada penelitian ini, dilakukan analisis dengan rantai markov diskrit untuk memprediksi peluang penyebaran Covid-19 pada kabupaten/kota di Sulawesi Selatan. Penelitian ini adalah penelitian yang bersifat kuantitatif dengan menggunakan konsep stokastik. Pada bagian awal dilakukan kajian sumber-sumber pustaka dengan cara mengumpulkan data atau informasi yang berkaitan dengan masalah, mengumpulkan konsep pendukung yang diperlukan dalam menyelesaikan masalah, sehingga didapatkan suatu ide mengenai bahan dasar pengembangan upaya pemecahan masalah.  Hasil penelitian menunjukkan bahwa pada saat pengamatan (28 Agustus 2021) di Sulawesi Selatan (Sulsel), Kota Makassar menjadi daerah dengan peluang penyebaran yang paling tinggi, sedangkan Kabupaten Bantaeng dengan peluang penyebaran terendah. Pada hasil analisis dengan rantai Markov, terlihat bahwa terjadi penurunan peluang infeksi untuk setiap Kabupaten/Kota di Sulawesi Selatan dan cenderung menjadi homogen.Keywords: covid-19, Markov chain, peluang bersyarat
STRUCTURAL EQUATION MODELING FOR ANALYZING THE TECHNOLOGY ACCEPTANCE MODEL OF STUDENTS IN ONLINE TEACHING DURING THE COVID-19 PANDEMIC Suwardi Annas; Ruliana Ruliana; Wahidah Sanusi
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.15.1.104-115

Abstract

Online teaching can be a solution in the learning process during the pandemic to stop the spreading of the Covid-19 infection. Universitas Negeri Makassar (UNM) as an educational institution provided a Learning Management System (LMS) to support the online teaching and learning process with the platform name SYAM-OK. In this research, we examine the behavioral model of a student's acceptance of the use of an information system SYAM-OK in online teaching. 120 students in the sample used online teaching fully during the pandemic. The data was obtained from an online questionnaire using a google form whose contents were based on Technology Acceptance Model (TAM).  The variable of TAM consists of Perceived Ease of Use, Perceived Usefulness, Attitude Towards, Behavioral Intention, and Actual Use. The Structural Equation Modeling (SEM) PLS method was used in this research for modeling the relationship between TAM variables. Based on the results of the SEM we obtained that Perceived Usefulness significantly affects the Attitude Towards and Attitude Towards significantly affects the behavioral intention. By using the bootstrapping and T statistics, we conclude that SEM has identified the significant effects between variables of TAM. 
PEMODELAN LAJU INFLASI DENGAN MENGGUNAKAN REGRESI NON-LINEAR BERBASIS ALGORITMA GENETIKA (Kasus: Kota-Kota di Pulau Jawa) Wildan Mujahid; Muhammad Arif Tiro; Ruliana Ruliana
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 4 No. 1 (2022)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (381.978 KB) | DOI: 10.35580/variansiunm7

Abstract

This research is applied research that uses non-linear regression on the inflation rate data and the factors that are thought to influence it. By using the RESET Test, statistics are obtained, namely the RESET value = 3.7506 with P value = 0.04138, which means that the inflation data is appropriate to use non-linear regression. From the results of this study, it was found that the average inflation rate of 26 cities in Java was 22.08% with a standard deviation of 24.33%. From the results of this study it was also found that the consumer price index (X1), city/district minimum wages (X2), and regional gross domestic product (X3) are factors that affect the inflation rate with the best model with an RMSE value of 0.445.
Co-Authors Ahmar, Ansari Saleh Andi Feriansyah Annas, Suwardi Arfan Shalihin Amir Aswi Aswi Aswi, Aswi Fauziah Irma Yani Safitri Irwan Irwan Irwan Irwan M. Nadjib Bustan M. Nadjib Bustan Miguel Botto-Tobar Muh. Hizbul Zainul Muttaqim Muhammad Arif Tiro Muhammad Arif Tiro Muhammad Arif Tiro Muhammad Isbar Pratama Muhammad Kasim Aidid Muhammad Kasim Aidid Muhammad Kasim Aidid Muhammad Nadjib Bustan Muhammad Nusrang Muhammad Rifandi Nor Zila Abdul Hamid Nurtiwi Nurtiwi Nurul Madany Ogi Suhendra Rezki Amalia Idrus Rezky Novita Said Suhartin M Suwardi Annas Syafruddin Side Taufiq Hidayat Titi Kurnianti HR Wahidah Sanusi Wildan Mujahid Zakiyah Mar'ah Zulkifli Rais