cover
Contact Name
Ansari Saleh Ahmar
Contact Email
jurnalvariansi@unm.ac.id
Phone
-
Journal Mail Official
jurnalvariansi@unm.ac.id
Editorial Address
Program Studi Statistika, Fakultas MIPA UNM, Jalan Daeng Tata Raya, Makassar, 90223
Location
Kota makassar,
Sulawesi selatan
INDONESIA
VARIANSI: Journal of Statistics and Its Application on Teaching and Research
ISSN : -     EISSN : 26847590     DOI : http://dx.doi.org/10.35580/variansiunm26374
VARIANSI: Journal of Statistics and Its application on Teaching and Research memuat tulisan hasil penelitian dan kajian pustaka (reviews) dalam bidang ilmu dasar ataupun terapan dan pembelajaran dari bidang Statistika dan Aplikasinya dalam pembelajaran dan riset berupa hasil penelitian dan kajian pustaka.
Articles 5 Documents
Search results for , issue "Vol. 5 No. 02 (2023)" : 5 Documents clear
Penerapan Radial Basis Function Neural Network dalam Mengklasifikasikan Kab/Kota di Provinsi Sulawesi Selatan Berdasarkan Indeks Kesejahteraan Rakyat Jiran Julita; Sudarmin Sudarmin; Zulkifli Rais
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 5 No. 02 (2023)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm95

Abstract

Jiran Julita, 2023. Penerapan Radial Basis Function Neural Network dalam Mengklasifikasikan Kab/Kota di Provinsi Sulawesi Selatan Berdasarkan Indeks Kesejahteraan Rakyat. Program Studi Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Negeri Makassar. (Dibimbing oleh Sudarmin dan Zulkifli Rais). Klasifikasi merupakan cara pengelompokan benda berdasarkan ciri-ciri yang dimiliki oleh objek klasifikasi. Metode yang digunakan dalam penelitian ini yaitu radial basis function neural network (RBFNN) yang merupakan salah satu arsitektur ANN yang popular digunakan dalam klasifikasi. Penelitian ini bertujuan untuk melihat klasifikasi dari Kab/Kota di Provinsi Sulawesi Selatan berdasarkan indeks kesejahteraan rakyat menggunakan RBFNN. Adapun data yang digunakan berjumlah 24 data dengan 10 variabel. Pada penelitian ini metode K-Means diaplikasikan untuk mengelompokan Kab/Kota di Provinsi Sulawesi Selatan berdasarkan indeks kesejahteraan rakyat dengan validasi cluster menggunakan Davies Boulding Index, hasil klasifikasi dari penelitian ini diperoleh 4 cluster terbaik berdasarkan indeks kesejahteraan rakyat Kab/Kota di Provinsi Sulawesi Selatan dengan perfoma klasifikasi dengan hasil accuracy 90%, precision 75%, recall 100% dan F-Measure 85%.
Analisis Regresi Nonparametrik Spline Truncated untuk Menganalisis Faktor-Faktor yang Mempengaruhi Tingkat Pengangguran Terbuka di Provinsi Sulawesi Selatan Devi Carolin Wongkar; Ruliana Ruliana; Muhammad Fahmuddin S
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 5 No. 02 (2023)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm101

Abstract

The nonparametric regression analysis is a regression model used to determine the relationship between response variable and independent variables with unknown regression curve shapes. In the nonparametric approach, one of the frequently used estimators is the spline truncated. Spline truncated model is a segmented polynomial truncation model. The advantage of this model is that it is flexible because it has knot points that can show changes in data patterns. The unemployment rate in South Sulawesi Province in 2021 reached 5.72% and became the province with the second highest unemployment rate on Sulawesi Island. Therefore, spline truncated nonparametric regression modelling will be carried out in the case of unemployment rate with each of the factors that are thought to be influential because the regression curve is found not to form a certain pattern. Based on the analysis results, the best truncated spline nonparametric regression model was obtained using three knot points and obtained the minimum GCV value of 0.38 with a coefficient of determination (R2) value of 89%. Factors that have a significant effect on the unemployment rate in South Sulawesi are mean years of schooling (x1) and labour force participation rate (x2).
Analisis Regresi Data Panel pada Angka Partisipasi Murni Jenjang Pendidikan SMP Sederajat di Provinsi Jawa Barat pada Tahun 2018-2021 Karunia Rahayu Ayu; Muhammad Kasim Aidid; Zulkifli Rais
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 5 No. 02 (2023)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm113

Abstract

Pure Enrollment Rate (APM) is the ratio of school-age children to the corresponding age population and is expressed as a percentage. Regression analysis is a statistical analysis method that aims to see the relationship between a dependent variable and one or more independent variables. Regression using panel data is called the panel data regression model. Panel data is a combination of time series and cross-section data. This study aims to determine the modeling of regression analysis with panel data regarding the Pure Participation Rate (APM) at the junior high school education level in West Java Province in 2018-2021 and to determine the factors that affect the level of Pure Participation Rate (APM) at the junior high school education level in West Java Province in 2018-2021. Based on the model selection carried out by conducting the Chow Test, Hausman Test, and Breucsh-Pagan Test, the best model is the Random Effect Model. From the random effect model, it is known that the factor or variable that has a very significant effect on the Pure Participation Rate (APM) of equivalent junior high schools in West Java province is the student-to-school ratio variable (X1).
APLIKASI FUNGSI TRANSFER MULTIVARIAT UNTUK PERAMALAN CURAH HUJAN DI KOTA MAKASSAR Idul Fitri Abdullah Abdullah; Ruliana Ruliana; Muhammad Fahmuddin S
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 5 No. 02 (2023)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm117

Abstract

This study aims to determine the transfer function model and factors that significantly affect the level of rainfall in Makassar city. This study uses rainfall data as the output series and air humidity (X1), air temperature (X2) and wind speed (X3) as the input series. The data used is monthly data with a period of January 2013 - December 2022. The initial stage of modeling is done by determining the ARIMA model of each input series which is then used to calculate the identification of the transfer function model Based on the research obtained multivariate transfer function model X1 (b=3, r=0, s=0) X12(b=0, r=0, s=0) ARIMA (2,1,0)(1,1,0)12 with air humidity and air temperature being significant factors affecting rainfall in Makassar city.
Pemodelan Regresi Data Panel terhadap Determinan Indeks Kualitas Lingkungan Hidup (IKLH) Provinsi di Pulau Sulawesi Tahun 2011-2020 Nurhamidah Mursyidin; Suwardi Annas; Zulkifli Rais
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 5 No. 02 (2023)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm118

Abstract

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