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All Journal Journal of Mathematics Education and Application (JMEA) MES: Journal of Mathematics Education and Science Journal of Research in Mathematics Trends and Technology Journal of Mathematics Technology and Education Innovative: Journal Of Social Science Research
Pane, Rahmawati
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PERBANDINGAN PENGENDALIAN KUALITAS PRODUK WALL DISPLAY DENGAN DIAGRAM KENDALI D^2 DAN T^2 HOTELLING Harahap, Sherly Vitara; br Tarigan, Ernita Dewi; Sembiring, Pasukat; Pane, Rahmawati
MES: Journal of Mathematics Education and Science Vol 10, No 1 (2024): Edisi Oktober (Progress)
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/mes.v10i1.9584

Abstract

Quality control is the application of a statistical model of quality control to collect and analyze data to evaluate and monitor production results. Melia Frame Calligraphy is an agent and manufacturer of frames or frame bars and finished frameworks made from fiber and wood. The best-selling product is the wall display. Although wall displays are in high demand, they are also the most returned products due to defects since 2023. Based on observation data, it is calculated that the product defect data is quite high, with an average total of 34 defects per day. This study aims to detect the quality of wall display products with  (Mahalanobis Distance) and  Hotelling control charts at Melia Frame Calligraphy Trade Business. The results of this study found that the product experienced the most defects in October 2023 with a total defective product of 1009 units. By using the control diagram, 20 observations out of a total of 75 observations are outside the control limits, then by using the control diagram, 2 observations out of a total of 75 observations are outside the control limits. This shows that the wall display production process is not yet under control. These observations show that the  (Mahalanobis Distance) control chart has more sensitive control limits than the  Hotelling control chart control limits.
Perbandingan Regresi LASSO dan Principal Component Regression dalam Mengatasi Masalah Multikolinearitas Nasution, Elsa Fadillah; Pane, Rahmawati
MES: Journal of Mathematics Education and Science Vol 10, No 1 (2024): Edisi Oktober (Progress)
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/mes.v10i1.9656

Abstract

Multicollinearity is a problem that often arises in regression analysis. If the assumption of the absence of multicollinearity is not met, researchers will have difficulty in identifying independent variables that have a significant effect in the regression model. The presence of multicollinearity can cause the estimation of regression parameters in the Ordinary Least Square (OLS) method to be inefficient. To overcome this, the LASSO Regression method and the Principal Component Regression (PCR) method are used. The data used in this study are generation data derived from low (0,1-0,3), medium (0,4-0,6), and high (0,7-0,9) correlation levels with different sample sizes (n=20,40,120,200) from normal distribution with 30 and 60 independent variables. The performance of LASSO Regression method and Principal Component Regression (PCR) method is evaluated using Mean Square Error (MSE) value and coefficient of determination ( ) value. Based on this research, the LASSO Regression method has better efficiency than the Principal Component Regression (PCR) method because the LASSO Regression method obtains a smaller Mean Square Error (MSE) value and a higher coefficient of determination ( ) value than the Principal Component Regression (PCR) method.
ANALISIS METODE PLS-SEM DENGAN MODIFIKASI MODEL UTAUT2 PADA PENGGUNAAN CHATGPT OLEH MAHASISWA UNIVERSITAS SUMATERA UTARA Silalahi, Putri Mayang Syafira; br Tarigan, Ernita Dewi; Pane, Rahmawati; Suyanto, Suyanto
MES: Journal of Mathematics Education and Science Vol 10, No 1 (2024): Edisi Oktober (Progress)
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/mes.v10i1.9562

Abstract

The rapid advancement of technology in modern times has a great influence in various aspects of life, including in the world of education. One example is the presence of ChatGPT among students in learning activities. The use of ChatGPT has many benefits but the use of this technology must still be addressed wisely to avoid ethical issues, copyright and plagiarism. This study aims to determine what factors influence the use of ChatGPT by students of the University of North Sumatra in education. By using the Partial Least Squares-Structural Equation Modeling (PLS-SEM) method with the variables used, namely the UTAUT2 model. The findings of this study state that 8 hypotheses of the relationship between variables tested in the study, of which 4 hypotheses of the relationship between variables are accepted and 4 hypotheses of the relationship between variables are rejected.
Forecasting the Amount of Oil Palm Production in Simalungun Regency Based on Data for 2000-2019 Using Double Exponential Smoothing Method Nababan, Yosua Pernando; Pane, Rahmawati
Journal of Mathematics Technology and Education Vol. 1 No. 2 (2022): Journal of Mathematics Technology and Education
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (662.821 KB) | DOI: 10.32734/jomte.v1i2.7734

Abstract

Economic growth in our country comes from various sectors, one of which is the agricultural and plantation sectors. This sector plays an important role in generating a source of foreign exchange for our country after the oil and gas mining sector through its commodity exports. The data used by the author in this final project is secondary data from the Central Bureau of Statistics of North Sumatra regarding oil palm production in Simalungun Regency. Quantitative analysis is used to determine the amount of oil palm production in Simalungun Regency which is predicted in 2020, 2021, and 2022, involving production patterns from 2000 to 2019 Then based on the amount of production data, the data is processed using quantitative time forecasting methods. series, namely Double Exponential Smoothing one parameter from Brown, by looking at the resulting error value, namely the Mean Absoute Percentage Error (MAPE) value. Based on forecasting results, the amount of oil palm production in Simalungun Regency in 2020 is 467,295.15 tons, the amount of oil palm production in Simalungun Regency in 2021 is 501,766.48 tons, in 2022 it is 536,237.81 tons. So the production of palm oil in Simalungun Regency increases from year to year, but there are times when it decreases not so drastically, so it can be concluded that the production of palm oil harvests in Simalungun Regency is increasing.
Comparison of Newton Raphson Method and Ridge Method In Probit Regression Parameter Estimation Yastri, Yastri; Pane, Rahmawati
JMEA : Journal of Mathematics Education and Application Vol 2, No 3 (2023): Oktober
Publisher : JMEA : Journal of Mathematics Education and Application

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jmea.v2i3.13327

Abstract

Probit regression model is a non-linear model used in the process of analyzing the relationship between a response variable that has categorical properties. The problem that is very often experienced in probit regression when the predictor variable consists of one or more is that there is a very high correlation between predictor variables called multicollinearity. To overcome this, the Newton Raphson method and the Rigde method are used. So this research was conducted to compare the Newton Raphson method and the Ridge method in the estimation of the Probit Regression parameter. The data used in this research is 1000 data generation that contains multicollinearity. Based on this research, the estimated mean square error of the Probit Regression model using the Newton Raphson method is 0.488. The estimation result of the mean square error of the Probit Regression model using the Ridge method is 0.488. The results of this study indicate that the estimation of the Probit Regression parameter using the Newton Raphson method is as good as the Ridge method. This can be seen from the estimated value of MSE using the Newton Raphson method and the Ridge method. This can happen due to the small value of the langrage multiplier obtained, so it does not have an impact on the model obtained.
Perbandingan Regresi LASSO dan Principal Component Regression dalam Mengatasi Masalah Multikolinearitas Nasution, Elsa Fadillah; Pane, Rahmawati
MES: Journal of Mathematics Education and Science Vol 10, No 1 (2024): Edisi Oktober
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/mes.v10i1.9656

Abstract

Multicollinearity is a problem that often arises in regression analysis. If the assumption of the absence of multicollinearity is not met, researchers will have difficulty in identifying independent variables that have a significant effect in the regression model. The presence of multicollinearity can cause the estimation of regression parameters in the Ordinary Least Square (OLS) method to be inefficient. To overcome this, the LASSO Regression method and the Principal Component Regression (PCR) method are used. The data used in this study are generation data derived from low (0,1-0,3), medium (0,4-0,6), and high (0,7-0,9) correlation levels with different sample sizes (n=20,40,120,200) from normal distribution with 30 and 60 independent variables. The performance of LASSO Regression method and Principal Component Regression (PCR) method is evaluated using Mean Square Error (MSE) value and coefficient of determination ( ) value. Based on this research, the LASSO Regression method has better efficiency than the Principal Component Regression (PCR) method because the LASSO Regression method obtains a smaller Mean Square Error (MSE) value and a higher coefficient of determination ( ) value than the Principal Component Regression (PCR) method.
ANALISIS METODE PLS-SEM DENGAN MODIFIKASI MODEL UTAUT2 PADA PENGGUNAAN CHATGPT OLEH MAHASISWA UNIVERSITAS SUMATERA UTARA Silalahi, Putri Mayang Syafira; br Tarigan, Enita Dewi; Pane, Rahmawati; Suyanto, Suyanto
MES: Journal of Mathematics Education and Science Vol 10, No 1 (2024): Edisi Oktober
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/mes.v10i1.9562

Abstract

The rapid advancement of technology in modern times has a great influence in various aspects of life, including in the world of education. One example is the presence of ChatGPT among students in learning activities. The use of ChatGPT has many benefits but the use of this technology must still be addressed wisely to avoid ethical issues, copyright and plagiarism. This study aims to determine what factors influence the use of ChatGPT by students of the University of North Sumatra in education. By using the Partial Least Squares-Structural Equation Modeling (PLS-SEM) method with the variables used, namely the UTAUT2 model. The findings of this study state that 8 hypotheses of the relationship between variables tested in the study, of which 4 hypotheses of the relationship between variables are accepted and 4 hypotheses of the relationship between variables are rejected.
PERBANDINGAN PENGENDALIAN KUALITAS PRODUK WALL DISPLAY DENGAN DIAGRAM KENDALI D^2 DAN T^2 HOTELLING Harahap, Sherly Vitara; br Tarigan, Enita Dewi; Sembiring, Pasukat; Pane, Rahmawati
MES: Journal of Mathematics Education and Science Vol 10, No 1 (2024): Edisi Oktober
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/mes.v10i1.9584

Abstract

Quality control is the application of a statistical model of quality control to collect and analyze data to evaluate and monitor production results. Melia Frame Calligraphy is an agent and manufacturer of frames or frame bars and finished frameworks made from fiber and wood. The best-selling product is the wall display. Although wall displays are in high demand, they are also the most returned products due to defects since 2023. Based on observation data, it is calculated that the product defect data is quite high, with an average total of 34 defects per day. This study aims to detect the quality of wall display products with  (Mahalanobis Distance) and  Hotelling control charts at Melia Frame Calligraphy Trade Business. The results of this study found that the product experienced the most defects in October 2023 with a total defective product of 1009 units. By using the control diagram, 20 observations out of a total of 75 observations are outside the control limits, then by using the control diagram, 2 observations out of a total of 75 observations are outside the control limits. This shows that the wall display production process is not yet under control. These observations show that the  (Mahalanobis Distance) control chart has more sensitive control limits than the  Hotelling control chart control limits.
Pemodelan Geographically Weighted Panel Regression (GWPR) Pada Pengangguran Terbuka di Provinsi Sumatera Utara Periode 2018-2022 Tambunan, Ruth A; Nasution, Putri K; Sutarman, Sutarman; Pane, Rahmawati
Innovative: Journal Of Social Science Research Vol. 4 No. 4 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i4.12802

Abstract

Pada penerapan analisis regresi, sering kali dipengaruhi oleh aspek spasial juga temporal. Dengan memanfaatkan pendekatan regresi panel tertimbang secara geografis yakni geographically weighted panel regression (GWPR). GWPR merupakan pengembangan dari analisis regresi yang mempertimbangkan aspek spasial maupun temporal. Dalam penggunaan metode GWPR, dibutuhkan fungsi pembobot yang digunakan untuk memboboti tiap wilayah penelitian. Salah satu dari sekian banyak provinsi di Indonesia yang berusaha mengatasi masalah pengangguran terbuka adalah Sumatera Utara. Studi ini menggunakan data sekunder yang diambil dari BPS, mencakup data cross section dari 33 kabupaten/kota di Sumatera Utara dan data time series dari tahun 2018 hingga 2022. Matriks pembobot yang optimum dihasilkan oleh fungsi pembobot kernel Gaussian. Hasil penelitian menunjukkan nilai statistik uji t, standar error, dan p-value untuk setiap variabel di setiap lokasi pengamatan melalui penggunaan pengujian parsial. Pemodelan GWPR menghasilkan nilai R2 sebesar 93,511% dan RMSE sebesar 0,6702.
Estimation of Heteroskedasticity Semiparametric Regression Curve Using Fourier Series Approach Pane, Rahmawati; Sutarman; Andi Tenri Ampa
Journal of Research in Mathematics Trends and Technology Vol. 2 No. 1 (2020): Journal of Research in Mathematics Trends and Technology (JoRMTT)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jormtt.v2i1.3744

Abstract

A heteroskedastic semiparametric regression model consists of two main components, i.e. parametric component and nonparametric component. The model assumes that any data (x̰ i′ , t i , y i ) follows y i = x̰ i′ β̰+ f(t i ) + σ i ε i , where i = 1,2, … , n , x̰ i′ = (1, x i1 , x i2 , … , x ir ) and t i is the predictor variable. Parameter vector β̰ = (β 1 , β 2 , … , β r ) ′ ∈ ℜ r is unknown and f(t i ) is also unknown and is assumed to be in interval of C[0,π] . Random error ε i is independent on zero mean and varianceσ 2 . Estimation of the heteroskedastic semiparametric regression model was conducted to evaluate the parametric and nonparametric components. The nonparametric component f(t i ) regression was approximated by Fourier series F(t) = bt + 12 α 0 + ∑ α k 𝑐 𝑜𝑠 kt Kk=1 . The estimation was obtained by means of Weighted Penalized Least Square (WPLS): min f∈C(0,π) {n −1 (y̰− Xβ̰−f̰) ′ W −1 (y̰− Xβ̰− f̰) + λ ∫ 2π [f ′′ (t)] 2 dt π0 } . The WPLS solution provided nonparametric component f̰̂ λ (t) = M(λ)y̰ ∗ for a matrix M(λ) and parametric component β̰̂ = [X ′ T(λ)X] −1 X ′ T(λ)y̰
Co-Authors Andi Tenri Ampa Br Tarigan, Enita Dewi br Tarigan, Ernita Dewi Harahap, Sherly Vitara Nababan, Yosua Pernando Nasution, Elsa Fadillah Nasution, Putri K Pasukat Sembiring Silalahi, Putri Mayang Syafira Sutarman Sutarman Sutarman Suyanto Suyanto Tambunan, Ruth A Yastri, Yastri