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All Journal EKSAKTA: Journal of Sciences and Data Analysis Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika
Maktisen Ena
Universitas Tribuana Kalabahi
Chemical Engineering, Chemistry & Bioengineering Chemistry Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Materials Science & Nanotechnology Mathematics

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PERBANDINGAN PERBANDINGAN METODE ARTIFICIAL NEURAL NETWORK BACKPROPAGATION DAN GARCH DALAM MEMPREDIKSI HARGA SAHAM ( Studi Kasus : Saham Indosat Tahun 2012 – 2022 ) Maktisen Ena
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 4, ISSUE 2, August 2023
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol4.iss2.art3

Abstract

Abstract: One of the problems encountered in the forecasting process is the problem of heteroscedasticity. Heteroscedasticity occurs a lot, especially in stock data. Pt Share Price Indosat (tbk) from March 6 2012 – January 18 2022 has fluctuated from time to time, so the variance is heteroscedasticity. The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model and Artificial Neural Network Backpropagation (ANNBP) are methods that can be used on data with heteroscedasticity. The aim of this research is to obtain models and forecasting results from GARCH and ANN Backpropagation. In this study, the two models were compared based on the smallest MAPE value. This study uses daily data on the closing of Indosat shares. Forecasting is done on Indosat stock closing data, the total data is 2453 data divided into two parts, namely 80% training data totaling 1962 data and 20% training data totaling 491 data. Forecasting results from the GARCH model obtained a MAPE value of 11.04%, and the ANN Backpropagation model with 7 input layers, 20 hidden layers, obtained a MAPE value of 7.01%. Thus, the best model for predicting Indosat's share price in this study is the backpropagation model.
PENERAPAN METODE SINGLE EXPONENTIAL SMOOTHING DALAM MEMPREDIKSI JUMLAH PENERIMAAN MAHASISWA BARU Maktisen Ena
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 4 No. 2 (2023): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v4i2.357

Abstract

Forecasting is a technique for estimating future data by looking at past data and current data. Admissions of new students at Tribuana Kalabahi University are carried out every year since the founding of the Tribuana Kalabahi University campus, in 2007, the number of new student admissions from year to year has experienced an upward trend, therefore forecasting is carried out using Single Exponential Smoothing. The amount of data from 2007 to 2022 is 16 data. The calculation results with Single Exponential Smnothing have the lowest MAPE value, namely 1.41005% with a value of α = 0.1, the number of new student admissions is 664 people
MODEL BERWIRAUSAHA TERHADAP PRESTASI MATEMATIKA MAHASISWA UNIVERSITAS TRIBUANA KALABAHI Maktisen Ena; Narita Y. Adrianingsih; Falentina L. Kamutlaka
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 4 No. 3 (2023): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v4i3.471

Abstract

This research aims to determine whether there is an influence between entrepreneurship on student achievement, in this case student learning achievement and to find out how to analyze it. The population in this study were all Tribuana Kalabahi University students, totaling 3,101 students. In this research, 153 students were taken randomly (when the students met, the researchers immediately asked questions) at Tribuana Kalabahi University. The method used in this research is an interview, namely randomly interviewing students at Tribuana Kalabahi University. Then the data obtained from the interview results was processed through the SPSS program application with a simple linear regression statistical analysis tool. Judging from the significance value or p-value of 0.008, which is smaller than alpha 0.1, it can be concluded that entrepreneurship has a significant effect on student learning achievement. The regression equation model is Y=3.518-0.093x, because the coefficient value is minus (-) meaning that entrepreneurship (X) has a negative effect on the student's Learning Achievement Index (Y). Which means that if x has a value of 0 or is said to be non-entrepreneurial then the student's cumulative achievement index is 3.518. Meanwhile, if x has a value of 1 or is said to be entrepreneurial, the student's cumulative achievement index will decrease by 0.093. So it can be said that if students have entrepreneurship while studying, the cumulative achievement index will decrease. From the results of the coefficient of determination test, it was found that the independent variable number, namely entrepreneurship, was 4.5%, which could explain/explain the dependent variable, namely achievement, or in other words, entrepreneurship influenced student achievement by 4.5%, while the remaining 95.5% was explained/explained by other factors. which was not researched
PENERAPAN DOUBLE EXPONENTIAL SMOOTHING UNTUK MEMPREDIKSI JUMLAH PENERIMAAN MAHASISWA BARU Maktisen Ena; Narita Y. Adrianingsih; Maryanes A. Malese
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 2 (2024): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v5i2.632

Abstract

This research aims to find out or predict the number of new students who will register for admission at the UNTRIB Kalabahi campus in 2024. The data collection technique used in this research is secondary data obtained from BAAK (Student Academic Administration Bureau) UNTRIB Kalabahi from 2007 until 2023 there are 17 data. The method used in this research is the Double Exponential Smoothing method from Brown to analyze the number of new students in 2024 based on new student data in 2007-2023 by testing using 9 alpha value parameters, namely 0.1 to 0.9 by looking at the Mean value The smallest Absolute Percentage Error (MAPE). The research results show that the smallest MAPE value is 6.35% with an alpha parameter value of 0.5. The estimated number of new student admissions in the 2024/2025 academic year is 590 people
Co-Authors Falentina L. Kamutlaka Maryanes A. Malese Narita Y. Adrianingsih