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All Journal Jurnal Sains Matematika dan Statistika AKSIOMA JURNAL EKSAKTA PENDIDIKAN (JEP) Pelita Eksakta Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Journal of Mathematics UNP Rangkiang Mathematics Journal Jurnal Edukasi dan Penelitian Matematika
Defri Ahmad
Universitas Negeri Padang
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Education Mathematics Physics Other

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IMPLEMENTASI FUZZY TIME SERIES LOGIKA LEE UNTUK PERAMALAN INFLASI DI INDONESIA Aulia Fitri Fireza; Defri Ahmad
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.v4i2.386

Abstract

Inflation is a process of continuous increase in the price of goods or an economic situation that shows a tendency to increase the price level in general. One way to control inflation is to use forecasting. Forecasting is an activity to predict future events. Related to forecasting, the method that can be used in forecasting inflation time series data in Indonesia is the fuzzy time series method of Lee's logic. This study aims to apply Lee's Fuzzy Time Series method in forecasting inflation in Indonesia in the period January 2014 to December 2022. The forecasting results of the method are then measured using MAE and MAPE. In this study, the results of inflation forecasting in Indonesia follow the pattern of actual data. Meanwhile, the forecasting accuracy value obtained a MAE value of 0.0043 and a MAPE value of 11.7%, so that inflation forecasting in Indonesia using the Fuzzy Time Series Lee method based on MAPE criteria is good
ALGORITMA K-NEAREST NEIGHBOR TERHADAP PELUANG MAHASISWA MENJADI AKTIVIS KAMPUS PADA JURUSAN MATEMATIKA UNIVERSITAS NEGERI PADANG Muhammad Fadhli Gusvino; Defri Ahmad
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.v4i2.401

Abstract

The purpose of this study was to predict whether mathematics students at Padang State University have the opportunity to become campus activists using the K-Nearest Neighbor Algorithm (KNN). This research will be used as a benchmark to calculate how many mathematics students can become activists at Padang State University. The K-Nearest Neighbor Algorithm (KNN) is a machine learning algorithm that has resistance to training data where there is a lot of noise and is more effective for large data. The K-Nearest Neighbor Algorithm itself is a distance-based data classification process for determining the closeness between different data. become the closest neighbor data and choose a class or category based on the K category of nearest neighbors. In this research, for the first step, data was collected on mathematics students based on several factors that influenced them to become activists, and an analysis of finding distance using the Euclidean distance was carried out. 46% are not activists
ANALISIS HASIL PREDIKSI MAGNITUDO GEMPA DI WILAYAH KOTA PADANG MENGGUNAKAN TEKNIK RANDOM FOREST Ade Fauzan; Defri Ahmad
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.v4i3.450

Abstract

The topic of earthquake prediction is an interesting one to research. As one of the natural disasters, earthquakes are included in natural disasters that can cause considerable damage. The damage caused not only affects the economy but also the life of an area. Several studies on earthquake prediction have been conducted so far, one of which is Machine Learning and using the Random forest method. The purpose of the research is to determine the analysis of earthquake magnitude prediction results in the Padang City area using machine learning techniques. The variables used in this study are time, latitude, longitude, and magnitude. Earthquake data is obtained from the United States Geological Survey (USGS) website. This research produces an RMSE value of 0.31758 and an MSE value of 0.10085
ANALISIS PEMAHAMAN MAHASISWA TERHADAP PEMBUKTIAN PERNYATAAN MATEMATIIKA PADA TOPIK GRUP DENGAN MODUL BERBASIS LOGIKA PEMBUKTIAN Defri Ahmad; Fridgo Tasman
Jurnal Edukasi dan Penelitian Matematika Vol 9, No 4 (2020): Desember 2020
Publisher : Departemen Matematika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/pmat.v9i4.11083

Abstract

Abstract- Proving mathematics statement is one of important ability for undergraduate student to learn mathematics, especially in learning abstract algebra, real analysis, linear algebra, etc. More than a half of topic in group need proving ability to be mastered. In this article, students’ understanding on proving some statement related to group (abstract algebra) that has been help by using proof reasoning module is examined. Data of student responses are collected using three item test and interview. Based on the result student ability in starting answer and create proving structure has been improved. But students’ overall score still satisfied because they fail on choose some basic concept like theorem or definition to help them in proof. Keyword- Proof Reasoning, Group, Proof Technique, Statement Type
Co-Authors Abdillah Janaki Daosti Ade Fauzan Amellia Fadjri annisa yovinda Aulia Fitri Fireza Defrisa Yoga Putra Deva Eliza Dina Fitria Fadhilah Fitri Fridgo Tasman Hafis Alrizal Indiko Prima Kefiano Fangelis Melisa Melisa Mella Susriyanti Meria Ultra Gusteti Muhammad Fadhli Gusvino Muhammad Subhan Nurul Hikmah Rara Sandy Winanda Rara Shandy Winanda Rida arifi Ronal Rifandi Saddam Al Aziz Suherman Suherman Tesa Nofri Handayani Ultari Femi Arshinta Wella Kurnia windi jelita Yani Sriyanti