Article Per Year (5 Year)
p-Index From 2021 - 2026
1.554
P-Index
This Author published in this journals
All Journal Jurnal Penelitian Fisika dan Aplikasinya (JPFA) Jurnal Teknologi Informasi dan Ilmu Komputer JURNAL KEPERAWATAN SEHAT Indonesian Review of Physics (IRiP) EduMatika: Jurnal MIPA Jurnal Pembelajaran Fisika Journal of Novel Engineering Science and Technology Buletin Edukasi Indonesia Jurnal Penelitian Pembelajaran Fisika Advances in Psychological Sciences and Applications
PRASETYO, ERWIN
Unknown Affiliation
Religion Humanities Astronomy Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Neuroscience Nursing Physics Social Sciences Other

Published : 13 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 13 Documents
Search

 1   2 
DEVELOPMENT OF PHYSICS MAGAZINE LEARNING MEDIA BASED ON ETHNOSCIENCE TO IMPROVE SCIENCE LITERACY IN JUNIOR HIGH SCHOOL STUDENTS najila; Alfarizi, Zakaria; Prasetyo, Erwin
JURNAL PEMBELAJARAN FISIKA Vol. 14 No. 3 (2025): Jurnal Pembelajaran Fisika (JPF) Universitas Jember
Publisher : Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/jpf.v14i3.53709

Abstract

The low scientific literacy of junior high school students is caused by the lack of interesting and contextual learning media. This study aims to develop an ethnoscience-based physics magazine as a learning media integrated with local culture. The method used is Research and Development (R&D) with the ADDIE model. Validation was carried out by media and material experts with very good and good results. The magazine was implemented in class VIII MTs At-Taqwa Beru. The results of the pretest and posttest showed a significant increase, from an average of 43.25 to 70, with a significance value of 0.000 and an effect size of 1.68. As many as 75% of students achieved the KKM. The output of this study is an ethnoscience-based physics magazine product that effectively improves students' scientific literacy through a local cultural approach.
Peningkatan Akurasi Klasifikasi Algoritma C 4.5 Menggunakan Teknik Bagging pada Diagnosis Penyakit Jantung Prasetyo, Erwin; Prasetiyo, Budi
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 5: Oktober 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2020752379

Abstract

Perkembangan teknologi yang begitu pesat menjadikan kebutuhan akan suatu informasi semakin meningkat, sehingga keakuratan suatu informasi menjadi suatu hal yang sangat penting, Terutama keakuratan informasi yang dibutuhkan dalam memprediksi penyakit dalam bidang medis. Dalam proses pengumpulan suatu informasi dibutuhkan metode tertentu, sehingga informasi yang telah diproses menjadi sebuah pengetahuan menggunakan suatu metode tertentu disebut dengan penambangan data atau istilah lainnya adalah data mining. Umumnya data mining digunakan untuk memprediksi suatu penyakit yang bersumber dari data rekam medis pasien, khususnya penyakit jantung. Data penyakit jantung diambil dari dataset UCI Machine Learning Repository. Tujuan dari penulis melakukan penelitian ini yaitu untuk mengetahui penerapan teknik bagging pada algoritma C4.5, mengetahui hasil akurasi dalam algoritma C4.5, dan membandingkan tingkat akurasi dari penerapan teknik bagging pada algoritma C4.5. Dataset yang diklasifikasikan dengan algoritma C4.5 memperoleh akurasi sebesar 72,98%. Hasil akurasi ini dapat ditingkatkan dengan menerapkan teknik bagging menghasilkan akurasi sebesar 81,84%, sehingga terjadi peningkatan akurasi sebesar 8,86%  dari penerapan teknik bagging pada Algoritma C4.5. AbstractThe quick development of technology makes the need for information increase, so that the accuracy of the information becomes a very important thing, especially the accuracy of the information needed in predicting diseases in the medical field. In the process of gathering information certain methods are needed, so information that has been processed into knowledge using a certain method is called data mining or other terms is data mining. Data mining is generally used to predict a disease originating from patient medical record data, especially heart disease. Heart disease data is taken from the UCI Machine Learning Repository dataset. The purpose of the authors conducting this research is to determine the application of bagging techniques on the C4.5 algorithm, determine the accuracy of the results in the C4.5 algorithm, and compare the level of accuracy of the application of bagging techniques on the C4.5 algorithm. The dataset classified by the C4.5 algorithm obtained an accuracy of 72.98%. The results of this accuracy can be improved by applying bagging techniques resulting in an accuracy of 81.84%, resulting in an increase in accuracy of 8.86% from the application of bagging techniques in the C4.5 Algorithm.
The Application of STEM Education Approach in Inquiry-Based Physics Learning with Contextualization of Local Wisdom to Improve Science Process Skills Prasetyo, Erwin; Rusdin, Muhamad Epi; Sina, Tuti Asmiranti; Sulisworo, Dwi; Al Farizi, Zakaria; Iftitah, Nur
Indonesian Review of Physics Vol. 7 No. 2 (2024)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/irip.v7i2.12433

Abstract

Education in Indonesia, particularly in eastern regions, faces significant challenges in preparing students to meet the demands of the 21st century. Conventional teaching methods often fail to effectively enhance science process skills, which are critical in the era of Industrial Revolution 4.0 and Society 5.0. This study aims to examine the effectiveness of a STEM Education approach combined with inquiry-based learning and the contextualization of local wisdom in improving students' science process skills. The research employed a quasi-experimental method with a pretest-posttest control group design. The subjects were students from four schools in Lembata Regency, namely SMA N Lebatukan, SMA N 1 Nubatukan, SMA N 2 Nubatukan, and MAN Lembata, East Nusa Tenggara, selected using purposive sampling. Data were analyzed using t-tests to evaluate significant differences between the two groups and effect size analysis to measure the impact of the treatment. The results showed a significant improvement in science process skills in the experimental group compared to the control group (p < 0.0001). The highest average score was achieved by SMA N Lebatukan (59.46), while MAN Lembata recorded the lowest average score (50.9). These findings confirm that integrating STEM, inquiry, and local wisdom effectively enhances scientific skills and the relevance of learning for students.
Co-Authors Adi Jufriansah Ahdiany, Dian Al Farizi, Zakaria Alfarizi, Zakaria Anwar, Zaina Arief Hermanto Azmi Khusnani Bogar, Dominika Yonavista Budi Jatmiko Budi Prasetiyo, Budi Donuata, Pujianti Bejahida Farizi, Zakaria Al Fitri, Mohamad Iftitah, Nur Lasiyati Yuswo Yani Moh. Toifur najila Nurfadilah Nuwa, Gisela Pujianti Bejahida Donuata Rajak, Faysal Rusdin, Muhamad Epi Rusdin, Muhammad Epi Sina, Tuti Asmiranti Syarif, Ratih Ulfah R Wahyuningsih Wahyuningsih Wahyuningsih