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All Journal Jurnal Teknologi Sistem Informasi dan Aplikasi JTPVI: Jurnal Teknologi dan Pendidikan Vokasi Indonesia
Taufiq, Ilham
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Automotive Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Industrial & Manufacturing Engineering Other

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Pengaruh Penerapan Media Pembelajaran CVT Berbasis Simulator terhadap Hasil Belajar Siswa di SMK N 2 Payakumbuh Taufiq, Ilham; Setiawan, M. Yasep; Sugiarto, Toto; Saputra, Hendra Dani
JTPVI: Jurnal Teknologi dan Pendidikan Vokasi Indonesia Vol. 2 No. 1 (2024): JTPVI: Jurnal Teknologi dan Pendidikan Vokasi Indonesia
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jtpvi.v2i1.148

Abstract

Model pembelajaran yang masih konvensional belum menjadi media yang efesien. Dengan menggunakan media pembelajaran menggunakan simulator bisa menarik perhatian peserta didik dalam pembelajara. Penelitian ini bertujuan untuk mengetahui Pengaruh penerapan Media Simulator terhadap hasil belajar siswa pada mata pelajaran Pemeliharaan SPT Sepeda Motor Jurusan Teknik Bisnis Sepeda Motor di SMK N 2 Payakumbuh. Jenis penelitian ini adalah penelitian eksperimen dengan populasi dalam sebanyak 34 siswa. Data dikumpulkan melalui tes, observasi dan dokumentasi. Yang diolah melalui SPSS V 20 dan microsoft excel. Hasil penelitian ini menunjukkan bahwa simulator berpengaruh signifikan terhadap hasil belajar siswa Jurusan TSM di SMK Negeri 2 Payakumbuh diterima yang dapat dilihat dari uji koefisien determinasi sebesar 0,568 dengan persentase 32,3 % yang artinya terdapat pengaruh yang kuat. Maka dapat dilihat semakin besar nilai variabel media simulator semakin besar pula nilai hasil belajar. Learning models that are still conventional have not become efficient media. By using learning media using simulators can attract the attention of students in learning. This study aims to determine the effect of the application of Simulator Media on student learning outcomes in Motorcycle SPT Maintenance subjects, Department of Motorcycle Business Engineering at SMK N 2 Payakumbuh. This type of research is experimental research with a population of 34 students. Data collected through tests, observation and documentation. Which is processed through SPSS V 20 and microsoft excel. The results of this study indicate that the simulator has a significant effect on the learning outcomes of TSM Department students at SMK Negeri 2 Payakumbuh, which can be seen from the determination coefficient test of 0.568 with a percentage of 32.3%, which means that there is a strong influence. So it can be seen that the greater the value of the simulator media variable, the greater the value of learning outcomes.
Model Optimasi Random Forest dengan PSO-CHI-SM dalam Mengatasi High Dimensional dan Imbalanced Data Banjir Kota Samarinda Taufiq, Ilham; Siswa, Taghfirul Azhima Yoga; Pranoto, Wawan Joko
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 7 No. 3 (2024): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v7i3.41632

Abstract

Flooding is a natural disaster that frequently affects our country. Samarinda City, in particular, continues to experience frequent flooding events with 18 incidents in 2018, 33 incidents in 2020, and 32 incidents in 2021. To predict flood disasters, it is necessary to utilize technology known as machine learning for analyzing and classifying floods. However, classification often encounters issues with high-dimensional data and class imbalance. This study aims to determine the extent to which the accuracy of flood disaster classification improves by using the Random Forest algorithm with PSO for optimization, Chi-Square feature selection, and SMOTE oversampling to balance classes. The data used in this study comprises flood data from 2021-2023 obtained from BMKG and BPBD Samarinda City, with a total of 1095 records and 11 attributes. The validation technique used is 5-fold cross-validation, and the evaluation uses a confusion matrix. The results of the Chi-Square feature selection identified Rainfall, Maximum Wind Direction, Most Frequent Wind Direction, Humidity, Sunshine Duration, and Wind Speed as the most influential features based on Chi-Square scores and P-values. The average accuracy obtained from the proposed classification model using 5-fold cross-validation reached 96.02%.
Co-Authors Hendra Dani Saputra M. Yasep Setiawan Sugiarto, Toto Tagfirul Azima Yoga Siswa, Muspidar Mulyadi Wawan Joko Pranoto