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All Journal BIOCHEPHY: Journal of Science Education Journal of Novel Engineering Science and Technology Jurnal Pendidikan MIPA
Arifin, Anggun Syafira
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Environmental Science Mechanical Engineering

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MENINGKATKAN MINAT DAN MOTIVASI BELAJAR SISWA KELAS 12 MELALUI INTEGRASI AI DAN IoT DALAM PEMBELAJARAN TEKNOLOGI DIGITAL DI ERA KURIKULUM MERDEKA Arifin, Anggun Syafira; Al Farizi, Zakaria; Nurfadilah; Karanggulimo, Yohana; Maria, Eko Goran; Akhrajal; Alip, Isma; Fitriani, Nadya
BIOCHEPHY: Journal of Science Education Vol. 4 No. 2 (2024)
Publisher : MO.RI Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52562/biochephy.v4i2.1358

Abstract

Penelitian ini bertujuan untuk mengevaluasi efektivitas integrasi teknologi Artificial Intelligence AI dan IoT dalam meningkatkan minat dan motivasi belajar siswa kelas 12 pada pembelajaran teknologi digital di era Kurikulum Merdeka. Metode yang digunakan adalah kuasi-eksperimen dengan pendekatan PjBL yang diterapkan di tiga sekolah di NTT, yaitu SMA Negeri 1 Wolowaru, SMA Negeri 1 Maumere, dan SMAN Buyasari. Penelitian ini menggunakan instrumen kuesioner skala Likert untuk mengukur minat dan motivasi siswa sebelum dan sesudah intervensi. Hasil penelitian menunjukkan bahwa integrasi AI dan IoT secara signifikan meningkatkan keterlibatan dan kepercayaan diri siswa dalam mempelajari materi teknologi digital, dengan SMA Negeri 1 Wolowaru mencatat performa tertinggi di antara ketiga sekolah. Peningkatan ini diindikasikan oleh peningkatan nilai rata-rata pada indikator minat dan motivasi, serta distribusi nilai yang lebih merata pada rentang tinggi. Penelitian ini menawarkan solusi baru dalam pembelajaran berbasis teknologi yang relevan dengan dunia nyata, berbeda dari metode konvensional yang sering kurang menarik bagi siswa. Kesimpulannya, penerapan AI dan IoT dalam pembelajaran berbasis proyek dapat meningkatkan minat dan motivasi siswa, tetapi penelitian lebih lanjut diperlukan untuk memperluas cakupan studi dan mengatasi keterbatasan seperti variasi infrastruktur dan pelatihan guru. Penelitian ini memberikan kontribusi terhadap peningkatan kualitas pendidikan teknologi di Indonesia dan relevansi pembelajaran dengan tantangan di era digital.
Experimental Study of Gravity Measurement with a Video-Based Laboratory Pendulum with Tracker Software: Comparison of Weighted and Unweighted Tests Wahab, Dedi Suwandi; Hamsa, Berlian; Sina , Tuti Asmianti; Deti, Maria; Anwar, Zaina; Arifin, Anggun Syafira; Nursilawati, Wingki; Servia; Jaudin, Santi Hasan; Jufriansah, Adi
Journal of Novel Engineering Science and Technology Vol. 4 No. 01 (2025): Journal of Novel Engineering Science and Technology
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/jnest.v4i01.644

Abstract

This research aims to determine the value of the Earth's gravitational acceleration (g) using the mathematical pendulum swing method with an unweighted linear regression approach, weighted linear regression, and the 4th-order Runge-Kutta numerical method. The data used are the results of measuring the swing period of the pendulum for various lengths of string. The analysis was carried out by calculating the average value of gravitational acceleration using multiple methods. The results show that weighted linear regression provides more consistent and accurate estimates than unweighted linear regression, with a high coefficient of determination (R²) value. The Runge-Kutta numerical method is also used to predict swing periods with a more in-depth mathematical approach, producing values ​​supporting experimental data trends. Overall, this research makes an average value of gravitational acceleration of around 9.11 m/s², close to the expected theoretical value. These findings show that the mathematical pendulum swing method can be used effectively to measure the Earth's gravitational acceleration with sufficient accuracy and provide an essential contribution in the context of physics education regarding the application of basic principles in physics experiments.
Optimizing Students' HOTS Skills through AI and IoT Integration in Digital Technology Learning Farizi, Zakaria Al; Nurfadilah, Nurfadilah; Arifin, Anggun Syafira; Fitriani, Nadya
Jurnal Pendidikan MIPA Vol 25, No 4 (2024): Jurnal Pendidikan MIPA
Publisher : FKIP Universitas Lampung

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Abstract

Higher-order thinking skills (HOTS) are essential for students to face increasingly complex global challenges. However, results from the Programme for International Student Assessment (PISA) indicate that these skills among Indonesian students remain low. This study aims to address this limitation by integrating Artificial Intelligence (AI) and Internet of Things (IoT) technologies into learning, specifically to enhance students' HOTS within the framework of the Kurikulum Merdeka. This research employs a quasi-experimental method with a one-group pretest-posttest design, involving three schools in East Nusa Tenggara as the sample. Data on students' HOTS were collected before and after the AI and IoT-based learning intervention and analyzed using paired sample T-tests and N-Gain to assess the significance and effectiveness of the improvement. The results show a significant increase in students' HOTS scores across all three schools, with p < 0.001 in paired sample T-tests and an average N-Gain score in the medium category. These findings suggest that AI and IoT-based learning can improve students' critical and analytical thinking skills. Implementing technology within the Kurikulum Merdeka offers relevant and promising benefits in preparing students to face future knowledge dynamics. This study contributes to the literature on technology-based education in Indonesia, with the hope that broader technology integration will accelerate the enhancement of national education quality.        Keywords: higher-order thinking skills, artificial intelligence, internet of things, kurikulum merdeka, technology-based learning.DOI: http://dx.doi.org/10.23960/jpmipa/v25i4.pp1719-1737
Co-Authors Adi Jufriansah Akhrajal Al Farizi, Zakaria Alip, Isma Anwar, Zaina Deti, Maria Farizi, Zakaria Al Fitriani, Nadya Hamsa, Berlian Jaudin, Santi Hasan Karanggulimo, Yohana Maria, Eko Goran Nurfadilah Nurfadilah Nurfadilah Nursilawati, Wingki Servia Sina , Tuti Asmianti Wahab, Dedi Suwandi