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All Journal Jurnal Kumparan Fisika Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Pengabdian Kepada Masyarakat
Gultom, Fades Br
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Economics, Econometrics & Finance Education Health Professions Industrial & Manufacturing Engineering Physics Social Sciences

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PENGENALAN AKTIVITAS SAINS SERU BAGI SISWA-SISWI SD IT INSAN INTANI KOTA BENGKULU Insani, Luthfi Cahya; Fadhila, Ahmad Dhimas; Maulinda, Siti Meylan; Khoiriyah, Putri; Gultom, Fades Br; Haryanto, Hery
JURNAL PENGABDIAN KEPADA MASYARAKAT Vol. 5 No. 2 (2025): Jurnal Pengabdian kepada Masyarakat
Publisher : LPPM Universitas Kahuripan Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51158/962x1f66

Abstract

Kegiatan pengabdian ini bertujuan untuk meningkatkan minat dan pemahaman siswa terhadap sains melalui eksperimen sederhana yang interaktif di SD IT Insan Intani, Kota Bengkulu. Metode pelaksanaan mencakup penyampaian materi, demonstrasi eksperimen (tiga warna ajaib, balon mengembang tanpa ditiup, dan ilustrasi gunung meletus), serta keterlibatan aktif siswa dalam pelaksanaannya. Hasil kegiatan menunjukkan antusiasme dan partisipasi tinggi dari siswa, serta respons positif dari guru yang menilai kegiatan ini mendukung proses pembelajaran tematik. Kegiatan ini memberikan dampak positif dalam memperkuat fondasi pembelajaran sains yang menyenangkan dan berbasis pengalaman langsung di tingkat sekolah dasar.
Pelatihan Praktikum IPA Inovatif Berbasis Chemlab bagi Siswa dan Guru IPA SMP Uliyandari, Mellyta Mellyta; Sutarno, Sutarno Sutarno; Gultom, Fades Br
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 8, No 3 (2025): SEPTEMBER 2025
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v8i3.3117

Abstract

SMP Plus Ja-Alhaq Bengkulu is one of the private junior high schools in Bengkulu City that does not yet have adequate laboratory facilities. One solution to this problem is conducting virtual practicum using the chemlab application. The advantage of learning with chemlab is its practicality and ease of use, as well as the fact that it does not require many expensive tools and materials as in a real laboratory. This community service aimed to provide innovative science practicum training based on chemlab for students and science teachers at SMP Plus Ja-Alhaq. The program was carried out using the Technical Assistance Model in the form of training and mentoring activities. The training focused on explaining how to use the chemlab application, its features, and its functions, while the mentoring involved hands-on practice of applying chemlab in science practicum. The results of this activity showed that both students and teachers were able to use chemlab as a practicum medium to conduct science experiments virtually, thereby enhancing students’ motivation and learning outcomes.
EVALUASI KINERJA BERBAGAI JENIS SENSOR LDR SEBAGAI LUXMETER MELALUI KALIBRASI REGRESI EKSPONENSIAL DAN POWER Heriansyah, Heriansyah; Gultom, Fades Br
Jurnal Kumparan Fisika Vol. 8 No. 3: Desember 2025
Publisher : Unib Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jkf.8.3.87-94

Abstract

This study aims to evaluate the performance of various types of Light Dependent Resistor (LDR) sensors as alternative luxmeters based on Arduino using exponential and power regression calibration methods. Four LDR types—GL5506, GL5528, GL5537, and GL5539—were tested under controlled lighting conditions using a dimmable smart bulb with light intensity variations from 5% to 100%. A commercial GM1030C luxmeter was used as the calibration reference. The measured data were analyzed using statistical parameters, including the coefficient of determination (R²), root mean square error (RMSE), mean absolute error (MAE), and mean percentage error, to determine the accuracy and stability of each sensor. The results show that all sensor types achieved R² values ranging from 0.9772 to 0.9992, indicating that both regression models effectively represent the nonlinear relationship between sensor output and actual light intensity. The GL5506 sensor exhibited the best accuracy with R² = 0.9962, RMSE = 13.13 lux, MAE = 11.1 lux, and an average error of 2.89% using the power regression model. The power regression model performed better for sensors with fast and linear responses (GL5506 and GL5528), while the exponential regression model was more suitable for sensors with gradual nonlinear responses (GL5537 and GL5539). With overall errors below 7%, all LDR sensors tested are suitable for use as economical and reliable Arduino-based luxmeters for educational and basic research applications.
Co-Authors Fadhila, Ahmad Dhimas Heriansyah Hery Haryanto Insani, Luthfi Cahya Khoiriyah, Putri Maulinda, Siti Meylan Sutarno, Sutarno Sutarno Uliyandari, Mellyta Mellyta