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All Journal Katalogis JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL PENDIDIKAN TAMBUSAI Jurnal Pengabdian UNDIKMA
Agus, Muh.
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Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Nursing Public Health Social Sciences Other

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PENGARUH GAYA KEPEMIMPINAN TRANSFORMASIONAL, KOMPENSASI DAN MOTIVASI TERHADAP KINERJA PEGAWAI PADA KANTOR KESYAHBANDARAN DAN OTORITAS PELABUHAN PANTOLOAN Agus, Muh.
Katalogis Vol 5, No 7 (2017)
Publisher : Katalogis

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (370.232 KB)

Abstract

The objective of this study is to determine the influence of transformational leadership style, compensation and motivation on the  performance of officials in the maritime and port authority office of pantoloan.this study uses explanatory approach in explaining the relationship between variables by involving 70 officials in the maritim and port authority office as respondents, who were selected through census method. The result of the tests shows that: 1) transformational leadership, compensation and motivation simultaneously have  significant influence on on the officials ‘performance; 2) transformational leadership style is partially has positive and  significant influence  on the officials‘performance; 3) compensation partially has positive and significant influencet on the officials‘performance; 4) motivation partially has positive and significant influence on the office ‘performance.
Efektivitas Media Pembelajaran Fisika Berbasis TikTok terhadap Hasil Belajar Peserta Didik Kelas XI SMA Negeri 8 Takalar Agus, Muh.; Jusman, Jusman; Suarti, Suarti; Hamansah, Hamansah; Sudirman, Sudirman
Jurnal Pendidikan Tambusai Vol. 9 No. 2 (2025): Agustus
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jptam.v9i2.30826

Abstract

Penelitian ini bertujuan menganalisis efektivitas media pembelajaran fisika berbasis TikTok dan PowerPoint terhadap hasil belajar peserta didik kelas XI SMA Negeri 8 Takalar. Latar belakangnya adalah rendahnya hasil belajar fisika akibat metode konvensional dan tingginya penggunaan TikTok oleh siswa. Menggunakan pendekatan kuantitatif dengan desain eksperimen kuasi ("The Matching Only Pretest-Posttest Control Group Design"), penelitian melibatkan populasi 62 siswa kelas XI MIPA dan sampel 25 pasang siswa yang dicocokkan dari kelas XI MIPA 1 dan XI MIPA 2. Instrumen yang digunakan adalah tes hasil belajar fisika pilihan ganda. Analisis data meliputi deskriptif (N-Gain) dan inferensial (uji normalitas, homogenitas, dan Independent Samples T-test). Hasil menunjukkan bahwa media PowerPoint "tidak efektif" (N-Gain rata-rata 18.34%), sedangkan media TikTok "kurang efektif" (N-Gain rata-rata 48.08%). Meskipun demikian, terdapat perbedaan efektivitas yang signifikan (p < 0.05) antara kedua media, dengan TikTok menunjukkan peningkatan hasil belajar yang lebih baik. Disimpulkan bahwa media TikTok lebih efektif dibandingkan PowerPoint, namun pengembangan pedagogis dan teknis lebih lanjut, serta strategi pendampingan yang tepat, masih diperlukan untuk optimalisasi
Pelatihan MIT App Inventor sebagai Upaya Meningkatkan Kemampuan Berpikir Logis Siswa SMAN 4 Parepare Maharani, Putri Ayu; Gunadin, Indar Chaerah; Intizhami, Naili Suri; Nuranti, Eka Qadri; Rafrin, Mardhiyyah; Agus, Muh.; Iskandar, M. Fauzan; Yunus, Sitti Rahma; Al-Fauzi S., Muhammad Faruq; Tunru, Muh. Abubakar
Jurnal Pengabdian UNDIKMA Vol. 5 No. 1 (2024): February
Publisher : LPPM Universitas Pendidikan Mandalika (UNDIKMA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/jpu.v5i1.9786

Abstract

This community service activity aims to improve the logical thinking abilities of SMAN 4 Parepare students by teaching the application of mathematical logic in compiling computer instructions based on MIT App Inventor. The method for implementing this service was problem-based learning training by taking the example of the traditional game of rock-paper-scissors as a learning case. Next, create a rock-paper-scissors game program using MIT App Inventor as a student learning experience in applying mathematical logic concepts. The evaluation instrument employed was a questionnaire to collect pre-test and post-test results, which were then analyzed using descriptive statistics and paired sample t-tests. The results of this service showed an increase in the average participant score on the post-test results, where the average pre-test score was 7.24 out of 15, while the average post-test score was 9.17 out of 15.
Integration of YOLOv8 and IoT-Based LiDAR Sensors on Drones for Deforestation Area Detection and Reforestation Mapping Agus, Muh.; Maharani, Putri Ayu; Marka M, Ilham Ali; Al-Fadillah, Muhammad Aslam
Journal of Applied Informatics and Computing Vol. 10 No. 3 (2026): June 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i3.11778

Abstract

Deforestation has caused significant ecosystem degradation and increased the need for more accurate and efficient monitoring systems and reforestation planning. This study develops an integrated system combining YOLOv8 and Internet of Things (IoT)-based LiDAR sensors on a drone platform to detect deforested areas and generate 3D mapping to support reforestation efforts. The dataset consists of 1,822 aerial images collected from public datasets and drone-mounted cameras under various lighting conditions and flight altitudes. The YOLOv8 model was trained using transfer learning with an input size of 640 × 640, a batch size of 16, a learning rate of 0.001, and 100 training epochs. The results demonstrate that the model achieved a precision of 93%, a recall of 90%, and an mAP@0.5 of 94%, while successfully performing real-time deforestation area detection on the drone platform. Integration with the LiDAR sensor produced 3D point cloud visualizations with mapping deviations of less than 2 meters. The developed system effectively supports the identification of priority areas for reforestation more rapidly, accurately, and efficiently than conventional manual survey methods.
Co-Authors Al-Fadillah, Muhammad Aslam Al-Fauzi S., Muhammad Faruq Baehaqi Eka Qadri Nuranti Gunadin, Indar Chaerah Hamansah Iskandar, M. Fauzan Maharani, Putri Ayu Marka M, Ilham Ali Naili Suri Intizhami Rafrin, Mardhiyyah Suarti, Suarti Sudirman Sudirman Tunru, Muh. Abubakar Yunus, Sitti Rahma