Edukasi Postur Tubuh Ergonomi Untuk Mencegah Frozen Shoulder Pada Guru di SMP
DOI:
https://doi.org/10.62354/healthcare.v3i1.103Keywords:
frozen shoulder, postur tubuh ergonomi, terapi latihanAbstract
Ergonomi merupakan ilmu yang mempelajarikarakteristik tubuh manusia dalam merancang produk, fasilitas, dan sistem kerja guna menciptakan kualitas kerja yang optimal. ilmu ini bertujuan untuk memastikan kesehatan, keselamatan, dan tetap terjaga selama bekerja. dalam penerapannya ergonomimengatur aktivitas manusia agar lingkungan kerja menjadi nyaman. kegiatan pengabdian kepada masyarakat ini diselenggarakan di SMP Negeri 20 Buru, Maluku dengan melibatkan 2o partisipan. metode yang digunakan adalah service learning, dengan evaluasi ketercapaian melalui pre-test dan post-test. evaluasi ini mencangkup, beberapa indikator seperti definisi postur tubuh ergonomis, definisi frozen shoulder, tanda dan gejala, serta rehabilitasinya. hasil pre-test menunjukkan tingkat pemahaman sebesar 5% hingga 15% sementara hasil post-test meningkat hingga 95%. dengan demikian kegiatan ini berhasil meningkatkan pengetahuan partisipan.
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[1] J. Ahmad, A. ul Hasan, T. Naqvi, and T. Mubeen, “A Review on Software Testing and Its Methodology,” Manag. J. Softw. Eng., vol. 13, no. 1, pp. 32–38, 2019, doi: 10.26634/jse.13.3.15515.
[2] E. A. Shams and A. Rizaner, “A novel support vector machine based intrusion detection system for mobile ad hoc networks,” Wirel. Networks, vol. 24, no. 5, pp. 1821–1829, 2018, doi: 10.1007/s11276-016-1439-0.
[3] S. Aljawarneh, M. Aldwairi, and M. B. Yassein, “Anomaly-based intrusion detection system through feature selection analysis and building hybrid efficient model,” J. Comput. Sci., vol. 25, no. 1, pp. 152–160, 2018, doi: 10.1016/j.jocs.2017.03.006.
[4] Y. I. Kurniawan, A. Rahmawati, N. Chasanah, and A. Hanifa, “Application for determining the modality preference of student learning,” in Journal of Physics: Conference Series, 2019, vol. 1367, no. 1, pp. 1–11, doi: 10.1088/1742-6596/1367/1/012011.
[5] Y. Guo, S. Han, Y. Li, C. Zhang, and Y. Bai, “K-Nearest Neighbor combined with guided filter for hyperspectral image classification,” in International Conference On Identification, Information and Knowledge in the Internet of Things, 2018, pp. 159–165.
[6] Y. I. Kurniawan, E. Soviana, and I. Yuliana, “Merging Pearson Correlation and TAN-ELR algorithm in recommender system,” in AIP Conference Proceedings, 2018, vol. 1977, doi: 10.1063/1.5042998.
[7] M. Sridevi, S. Aishwarya, A. Nidheesha, and D. Bokadia, Anomaly Detection by Using CFS Subsets and Neural Network with WEKA Tools. Springer Singapore.
[8] C. Low, “NSL-KDD Dataset,” 2015. https://github.com/defcom17/NSL_KDD (accessed Sep. 13, 2019).
[9] D. Handoko, “Sistem Pendukung Keputusan Seleksi Penentuan Penerima Beasiswa Dengan Metode Simple Additive Weighting (SAW),” Universitas Muhammadiyah Surakarta, 2016.
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