Pengembangan Keterampilan Mekatronika Siswa SMK Puger melalui Proyek ROV
DOI:
https://doi.org/10.51278/bce.v5i2.1775Keywords:
Mechatronics, Vocational High School, ROV, Project-Based Learning, Industry 4.0Abstract
Mastery of mechatronics skills is a key factor in enhancing the competitiveness of vocational high school (SMK) graduates, especially in the era of Industry 4.0. This study aims to develop the mechatronics skills of SMK Puger students through a Remotely Operated Vehicle (ROV) project. The method used in this research is a project-based learning approach, involving the design, assembly, and testing of the ROV directly by students. The results show that the implementation of this project improves students' understanding of electrical systems, microcontroller programming, and mechanical assembly skills. Furthermore, this project also enhances teamwork and problem-solving skills. Thus, the development of mechatronics skills through the ROV project can be an effective alternative in improving the quality of learning in vocational schools. This research makes several significant contributions to vocational education, particularly in enhancing students’ mechatronics competencies through a practical and innovative learning model. These findings suggest that integrating PjBL and technological innovation in vocational education is a viable and impactful method to enhance student learning outcomes and workforce readiness
References
Anfasa, I. and Sutrisno, I. (2021). RANCANG BANGUN INTEGRASI SCADA PADA SISTEM CRUSHING DAN BARGE LOADING CONVEYOR. Jurnal Conference on Automation Engineering and Its Application.
Danis B, Agus K, Projek P, Mohammad B, and Sutrisno, I. (2019). Ball Direction Prediction for Wheeled Soccer Robot Goalkeeper Using Trigonometry Technique. Applied Technology and Computing Science Journal.
Budianto, I. et al (2020). Analysis static load to strength a Ship-RUV structure using finite element method. IOP Conf. Series: Materials Science and Engineering 1175 (2021) 012017.
Hakim, A. S., & Munaf, R. (2019). Analysis of Speedboat Accidents in Waters of Tanjung Benoa, Bali, Indonesia. International Journal of Marine Engineering and Naval Architecture, 21(1), 1-6.
Hananur, R. N. and Sutrisno, I. (2018). Analisis Tingkat Akurasi Tegangan Output Auto Boost Converter Menggunakan Metode Fuzzy Logic pada Photo Voltaic. Seminar MASTER PPNS.
Hasugian, S., Rahmawati, M. and Sutrisno, I. (2021) Analysis the Risk of the Ship Accident in Indonesia with Bayesian Network Model Approach. Annals of R.S.C.B., ISSN:1583-6258, Vol. 25, Issue 2, Pages. 3341 - 3356
Hayati, N. F., & Munaf, R. (2018). Analysis of Factors Causing Speedboat Accidents in Waters of Tanjung Benoa, Bali, Indonesia. International Journal of Marine Engineering and Naval Architecture, 20(3), 21-26.
Iskandar, Dewa, P., and Sutrisno, I. (2022). Prototype of Bridge Navigational Watch Alarm System Equipped Obstacle Warning System Based on Image Processing and Real-Time Tracking. International journal of Marine Engineering and Research. Volume 7. No 1.
Jami’in, M. A., Sutrisno, I., and Hu, J. (2015). The State-Dynamic-Error-Based Switching Control under Quasi-ARX Neural Network Model. AROB 20th B-Con Plaza, Beppu, Japan
Jami’in, M. A., Sutrisno, I., and Hu, J. (2014). Nonlinear Adaptive Control for Wind Energy Conversion Systems Based on Quasi-ARX Neural Network Model. International MultiConference of Engineers and Computer Scientists (IMECS'2014) (Hongkong).
Khumaidi, A. et al (2018). Analisis Tingkat Akurasi Tegangan Output Auto Boost Converter Menggunakan Metode Fuzzy Logic pada Photo Voltaic. Seminar MASTER PPNS.
Kurniawan, A., & Munaf, R. (2017). Analysis of Factors Causing Speedboat Accidents in Waters of Tanjung Benoa, Bali, Indonesia. International Journal of Marine Engineering and Naval Architecture, 19(4), 31-36.
Mohammad B, Sutrisno, I., Budianto, Santosa, A. W. B., and Nofandi, F (2020). Vibration Analysis of Ship-RUV Structure in Operational Conditions. IOP Conf. Series: Earth and Environmental Science 519 012045
Munaf, R., & Handayani, H. F. (2016). Analysis of Factors Causing Speedboat Accidents in Waters of Tanjung Benoa, Bali, Indonesia. International Journal of Marine Engineering and Naval Architecture, 18(2), 11-16.
Nofandi, F., Devandra, RH., Hasugian, S., Sutrisno, I., Setiawan. E. Design floating robot of shallots irrigation with GPS based and using the waypoint navigation method. IOP Conference Series: Materials Science and Engineering
Rifai, M., et al (2021). Dynamic time distribution system monitoring on traffic light using image processing and convolutional neural network method. IOP Conf. Series: Materials Science and Engineering 1175.
Santosa, AWB., Hardianti, A., Hasugian, S., Sutrisno, I., Khumaidi, A. (2021). Safe distance reminder system on ship against port for the standing process using image processing. IOP Conference Series: Materials Science and Engineering.
Sutrisno, I. (2020). Vibration Analysis of Ship-RUV Structure in Operational. International Conference Earth Science & Energy
Sutrisno, M. and Muhammad F, dkk, (2019). Implementation of Backpropagation Neural Network and Extreme Learning Machine of pH Neutralization Prototype. IOP Conf. Series: Journal of Physics: Conf. Series 1196 012048
Sutrisno, I. (2009). Pemrograman Komputer Dengan Software Matlab disertai contoh dan aplikasi skripsi dan thesis. ITS Press.
Sutrisno, I., et al (2013). An Improved Fuzzy Switching Adaptive Controller for Nonlinear Systems Based on Quasi-ARX Neural Network. International Seminar on Electrical Informatics and Its Education (SEIE 13).
Sutrisno, I. et al (2013). Implementation of Lyapunov Learning Algorithm for Fuzzy Switching Adaptive Controller Modeled Under Quasi-ARX Neural Network. Inter. Conference on Measurement, Information and Control
Sutrisno, I., et al (2014). Nonlinear Model-Predictive Control Based on Quasi-ARX Radial-Basis Function-Neural-Network. 2014 8th Asia Modelling Symposium.
Sutrisno, I., Che, C. and Hu, J. (2014). Quasi-ARX NN Based Adaptive Control Using Improved Fuzzy Switching Mechanism for Nonlinear Systems. AROB 19th B-Con Plaza, Beppu, Japan.
Sutrisno, I. and Jami’in, M. A. (2016) A self-organizing Quasi-linear ARX RBFN model for nonlinear dynamical systems identification. SICE Journal of Control, Measurement, and System Integration.
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