relation: http://repository.upi.edu/144409/
title: PEMBUATAN MODUL PEMBELAJARAN OTOMASI INDUSTRI BERBASIS TEKNOLOGI PLC DAN HMI TERINTEGRASI IOT: Pendekatan Deep Learning Sebagai Strategi Pembelajaran Abad 21
creator: Ikrima Akmalia, -
creator: Jaja Kustija, -
subject: L Education (General)
subject: TK Electrical engineering. Electronics Nuclear engineering
description: Pendidikan memiliki peran penting dalam pengembangan pola pikir, kreativitas, dan kemampuan berpikir kritis siswa, terutama melalui pendekatan pembelajaran yang menekankan penguasaan keterampilan 4C: creative, collaborative, communicative, dan critical thinking. Salah satu pendekatan yang esensial dalam mendukung hal tersebut adalah deep learning, yang menekankan pemahaman mendalam, refleksi, dan keterhubungan antar konsep, sehingga mendorong siswa untuk berpikir secara analitis, kontekstual, dan berkelanjutan dalam menghadapi tantangan nyata di dunia industri. Revolusi Industri 4.0 telah mendorong transformasi signifikan dalam pendidikan vokasi, khususnya terkait integrasi teknologi seperti otomasi, IoT, dan kecerdasan buatan. Namun, tantangan utama masih meliputi kurangnya integrasi teknologi industri dalam pembelajaran, keterbatasan fasilitas praktik, pendekatan pedagogis yang belum optimal, rendahnya kesiapan siswa menghadapi tuntutan industri berbasis IoT dan PLC, serta keterbatasan modul ajar yang kontekstual dan mudah diakses. Penelitian ini bertujuan mengembangkan modul pembelajaran otomasi industri berbasis PLC Omron, HMI Haiwell, dan IoT dengan pendekatan deep learning untuk meningkatkan kualitas pembelajaran dan kesiapan kerja siswa. Menggunakan metode R&D dengan model ADDIE, penelitian melibatkan 32 siswa SMK kelas XII Teknik Otomasi Industri. Hasil menunjukkan modul memperoleh skor kelayakan rata-rata 80,16% (kategori “baik”) dari aspek materi, media, dan pembelajaran. Kebaruan penelitian terletak pada integrasi konten teknis dengan pendekatan deep learning yang mendorong keterampilan berpikir reflektif dan kolaboratif. Penelitian merekomendasikan uji efektivitas melalui pre-test dan post-test serta pengembangan fitur digital interaktif untuk pengalaman belajar yang lebih adaptif.    Education plays a crucial role in developing students' thinking patterns, creativity, and critical thinking skills, particularly through a learning approach that emphasizes mastery of the 4C skills: creative, collaborative, communicative, and critical thinking. One essential approach that supports these goals is deep learning, which emphasizes profound understanding, reflection, and interconnection between concepts, thereby encouraging students to think analytically, contextually, and sustainably in responding to real-world industrial challenges. The Industrial Revolution 4.0 has significantly transformed vocational education, especially with the integration of technologies such as automation, IoT, and artificial intelligence. However, challenges persist, including limited integration of industrial technology in learning, inadequate practical facilities, suboptimal pedagogical methods, low student readiness for IoT and PLC-based industry demands, and a lack of contextual, accessible teaching modules. This study aims to develop an industrial automation learning module based on Omron PLC, Haiwell HMI, and IoT using a deep learning approach to improve learning quality and student job readiness. Using the R&D method with the ADDIE model, the study involved 32 twelfth-grade vocational students in Industrial Automation Engineering. The module achieved an average feasibility score of 80.16% (“good”) in terms of content, media, and instructional quality. The novelty of this research lies in the integration of technical content with a deep learning approach that promotes reflective and collaborative thinking. The study recommends further effectiveness testing through pre- and post-assessments and the development of interactive digital features to support a more adaptive learning experience.
date: 2025-08-25
type: Thesis
type: NonPeerReviewed
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identifier: http://repository.upi.edu/144409/1/S_TE_2109795_Title.pdf
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identifier: http://repository.upi.edu/144409/2/S_TE_2109795_Chapter%201.pdf
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identifier: http://repository.upi.edu/144409/3/S_TE_2109795_Chapter%202.pdf
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identifier: http://repository.upi.edu/144409/4/S_TE_2109795_Chapter%203.pdf
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identifier: http://repository.upi.edu/144409/5/S_TE_2109795_Chapter%204.pdf
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identifier: http://repository.upi.edu/144409/6/S_TE_2109795_Chapter%205.pdf
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identifier: http://repository.upi.edu/144409/7/S_TE_2109795_Appendix.pdf
identifier:   Ikrima Akmalia, - and Jaja Kustija, -  (2025) PEMBUATAN MODUL PEMBELAJARAN OTOMASI INDUSTRI BERBASIS TEKNOLOGI PLC DAN HMI TERINTEGRASI IOT: Pendekatan Deep Learning Sebagai Strategi Pembelajaran Abad 21.  S1 thesis, Universitas Pendidikan Indonesia.   
relation: https://repository.upi.edu/