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All Journal Empowerment JPTE: Jurnal Pendidikan Teknik Elektro Jurnal Teknik, Komputer, Agroteknologi dan Sains Journal of Industrial Automation and Electrical Engineering
Hendra, Ayu
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Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Other

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Friability Tester Berbasiskan Node MCU 8266 Dikontrolkan Dengan Android Nurqaidah, Siti; Timor, Agus Rahmad; Nurmantika, Julia; Hendra, Ayu; Marly, Andresta
Educativo: Jurnal Pendidikan Vol 3 No 1 (2024): Jurnal Teknik, Komputer, Agroteknologi dan Sains (Marostek) IN PRESS
Publisher : PT. Marosk Zada Cemerlang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56248/marostek.v3i1.102

Abstract

Penelitian ini bertujuan untuk menghasilkan sebuah alat yang digunakan untuk menentukan keregasan, kerapuhan atau kepadatan tablet terutama pada saat tablet akan dilapisi (coating). Adapun metode penelitian yang digunakan adalah metode penelitian pengembangan dengan model R-D-R (Research-Development-Research). Model penelitian ini memiliki tiga kegiatan pokok pengembangan yaitu melakukan penelitian pendahuluan, pengembangan perangkat produk, dan melakukan uji keefektifan alat. Alat Friability Tester berbasiskan Node MCU 8266, dikontrol dengan android, dengan tegangan kerja sebesar 220VAC, arus sebesar 3 ampere dan daya sebesar 660 watt, dilengkapi dengan mode wifi dimana agar dapat mempermudah pengguna dalam mensetting waktu dan mengatur RPM sesuai yang diinginkan oleh pengguna. Berdasarkan hasil penelitian uji fungsi alat pada beberapa tablet maka dapat disimpulkan bahwa alat dapat berfungsi sesuai rancangan dilihat dari keakurasian timer, pengujian titik pengukuran, dan pengujian kecepatan motor tidak terdapat selisih yang terlalu signifikan.
Peningkatan Kompetensi Otomasi Mesin Industri menggunakan Human Machine Interface (HMI) untuk Guru Vokasi Sardi, Juli; Habibullah, Habibullah; Eliza, Fivia; Risfendra, Risfendra; Hendra, Ayu; Setyawan, Herlin
Jurnal Pendidikan Teknik Elektro Vol 6 No 1 (2025): Jurnal Pendidikan Teknik Elektro
Publisher : Jurusan Teknik Elektro Fakultas Teknik Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jpte.v6i1.530

Abstract

The enhancement of teachers' competencies in industrial automation technology is urgently needed to address the challenges of Industry 4.0. This study aims to measure the effectiveness of the training program Industrial Machine Automation Using Human Machine Interface (HMI) in improving teachers' competencies at SMK Negeri 5 Solok Selatan. The research employed a One Group Pre-test Post-test Design method, with data analysis conducted using the Paired Sample T-Test. A total of 20 teachers participated in the training, which consisted of theoretical sessions, software simulations, and hands-on practice with HMI hardware. The results indicated a significant improvement in participants' competencies, with the average score increasing from 55 in the pre-test to 83.25 in the post-test (p<0.05). The training effectively strengthened participants' conceptual understanding, programming skills, and troubleshooting abilities. Furthermore, the program was deemed relevant to the technological needs of vocational education, supporting the integration of automation technology into the vocational school curriculum. This study concludes that HMI training can serve as a strategic model for teacher competency development, contributing to improving vocational education quality. Recommendations include conducting advanced training sessions, enhancing collaboration with industry, and developing project-based curricula oriented toward modern technologies.
Peningkatan Produktifitas Teaching Factory Industrial Robotic and Automation sebagai Pusat Inovasi Peralatan Laboratorium Pendidikan Vokasi Risfendra, Risfendra; Sukardi, Sukardi; Sardi, Juli; Habibullah, Habibullah; Hendra, Ayu; Setyawan, Herlin
Jurnal Pendidikan Teknik Elektro Vol 6 No 1 (2025): Jurnal Pendidikan Teknik Elektro
Publisher : Jurusan Teknik Elektro Fakultas Teknik Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jpte.v6i1.531

Abstract

The Teaching Factory Industrial Robotics and Automation ( TEFA IRA) at Universitas Negeri Padang (UNP) represents an innovative vocational education model integrating practice-based learning with real-world production activities. As an innovation hub, TEFA IRA produces laboratory equipment to support vocational learning, trains vocational high school (SMK) teachers, and enhances student competencies to meet the workforce's demands in the Fourth Industrial Revolution era. This study evaluates the productivity of TEFA IRA by analysing operational processes, the impact of teacher training, student learning experiences, product relevance, and collaboration with industry partners. The research employs a mixed-methods approach, combining qualitative and quantitative techniques with data collected through observation, interviews, surveys, and document analysis. The results indicate that TEFA IRA successfully produced 25 units of laboratory equipment with a 92% success rate. Training for SMK teachers improved their technology mastery scores from 3.2 to 4.1 (on a 5-point scale), while 90% of students reported that their learning experiences were relevant to workforce demands. Collaboration with industry partners reached an active involvement rate of 87%, including contributions to technology and technical training. However, TEFA IRA faces challenges, such as limited specialised expertise, the need for updated training modules, and the optimisation of facilities. Support from Universitas Negeri Padang is essential to address these challenges through strategic policies, facility enhancements, and strengthened industry partnerships. Overall, TEFA IRA has successfully established itself as an innovative and relevant Teaching Factory model for vocational education in Indonesia. This program holds significant potential to be further developed as a pioneer in technology-driven vocational education with global competitiveness.
AI-BASED TRAINING TO ENHANCE TEACHERS' BEHAVIORAL INTENTIONS AND WILLINGNESS TO UTILIZE AI TECHNOLOGY IN CLASSROOM LEARNING Ranuharja, Fadhli; Willyansyah, Willyansyah; Marta, Rizka Yani; Hendra, Ayu; Rudi Mulya; Novid, Igor
Jurnal Empowerment Vol 14 No 1 (2025): February 2025
Publisher : IKIP Siliwangi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22460/empowerment.v14i1.5358

Abstract

The technological transformation in educational media has driven significant changes in teaching and learning processes, particularly highlighted by the COVID-19 pandemic, which underscored the importance of adopting Artificial Intelligence (AI) as an assistive tool in developing more effective online learning materials. This community service program was conducted in collaboration with SMAN 3 Padang Panjang, involving 22 teachers from grades X to XII as participants. The program was designed in three main phases: (1) preparation and field observation, (2) field implementation, and (3) evaluation. Evaluation results indicate that teachers demonstrate high behavioral intention and willingness to use AI in their teaching practices. The average scores on the behavioral intention aspect suggest that teachers are inclined to recommend and intend to use AI in the future, while on the willingness-to-use aspect, teachers are willing to dedicate time to learning and overcoming challenges related to AI usage. These findings suggest that AI-based training is effective in enhancing teachers' readiness and commitment to integrating technology into the teaching process, thereby potentially strengthening educational quality in the digital era
Internet of Things (IoT) implementation through Node-RED to control and monitoring induction motors Bahri, Faisal; Ta ali; Hendra, Ayu
Journal of Industrial Automation and Electrical Engineering Vol. 1 No. 1 (2024): Vol 1 No 1 (2024): June 2024
Publisher : Department of Electrical Engineering Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/

Abstract

The Internet of Things (IoT) is a technology that plays an important role in the contemporary era, especially in the industrial sector. The Internet of Things allows remote access of physical objects at any time and from any location, simply by establishing an internet connection. Thus, in the control and monitoring of motors remotely, IoT allows adjusting the speed and direction of rotor rotation. The motor used is a 0.75 kW Siemens induction motor. To adjust the speed and direction of rotor rotation of the motor, a Sinamic G120 programmable logic controller S7-1200 VSD is programmed via TIA Portal to serve as the central controller for all induction motor control. A multi-interface system consisting of a KTP 700 Comfort HMI, a PC server, and clients in the form of PC and smartphone clients was used for control and monitoring of the induction motor. The visual interface of the HMI interface was designed using TIA Portal, while the visual interface of the server and client was designed using Node-RED. The PC server, PLC, HMI, and VSD are all connected via Ethernet. At the same time, the connection of the Internet of Things (IoT) client, which is integrated with the server, is connected via the Internet network. Research on IoT-based control and monitoring of induction motors through the Node-RED proposal has been successful and works as intended
Implementation of Maximum power control of Solar Panels using Modified Perturb and Observe Algorithm based on Adaptive Neuro Fuzzy Inference System Kurniawan, Ilham; Yuhendri, Muldi; Hendra, Ayu; Hidayat, Rahmat
Journal of Industrial Automation and Electrical Engineering Vol. 1 No. 1 (2024): Vol 1 No 1 (2024): June 2024
Publisher : Department of Electrical Engineering Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In this modern era, the need for renewable energy is increasing, and solar panels are one of the main solutions. To maximize the efficiency of energy extraction from solar panels, a method is needed. Based on the characteristics of voltage and current, the output power of these solar panels changes following changes in irradiation and temperature. Changes in the output power value have a maximum point, where each voltage and current value has a different maximum power point at each change in temperature. For this reason, the Maximum Power Point Tracker (MPPT) method is used to solve this problem by adjusting the solar panel voltage at the maximum point using a power converter. In this study, the MPPT control system will be implemented using a boost converter. This study develops a Maximum Power Point Tracking (MPPT) control system based on the Adaptive Neuro-Fuzzy Inference System (ANFIS), which is developed from conventional perturbation and observation algorithms. The ANFIS-based MPPT control system is implemented using an Arduino microcontroller. The experimental results verify that the proposed ANFIS-based MPPT system has successfully controlled the output power of solar panels at the maximum point
DC motor control using a four-quadrant chopper based on artificial neural networks Rahmad, Rahmad Rizki; Hendra, Ayu; Yuhendri, Muldi
Journal of Industrial Automation and Electrical Engineering Vol. 1 No. 2 (2024): Vol 1 No 2 (2024): December 2024
Publisher : Department of Electrical Engineering Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/q4vshv30

Abstract

DC motors are widely used as drives in various industrial applications. To ensure optimal performance, precise control of DC motors is essential, including managing rotation direction, speed, braking, and starting current. This paper presents a speed control system for a DC motor using a 4-quadrant DC chopper with a neural network as the control core. The system is designed and implemented on a 12V DC motor and tested under varying speed conditions. Motor speed is adjusted in MATLAB Simulink according to operational requirements. The results confirm that the proposed DC motor speed control system, utilizing a four-quadrant chopper, functions effectively, providing accurate speed control through MATLAB Simulink.
Control of  buck boost converter with Mamdani Fuzzy inference system using Microcontroller Arduino Syafyutina, Rahmat Alwafi; Yuhendri, Muldi; Dewi, Citra; Hendra, Ayu
Journal of Industrial Automation and Electrical Engineering Vol. 1 No. 2 (2024): Vol 1 No 2 (2024): December 2024
Publisher : Department of Electrical Engineering Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/2hs6xn51

Abstract

Various electrical equipment utilizes direct voltage (DC) as a power source. Examples of this equipment include various electronic devices as well as DC motors and others. The direct voltage used usually has various ratings, ranging from 1.5 volts to 12 volts, and other numbers. To ensure that the direct voltage is in accordance with the tool's needs, it is necessary to control this voltage. This control is generally carried out using a power converter. In this research, buck-boost converter output voltage control will be implemented using the Fuzzy Mamdani method with an Arduino Atmega 2560. The control system developed will be tested through experiments in the input voltage range between 12 to 24 Volts, with a maximum output of 18 Volts. The experimental results show that the Fuzzy Mamdani based buck-boost converter output voltage control system successfully regulates the output voltage according to the desired reference value
Co-Authors Agus Rahmad Timor, Agus Rahmad BAHRI, FAISAL Citra Dewi Fadhli Ranuharja Fivia Eliza Habibullah Habibullah Igor Novid Ilham Kurniawan Juli Sardi Marly, Andresta Marta, Rizka Yani Muldi Yuhendri Nurmantika, Julia Rahmad, Rahmad Rizki Rahmat Hidayat Risfendra, Risfendra Rudi Mulya Setyawan, Herlin Siti Nurqaidah Sukardi Sukardi Syafyutina, Rahmat Alwafi Ta ali Willyansyah, Willyansyah