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All Journal International Journal of Electrical and Computer Engineering Jurnal Teknoin Media Informatika Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Rotasi Jurnal Sistem Komputer TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Jurnal EECCIS FLYWHEEL : Jurnal Teknik Mesin Untirta Teknika: Jurnal Sains dan Teknologi Journal Industrial Servicess Setrum : Sistem Kendali-Tenaga-elektronika-telekomunikasi-komputer Jurnal Ilmiah Dinamika Rekayasa (DINAREK) Bulletin of Electrical Engineering and Informatics Proceeding of the Electrical Engineering Computer Science and Informatics VOLT : Jurnal Ilmiah Pendidikan Teknik Elektro Jurnal Elementer (Elektro dan Mesin Terapan) Jurnal Ilmu Komputer dan Bisnis IJITEE (International Journal of Information Technology and Electrical Engineering) Indonesian Journal of Electrical Engineering and Computer Science Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) INSANtek – Jurnal Inovasi dan Sains Teknik Elektro Jurnal Nasional Teknik Elektro dan Teknologi Informasi Indonesian Journal of Aerospace
romi wiryadinata
Universitas Sultan Ageng Tirtayasa
Aerospace Engineering Astronomy Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Transportation

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Journal : Bulletin of Electrical Engineering and Informatics

 1 
Design of a Low Cost Remotly Operated Vehicle with 3 Dof Navigation Romi Wiryadinata; Annisa Sucianti Nurliany; Imamul Muttakin; Teguh Firmansyah
Bulletin of Electrical Engineering and Informatics Vol 6, No 1: March 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v6i1.596

Abstract

One type of underwater robot is the ROV (Remotely Operated Vehicle) whose movements are controlled directly by humans from the water surface. In this paper, ROV prototype has been designed and tested with three DoF (Degrees of Freedom) and controlled by a joystick which is connected with UTP (Unshielded Twisted Pair) cables as data transmission between joystick with a microcontroller embedded in the robot. This prototype has 3 thrusters with 3 degrees of freedom, 1 rotational motion (heave) and 2 translational motion (yaw and surge), with direction of movement up, down, forward, backward, turn right, and turn left. Speed mode setting when forward movement on PWM (Pulse Width Modulation) 75% = 0,037 m/s, 90% = 0.053 m/s and 100% = 0,071 m/s, while the reverse speed by 75% = 0,034 m/s, 90% = 0.045 m/s and 100% = 0.059 m/s, when the ROV moves up is 0,042 m/s, down 0.032 m/s, turn right 9 o/s and turn left 15 o/s set with fixed PWM value, is 100%.
Laboratory prediction energy control system based on artificial intelligence network Desmira Desmira; Norazhar Abu Bakar; Mohd Ruzaini Hashim; Romi Wiryadinata; Mustofa Abi Hamid
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.1821

Abstract

The use of electrical energy increases globally every year. The laboratory prediction energy control system (LPECS) predicted energy demand. This research was conducted in the Electrical Engineering Vocational Education laboratory by comparing the artificial neural fuzzy system (ANFIS) with the fuzzy logic. The comparison of methods aimed to determine their reliability in the energy demand prediction systems. The results showed that the minimum value of the target data using the conventional method (actual data) was 44.42%. Meanwhile, the prediction data using the ANFIS method was 44.33%, and the prediction data using the fuzzy method was 59.31%. The maximum value of the conventional ways (actual data) of ANFIS and fuzzy was similar by 77.59%. The RMSE ANFIS value was 0.1355%, the mean absolute percentage error (MAPE) was 0.2791%, and the fuzzy logic was 0.1986%. Thus, the ANFIS is applicable to determine the minimum and maximum values. Meanwhile, fuzzy can only show the maximum value but cannot reach the minimum value properly.
Co-Authors Adi Nugraha Alfanz, Rocky Alfanz, Rocky Alia Shaliha Amany Alief Maulana Alimuddin Alimuddin Amany, Alia Shaliha Anggoro S Pramudyo Anggoro Suryo Pramudyo Annisa Sucianti Nurliany Aribowo, Didik Arya Prasetyo Habibie Boby Fisher Butar-butar Butar-butar, Boby Fisher Denny Hardiyanto Desmira Desmira Desmira Desmira Desmira Desmira, Desmira Dhimas Satria Didin Yogiyansyah Dwi Ana Ratnawati Fahrizal, Rian Fajar Saptono Felycia Firda Andini Galang Wicaksono Habibie, Arya Prasetyo Haryadi - Heri Kusharyanto Herudin Herudin Iing Mutakhiroh Imamul Muttakin Imron Rosyadi Istiyah, Umi Iwan Tirta Joko Lelono Kaharjito, Frandi A Kliwati, Sri M Iman Santoso Maulana, Alief Mohd Ruzaini Hashim Muhammad Afif Muhammad Ilham Daifullah Muhammad Nurtanto Muhammad Rofiki Adli Mustofa Abi Hamid Ni Ketut Caturwati, Ni Ketut Norazhar Abu Bakar Norazhar Abu Bakar NUR HASANAH Nur Kholifah Priswanto Priswanto, Priswanto Priswanto, Priswanto Raya Sagita Raya Sagita, Raya Ri Munarto Ri Munarto, Ri Rian Fahrizal Roman Lesmana Rustamaji, Rustamaji Setiawan, Ipick Setyawan, Haris Siswo Wardoyo Siswo Wardoyo Sobar, Fragrans Anjasmara Suhendar Suhendar Teguh Firmansyah Teguh Firmansyah Teguh Firmansyah Toto Supriyanto Umi Istiyah Wahyu Widada Wahyu Widada Wahyuni Martiningsih Widada, Wahyu Yul Antonisfia Yus Rama Denny Yusuf, Wildan