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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) ELKHA : Jurnal Teknik Elektro TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Jurnal Teknologi Informasi dan Ilmu Komputer Setrum : Sistem Kendali-Tenaga-elektronika-telekomunikasi-komputer JURNAL NASIONAL TEKNIK ELEKTRO Bulletin of Electrical Engineering and Informatics Journal Of Vocational Health Studies Elektrika JURNAL PENGABDIAN KEPADA MASYARAKAT Berdikari: Jurnal Pengabdian Masyarakat Indonesia PEDULI: Jurnal Imiah Pengabdian Pada Masyarakat Darmabakti Cendekia: Journal of Community Service and Engagements Journal of Electronics, Electromedical Engineering, and Medical Informatics Journal of Robotics and Control (JRC) Indonesian Journal of Electrical Engineering and Computer Science Jurnal Abdidas INAJEEE (Indonesian Journal of Electrical and Electronics Engineering) Indonesian Applied Physics Letters International Journal of Robotics and Control Systems JEEE-U (Journal of Electrical and Electronic Engineering-UMSIDA) Jurnal Nasional Pengabdian Masyarakat J-Innovation Sewagati
Yunardi, Riky Tri
Department Of Engineering, Faculty Of Vocational Studies, Universitas Airlangga, Indonesia
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Other

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Journal : telkomnika telecommunication computing electronics and control

 1 
Application of EMG and Force Signals of Elbow Joint on Robot-assisted Arm Training Riky Tri Yunardi; Eva Inaiyah Agustin; Risalatul Latifah; Winarno Winarno
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 6: December 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i6.11707

Abstract

Flexion-extension based on the system's robotic arm has the potential to increase the patient's elbow joint movement. The force sensor and electromyography signals can support the biomechanical system to detect electrical signals generated by the muscles of the biological. The purpose of this study is to implement the design of force sensor and EMG signals application on the elbow flexion motion of the upper arm. In this experiments, the movements of flexion at an angle of 45º, 90º and 135º is applied to identify the relationship between the amplitude of the EMG and force signals on every angle. The contribution of this research is for supporting the development of the Robot-Assisted Arm Training. The correlation between the force signal and the EMG signal from the subject studied in the elbow joint motion tests. The application of sensors tested by an experimental on healthy subjects to simulating arm movement. The experimental results show the relationship between the amplitude of the EMG and force signals on flexion angle of the joint mechanism for monitoring the angular displacement of the robotic arm. Further developments in the design of force sensor and EMG signals are potentially for open the way for the next researches based on the physiological condition of each patient.
Short-term photovoltaics power forecasting using Jordan recurrent neural network in Surabaya Aji Akbar Firdaus; Riky Tri Yunardi; Eva Inaiyah Agustin; Tesa Eranti Putri; Dimas Okky Anggriawan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14816

Abstract

Photovoltaic (PV) is a renewable electric energy generator that utilizes solar energy. PV is very suitable to be developed in Surabaya, Indonesia. Because Indonesia is located around the equator which has 2 seasons, namely the rainy season and the dry season. The dry season in Indonesia occurs in April to September. The power generated by PV is highly dependent on temperature and solar radiation. Therefore, accurate forecasting of short-term PV power is important for system reliability and large-scale PV development to overcome the power generated by intermittent PV. This paper proposes the Jordan recurrent neural network (JRNN) to predict short-term PV power based on temperature and solar radiation. JRNN is the development of artificial neural networks (ANN) that have feedback at each output of each layer. The samples of temperature and solar radiation were obtained from April until September in Surabaya. From the results of the training simulation, the mean square error (MSE) and mean absolute percentage error (MAPE) values were obtained at 1.3311 and 34.8820, respectively. The results of testing simulation, MSE and MAPE values were obtained at 0.9858 and 1.3311, with a time of 4.591204. The forecasting has minimized significant errors and short processing times.
Voice recognition system for controlling electrical appliances in smart hospital room Eva Inaiyah Agustin; Riky Tri Yunardi; Aji Akbar Firdaus
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 2: April 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i2.11781

Abstract

Nowadays, most hospitals have new problem that is lack of medical nurse due to the number of patient increas rapidly. The patient especially with physical disabilities are difficult to control the switch on electrical appliances in patient’s room. This research aims to develope voice recognition based home automation and being applied to patient room. A miniature of patient’s room are made to simulate this system. The patient's voice is received by the microphone and placed close to the patient to reduce the noise.V3 Voice recognition module is used to voice recognition process. Electrical bed of patient is represented by mini bed with utilising motor servo. The lighting of patient room is represented by small lamp with relay. And the help button to call the medical nurse is represented by buzzer. Arduino Uno is used to handle the controlling process. Six basic words with one syllable are used to command for this system. This system can be used after the patient's voice is recorded. This system can recognize voice commands with an accuracy 75%. The accuracy can be improved up to 85% by changing the voice command into two syllables with variations of vowels and identical intonation. Higher accuracy up to 95% can be reached by record all the subject’s voice.
Co-Authors A'yun, Qurrotul Agustin, Eva Inaiyah Arief Muchadin Arifianto, Deny Ario Imandiri, Ario Bachtiar, Farhan Bambang Suharto Bascha, Umi Farichah Dani Setiawan Dayyana, Nimas Rokhmatik Devy Kuswidiastuti Dian Yulie Reindrawati Dimas Okky Anggriawan Djoko Purwanto Eka Lestari Elsyea Adia Tunggadewi Farhan Bachtiar Firdaus, Aji Akbar Franky Chandra Satria Arisgraha Intan Prananingrum, Jihan Irhamni, Irfan Jihan Intan Prananingrum Jiwangga Hadi Nata Kartikasari, Amilia Khusnul Ain Kurnia Latifa Priyanti Mardhiyah, Ajeng W. Maulina, Farah Miladyah, Rizka Moh Yasin Moh. Zakky Zulfiar Muchadin, Arief Muhammad Attamimi Muhammad Rivai Muharom, Syahri Nasa Zata Dina Nur Emma Suriani Pramono Priyanti, Kurnia Latifa Pujiyanto Retna Apsari Riries Rulaningtyas Risalatul Latifah Riza Agung Ronny Mardiyanto, Ronny Rr. Wanda Auruma Putri Rudy Dikairono Ruth Johana Hutagalung Sisca Dina Nur Nahdliyah Teguh Aryo Nugroho Tesa Eranti Putri Totok Mujiono, Totok Tri Anggono Prijo, Tri Anggono Tri Arief Sardjono WINARNO Winarno, Winarno Yahya, M. Hafi