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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Reconfigurable and Embedded Systems (IJRES) International Journal of Applied Power Engineering (IJAPE) TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Sinergi Scientific Journal of Informatics Journal of Information Systems Engineering and Business Intelligence Bulletin of Electrical Engineering and Informatics Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer INTEGER: Journal of Information Technology BAREKENG: Jurnal Ilmu Matematika dan Terapan TIJAB (The International Journal of Applied Business) JURNAL PENGABDIAN KEPADA MASYARAKAT Jurnal Intake : Jurnal Penelitian Ilmu Teknik dan Terapan Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang Abdimasku : Jurnal Pengabdian Masyarakat Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Layanan Masyarakat (Journal of Public Service) Jurnal Nasional Pengabdian Masyarakat ALINIER: Journal of Artificial Intelligence & Applications Jurnal Sistim Informasi dan Teknologi Jurnal Ilmiah Hospitality Management Jurnal Rekayasa elektrika JGEN : Jurnal Pengabdian Kepada Masyarakat
Firdaus, Aji Akbar
Department Of Engineering, Faculty Of Vocational, Universitas Airlangga, Indonesia
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering 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 Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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The Home Security Monitoring System with Passive Infrared Receiver, Temperature Sensor and Flame Detector Based on Android System Uman Putra, Novian Patria; Firdaus, Aji Akbar; Winarno, Winarno; Prasaja, Alim; Setiawati, Kadek Juni
INTEGER: Journal of Information Technology Vol 6, No 1: Mei 2021
Publisher : Fakultas Teknologi Informasi Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.integer.2021.v6i1.1836

Abstract

A home state monitoring is important for homeowners. Because in Indonesia, theft and fire are common occurrences. This is caused by the negligence of homeowners. Therefore, home security monitoring systems are made to minimize theft and house fires. In this study, home security monitoring systems were made using human motion detection sensors or PIR (Passive Infrared Receiver) sensors, temperature sensors, flame detectors, buzzers, and pumps. The PIR sensor is used to detect thieves so buzzer can sound. The Temperature sensor and flame detector are used to detect fires then the pump will extinguish the fire. The system is then integrated with android HP devices, so homeowners can monitor the home wherever and whenever. From the test results, PIR sensor can detect human movement with a distance of 3.4 meters and the angle is 90o. The Temperature sensors and flame detectors detect temperatures and hotspots with a maximum distance of 25 cm, respectively
An improved control for MPPT based on FL-PSo to minimize oscillation in photovoltaic system Aji Akbar Firdaus; Riky Tri Yunardi; Eva Inaiyah Agustin; Sisca D. N. Nahdliyah; Teguh Aryo Nugroho
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 11, No 2: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (639.01 KB) | DOI: 10.11591/ijpeds.v11.i2.pp1082-1087

Abstract

Photovoltaic (PV) is a source of electrical energy derived from solar energy and has a poor level of efficiency. This efficiency is influenced by PV condition, weather, and equipments like Maximum Power Point Tracking (MPPT). MPPT control is widely used to improve PV efficiency because MPPT can produce optimal power in various weather conditions. In this paper, MPPT control is performed using the Fuzzy Logic-Particle Swarm Optimization (FL-PSO) method. This FL-PSO is used to get the Maximum Power Point (MPP) and minimize the output power oscillation from PV. From the simulation results using FL-PSO, the values of voltage, and output power from the boost converter are 183.6 V, and 637.7 W, respectively. The ripple of output power from PV with FL-PSO is 69.5 W. Then, the time required by FL-PSO reaches MPP is 0.354 s. Compared with MPPT control based on the PSO method, the MPPT technique using FL-PSO indicates better performance and faster than the PSO.
The comparison of dual axis photovoltaic tracking system using artificial intelligence techniques Machrus Ali; Aji Akbar Firdaus; Hamzah Arof; Hidayatul Nurohmah; Hadi Suyono; Dimas Fajar Uman Putra; Muhammad Aziz Muslim
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 10, No 4: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v10.i4.pp901-909

Abstract

In this paper, the efficiency of photovoltaic panels is improved by adding a sun tracking system. The solar tracking system is used for tracking the sun so that photovoltaic always faces the sun. This system uses a dual axis consisting of horizontal rotation axis and a vertical rotation axis. The horizontal rotational axis motion is to follow the azimuth angle of the sun from north to south. Then, to follow the sun's azimuth angle from east to west is the vertical axis motion. Both types of movements are controlled using a PID controller that is optimized with an artificial intelligence approach, namely particle swarm optimization (PID-PSO), firefly algorithm (PID-FA), imperialist competitive algorithm (PID-ICA), bat algorithm (PID-BA), and ant colony optimization (PID-ACO). Experiments of various approaches were carried out and the corresponding performance compared. The experimental results show that PID-BA performs best in terms of settling time and overshoot. The results also allow the comparison of different PID controller and the calculation of the fastest completion time.
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.
Robotic Leg Design to Analysis the Human Leg Swing from Motion Capture Riky Tri Yunardi; Aji Akbar Firdaus; Eva Inaiyah Agustin
Bulletin of Electrical Engineering and Informatics Vol 6, No 3: September 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (766.684 KB) | DOI: 10.11591/eei.v6i3.645

Abstract

In this paper presented the prototype of robotic leg has been designed, constructed and controlled. These prototype are designed from a geometric of human leg model with three joints moving in 2D plane. Robot has three degree of freedom using DC servo motor as a joint actuators: hip, knee and ankle. The mechanical leg constructed using aluminum alloy and acrylic material. The control movement of this system is based on motion capture data stored on a personal computer. The motions are recorded with a camera by use of a marker-based to track movement of human leg. Propose of this paper is design of robotic leg to present the analysis of motion of the human leg swing and to testing the system ability to create the movement from motion capture. The results of this study show that the design of robotic leg was capable for practical use of the human leg motion analysis. The accuracy of orientation angles of joints shows the average error on hip is 1.46º, knee is 1.66º, and ankle is 0.46º. In this research suggesting that the construction of mechanic is an important role in the stabilization of the movement sequence.
Robotic Leg Design to Analysis the Human Leg Swing from Motion Capture Riky Tri Yunardi; Aji Akbar Firdaus; Eva Inaiyah Agustin
Bulletin of Electrical Engineering and Informatics Vol 6, No 3: September 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (766.684 KB) | DOI: 10.11591/eei.v6i3.645

Abstract

In this paper presented the prototype of robotic leg has been designed, constructed and controlled. These prototype are designed from a geometric of human leg model with three joints moving in 2D plane. Robot has three degree of freedom using DC servo motor as a joint actuators: hip, knee and ankle. The mechanical leg constructed using aluminum alloy and acrylic material. The control movement of this system is based on motion capture data stored on a personal computer. The motions are recorded with a camera by use of a marker-based to track movement of human leg. Propose of this paper is design of robotic leg to present the analysis of motion of the human leg swing and to testing the system ability to create the movement from motion capture. The results of this study show that the design of robotic leg was capable for practical use of the human leg motion analysis. The accuracy of orientation angles of joints shows the average error on hip is 1.46º, knee is 1.66º, and ankle is 0.46º. In this research suggesting that the construction of mechanic is an important role in the stabilization of the movement sequence.
Distribution Network Reconfiguration Using Binary Particle Swarm Optimization to Minimize Losses and Decrease Voltage Stability Index Aji Akbar Firdaus; Ontoseno Penangsang; Adi Soeprijanto; Dimas Fajar U.P.
Bulletin of Electrical Engineering and Informatics Vol 7, No 4: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (906.197 KB) | DOI: 10.11591/eei.v7i4.821

Abstract

Power losses and voltage drop are existing problems in radial distribution networks. This power losses and voltage drop affect the voltage stability level. Reconfiguring the network is a form of approach to improve the quality of electrical power. The network reconfiguration aims to minimize power losses and voltage drop as well as decreasing the Voltage Stability Index (VSI). In this research, network reconfiguration uses binary particle swarm optimization algorithm and Bus Injection to Branch Current-Branch Current to Bus Voltage (BIBC-BCBV) method to analyze the radial system power flow. This scheme was tested on the 33-bus IEEE radial distribution system 12.66 kV. The simulation results show that before reconfiguration, the active power loss is 202.7126 kW and the VSI is 0.20012. After reconfiguration, the active power loss and VSI decreased to 139.5697 kW and 0.14662, respectively. It has decreased the power loss for 31.3136% significantly while the VSI value is closer to zero.
Distribution Network Reconfiguration Using Binary Particle Swarm Optimization to Minimize Losses and Decrease Voltage Stability Index Aji Akbar Firdaus; Ontoseno Penangsang; Adi Soeprijanto; Dimas Fajar U.P.
Bulletin of Electrical Engineering and Informatics Vol 7, No 4: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (906.197 KB) | DOI: 10.11591/eei.v7i4.821

Abstract

Power losses and voltage drop are existing problems in radial distribution networks. This power losses and voltage drop affect the voltage stability level. Reconfiguring the network is a form of approach to improve the quality of electrical power. The network reconfiguration aims to minimize power losses and voltage drop as well as decreasing the Voltage Stability Index (VSI). In this research, network reconfiguration uses binary particle swarm optimization algorithm and Bus Injection to Branch Current-Branch Current to Bus Voltage (BIBC-BCBV) method to analyze the radial system power flow. This scheme was tested on the 33-bus IEEE radial distribution system 12.66 kV. The simulation results show that before reconfiguration, the active power loss is 202.7126 kW and the VSI is 0.20012. After reconfiguration, the active power loss and VSI decreased to 139.5697 kW and 0.14662, respectively. It has decreased the power loss for 31.3136% significantly while the VSI value is closer to zero.
Short-Term Forecasting of Electricity Consumption Revenue on Java-Bali Electricity System using Jordan Recurrent Neural Network Tesa Eranti Putri; Aji Akbar Firdaus; Wilda Imama Sabilla
Journal of Information Systems Engineering and Business Intelligence Vol. 4 No. 2 (2018): October
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1369.973 KB) | DOI: 10.20473/jisebi.4.2.96-105

Abstract

Depending on the day and time, electricity consumption tends to fluctuate and directly affects the amount of gained revenue for the company. To anticipate future economic change and to avoid losses in calculating the company’s revenue, it is essential to forecast electricity consumption revenue as accurate as possible. In this paper, Jordan Recurrent Neural Network (JRNN) was used to do short term forecasting of the electricity consumption revenue from Java-Bali 500 kVA electricity system. Seven JRNN models were trained using electricity consumption revenue between January-March 2012 to predict the revenue of the first week of April 2012. As performance comparators, seven traditional feed forward Artificial Neural Network (ANN) models were also constructed. The forecasting results were as expected for both models, where both producing steady repeating pattern for weekdays, but failed quite poorly to predict the weekends’ revenue. This suggests that in Indonesia, weekends’ electricity consumption revenue has different characteristics than weekdays. Evaluation of the prediction result was carried out using Sum of Square Error (SSE) and Mean Square Error (MSE). The evaluation showed that JRNN produced smaller SSE and MSE values than traditional feed forward ANN, thus JRNN could predict the electricity consumption revenue of Java-Bali electricity system more accurately.
Co-Authors Achmad Luki Satriawan Adi Soeprijanto Agustin, Eva Inaiyah Alim Prasaja Aly, Muhammad Nilzam Ambarwati, Dewi Anang Budikarso Anang Tjahjono, Anang Andria Kusuma, Vicky Angkita Wasito Kirana Arof, Hamzah Asy'ari, Vaizal Azmita, Mimi Bambang Suharto Bambang Suharto DARMAWAN SETIA BUDI Daud, Muhamad Zalani Dimas Fajar U.P. Dimas Fajar Uman Putra Dimas Okky Anggriawan Dwi Retna Kumalaningrum Eka Prasetyono, Eka Eka Saputra Endro Wahjono Fasya, Arif Habib Firillia Filliana Gagas Gayuh Aji, Gagas Gayuh Ginting, Ina Veronica Hadi Suyono Hadi Suyono Hamzah Arof Hamzah Arof Happy Aprillia Hidayatul Nurohmah Indhana Sudiharto Jenrychk Marcelino Tandi Karrang Kadek Juni Setiawati Kenconojati, Hapsari Kharis Sugiarto Khuria Kirana, Angkita Wasito Kristanto, Damar Kristanto, Damar Kurnia Wijaya Kusuma Li Wang Machrus Ali Mahmud Iwan Solihin Maulana, Muhammad Hilmy Maurisia Putri Permatasari Mifta Nur Farid Mifta Nur Farid Mimi Azmita Muhaimin Muhaimin Muhammad Abby Rafdi Syah Muhammad Agung Nursyeha Muhammad Aziz Muslim Muhammad Aziz Muslim Muhammad Nizhom Ramadhani Muhammad Ridho Dewanto Muhammad Ruswandi Djalal Nabila Salvaningtyas Nasa Zata Dina Novian Patria Uman Putra Novian Uman Putra Nuruddi, Nuruddin Nyoman Juniarta, Nyoman Ontoseno Penangsang Pardede, Maria Agustina Prasaja, Alim Prayogo, Prayogo Priyanto, Yun Tonce Kusuma Putra, Dimas Fajar Uman Putra, Wahyu Haryanto Putri, Rahmah Fadiyah Rachman Sinatriya Marjianto Rahayu, Ragil Puji Rahmat Yuliawan Rajendran, Parvathy Risty Jayanti Yuniar Sena Sukmananda Suprapto Setiawati, Kadek Juni Sinulingga, Rizky Amalia Sisca Dina Nur Nahdliyah Sri Endah Kinasih Sri Endah Nurhidayati Suciyono, Suciyono Sugiarto, Kharis Suharno, Novianto Edi Suprapto, Sena Sukmananda Susanto, Fajar Annas Teguh Aryo Nugroho Teguh Herlambang Tesa Eranti Putri Trimulya, Hanif Uman Putra, Novian Patria Vicky Andria Kusuma Vicky Andria Kusuma Wilda Imama Sabilla Winarno Winarno Winarno, Winarno Yanuar Mahfudz Safarudin Yuli Prasetyo Yunardi, Riky Tri