cover
Contact Name
Herlambang Setiadi
Contact Email
h.setiadi@ftmm.unair.ac.id
Phone
+62881036000830
Journal Mail Official
jatm@ftmm.unair.ac.id
Editorial Address
Faculty of Advanced Technology and Multidiscipline, Gedung Kuliah Bersama, Kampus C Mulyorejo, Universitas Airlangga Jl. Dr. Ir. H. Soekarno, Surabaya, East Java 60115, Indonesia
Location
Kota surabaya,
Jawa timur
INDONESIA
Journal of Advanced Technology and Multidiscipline (JATM)
Published by Universitas Airlangga
ISSN : -     EISSN : 29646162     DOI : https://doi.org/10.20473/jatm.v1i2.40293
Journal of Advanced Technology and Multidiscipline (JATM) aims to explore global knowledge on sciences, information, and advanced technology. JATM provides a place for researchers, engineers, and scientists around the world to build research connections and collaborations as well as sharing knowledge on how addressing solutions to the (real world) problems through discoveries on cutting edge of science and technology. We encourage researchers to submit research in the following fields: ● Power System ● Control Systems ● Renewable Energy Technology ● Advanced Manufacturing ● Optimization & System Engineering ● Human Factors & Ergonomics ● Supply Chain & Logistic Management ● Waste Processing/ Waste Treatment ● Pollutant Removal ● Applied Chemistry ● Nano Medicine ● Sensor ● Artificial Intelligence ● Health Informatics ● Robotics & Mechatronics ● Computer Vision ● Data mining ● Human Computer Interaction ● Software Engineering ● Deep Learning ● Internet Of Things ● Natural Language Processing ● Learning Analytics & technologies ● Machine learning
Articles 4 Documents
Search results for , issue "Vol. 1 No. 1 (2022): Journal of Advanced Technology and Multidiscipline" : 4 Documents clear
Fuzzy based MPPT Control System in Grid Connected Solar Plant awan krismanto; Heru Purbo Waseso; Abraham Lomi; Eko Yohanes Setyawan; Adlan Bagus Pradana
Journal of Advanced Technology and Multidiscipline Vol. 1 No. 1 (2022): Journal of Advanced Technology and Multidiscipline
Publisher : Faculty of Advanced Technology and Multidiscipline Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1093.328 KB) | DOI: 10.20473/jatm.v1i1.39562

Abstract

The increase in demand for the electricity system is increasing. Thus, enviromentally friendly technologies such as new and renewable energy are needed, one of which is a power plant with Photovoltaic as the main component. Solar power plant has enviromentally friendly properties. The design of this solar power plant uses Fuzzy Logic Controller and PI Controller methods, where both methods are used to find the maximum power peak point used for fast charges and MPPT, which is simulted using MATLAB/Simulink. The things presented in developing the generating system using these two methods are solar radiation intensity, temperature and Photovoltaic module. The model developed will make it possible to examine the characteristics of solar power plant and predict the amount of energy generated by solar panels in a particular location and compare the effectiveness of Fuzzy Logic and PI methods. The results shows that Fuzzy method produces a boost converter output voltage in the range of 600 V with result that are still not good and less stable, but the irradiation of 100 W/m2 voltage is stable, while the boost converter output voltage controller by the PI method is very good and stable in all conditions. Radiation and voltage are also in the range of 600 V.
Classification of Types A and B Volcanic Earthquakes using Neural Network for Monitoring Mount Merapi Activities Dwi Lastomo; Wisnu Waskito Aji; Lalu Muhammad Jaelani; Agus Budi Santoso; Arif Musthofa
Journal of Advanced Technology and Multidiscipline Vol. 1 No. 1 (2022): Journal of Advanced Technology and Multidiscipline
Publisher : Faculty of Advanced Technology and Multidiscipline Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (727.001 KB) | DOI: 10.20473/jatm.v1i1.39576

Abstract

Mount Merapi is one of the most active volcanoes in the world. Seismic activity at Mount Merapi was divided into tectonic, volcanic A and B, avalanches, and multiphase. At the volcanology and mitigation station in the area of ​​Mount Merapi, the vibrations received by the seismometer installed on the mountain were then transmitted to the station to be interpreted in the form of a seismograph. Determination of the type of earthquake at the Mount Merapi station was done manually by analyzing the shape of the wave formed. Utilizing the earthquake waveform, it could be used to determine the type of earthquake using the Nntool toolbox in Matlab. So that the determination of the type of earthquake no longer needed to be done manually. The classification process began with training the system to understand earthquake-type classes. After the system understood the earthquake data belonging to each category, the classification process could be carried out. The types of earthquakes analyzed in this research were volcanic earthquakes of types A and B. The results of these classifications were used as a determinant of the type of earthquake that occurred. The results were obtained in the form of an introduction to the types of volcanic earthquakes type A and type B which were carried out automatically with a total accuracy of 91.83%. Type A earthquake recognition accuracy was 100%, type B earthquake recognition accuracy was 84.21%, the earthquake recognition accuracy of non-A & B type was 94.44%.
Self-motion behaviors of kinematically redundant manipulator for continuous path planning Setyamartana Parman; Mahmud Iwan Solihin
Journal of Advanced Technology and Multidiscipline Vol. 1 No. 1 (2022): Journal of Advanced Technology and Multidiscipline
Publisher : Faculty of Advanced Technology and Multidiscipline Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (606.217 KB) | DOI: 10.20473/jatm.v1i1.39600

Abstract

This paper presents self-motion behaviors of 3-DOF planar robotic arm when it tracks a predefined end-effector path. In this case, the self-motion contributes to geometry of a motion envelope. The Bezier curve degree fifth is utilized as the tracked path. Different geometry of the motion envelope can be used to avoid collision while it also follows the tracked path accurately. A theta global as closed form solution of 3-DOF planar robot is modeled as a polynomial degree sixth. A Genetic Algorithm (GA) as one of meta-heuristic optimizations is used to find optimal solution of the path planning approach. An effect of initial and final joint angles in the robotic arm motion is also investigated. The theta global trajectories are also possible to contain an imaginary number. The imaginary number of the theta global trajectories can be used as a sign that position errors are present and the trajectories need to be repaired using the self-motion analysis.
Speed Controller Design using Hybrid Differential Evolution Algorithm-Particle Swarm Optimization for PSMS Muhammad Aldo Setiawan; Herlambang Setiadi; Rodik Wahyu Indrawan; Rizki Putra Prastio
Journal of Advanced Technology and Multidiscipline Vol. 1 No. 1 (2022): Journal of Advanced Technology and Multidiscipline
Publisher : Faculty of Advanced Technology and Multidiscipline Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (339.731 KB) | DOI: 10.20473/jatm.v1i1.39764

Abstract

The use of engines that motorized the world based on fossil fuel sources has led to many problems, such as air pollution, energy security, global warming, and climate change. To prevent further damage reducing the application of fossil fuel as a source of the motor is crucial. Hence, utilizing an electric motor could be the solution to reduce the application of motors based on fossil fuel. Among the number of electric motors, permanent magnet synchronous motor (PSMS) is becoming more popular due to their efficiency. However, the challenge here is how to design the controller of PSMS, especially the speed controller. Hence, this paper proposed a design of a speed controller of PSMS using a PI controller. The hybrid differential evolution algorithm-particle swarm optimization (DEA-PSO) is used to optimize the PI controller for better performance. From the simulation result, it is found that the proposed method can enhance the performance of PSMS.

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