Journal of Advanced Technology and Multidiscipline <p>Journal of Advanced Technology and Multidiscipline (JATM) (<a href="" target="_blank" rel="noopener">e-ISSN: 2964-6162</a>) is an open access journal that publishes original research articles, review articles and case study articles. The JATM is open submission from scholars and experts in the wide areas of electrical engineering, industrial engineering, nanotechnology engineering, data science technology, and robotics and artificial intelligence. JATM publishes twice in a year, the first number is in May and the second number is in November. </p> Faculty of Advanced Technology and Multidiscipline Universitas Airlangga en-US Journal of Advanced Technology and Multidiscipline 2964-6162 <h2>Copyright</h2> <p>Journal of Advanced Technology and Multidiscipline (E-ISSN:<a href="">2964-6162</a>) by <a href="" target="_blank" rel="noopener">Universitas Airlangga,</a> Faculty of Advanced Technology and Multidiscipline is licensed under a <a href="">Creative Commons — Attribution 4.0 International — CC BY 4.0</a></p> <p><strong>Authors who publish with this journal agree to the following terms</strong>:</p> <ul> <li> <p align="justify">The journal allows <span class="m_-8872622167488361851m_3889253648079045002m_3801934354951983127m_-2782718132241447849m_-7691471417709598651m_7256872056212528454m_3794665997207553305gmail-animated">the author to hold the copyright of the article without restrictions.</span></p> </li> <li> <p align="justify">The journal allows the author(s) to retain publishing rights without restrictions.</p> </li> <li> <p align="justify">The legal formal aspect of journal publication accessibility refers to Creative Commons Attribution (CC BY).</p> </li> </ul> <p> </p> <p><strong>LICENSE TERMS</strong></p> <p>You are free to:</p> <ul> <li class="license remix"><strong>Share </strong>— copy and redistribute the material in any medium or format</li> <li class="license remix"><strong>Adapt</strong> — remix, transform, and build upon the material for any purpose, even commercially.</li> </ul> <p>Under the following terms:</p> <ul class="license-properties col-md-offset-2 col-md-8" dir="ltr"> <li class="license by"> <p><strong>Attribution</strong> — You must give <a id="appropriate_credit_popup" class="helpLink" tabindex="0" href="" target="_blank" rel="noopener" data-original-title="">appropriate credit</a>, provide a link to the license, and <a id="indicate_changes_popup" class="helpLink" tabindex="0" href="" target="_blank" rel="noopener" data-original-title="">indicate if changes were made</a>. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.<span id="by-more-container"></span></p> </li> </ul> <ul id="deed-conditions-no-icons" class="col-md-offset-2 col-md-8"> <li class="license"><strong>No additional restrictions</strong> — You may not apply legal terms or <a id="technological_measures_popup" class="helpLink" tabindex="0" href="" target="_blank" rel="noopener" data-original-title="">technological measures</a> that legally restrict others from doing anything the license permits</li> </ul> The Study the Relevance of the Development of a Garbage Power Plant to the Large Increase in Waste Volume in Indonesia <p><em>Garbage endangers the community in terms of health, the economy, and the land that is taken up. Indonesia is a country with many waste piles, but there is waste management in terms of recycling, the use of computers, and other things, even from energy sources for power plants. The Waste Power Plant (PLTSa) is an electric power plant that helps add electrical energy for the PLN to be distributed to the community. The source of combustion and the driving point for garbage power plan (PLTSa) is waste; therefore, most of these locations are located in landfills in big cities. This research article aims to strengthen the argument that the development of PLTSa can be accelerated because the increase in waste piles every year will cause unmanaged waste to also increase. The results of studies and literacy studies show that the average managed waste pile is 15,000 tons/year and still leaves 5 million tons/year of waste that is not appropriately managed; however, the PLTSa capacity is still small at 10 MWh/year. It is necessary to increase the quality of waste containers as a source of PLTSa energy to reduce the amount of unmanaged waste.</em></p> M. Syaiful Alim Dwi Lastomo Nurbaiti Nurbaiti Donny Yoesgiantoro Rudy Laksmono Copyright (c) 2023 M. Syaiful Alim, Dwi Lastomo, Nurbaiti Nurbaiti, Donny Yoesgiantoro, Rudy Laksmono 2023-12-31 2023-12-31 2 2 34 39 10.20473/jatm.v2i2.47839 Small Signal Stability Analysis of Kalimantan 500 KV Electricity System <p style="text-align: justify; margin: 0cm 0cm 8.0pt 0cm;"><strong><span style="font-size: 9.0pt; color: black;">Small signal stability refers to the ability of a system to return to equilibrium after experiencing a small disturbance. In this research, the Kalimantan electricity system will be analyzed for the stability of its small signal. Analysis of the stability of small signals in electrical systems including local disturbances and inter-area disturbances. The Kalimantan system will be analyzed using Power Factory software. System analysis was carried out by evaluating the eigenvalues ​​(real part and imaginary part), oscillation frequency (damped frequency and frequency ratio) produced in the Kalimantan 500 KV electricity analysis. In the analysis results, the Kalimantan system is categorized as stable as indicated by the real part and imaginary part values ​​located on the negative side of the Cartesian coordinate curve. Then, analyzing small signals, there are 117 modes categorized as local mode and 4 modes categorized as inter area mode.</span></strong><span style="font-size: 9.0pt; color: black;"> </span></p> Akbar Syahbani Agus Sadid Ismayahya Ridhan Mutiarso Fauzany Arif Kemal Iskandar Muda Fadhil Bintang Prawira Copyright (c) 2023 Akbar Syahbani Agus Sadid, Ismayahya Ridhan Mutiarso, Fauzany Arif, Kemal Iskandar Muda, Fadhil Bintang Prawira 2023-12-31 2023-12-31 2 2 40 46 10.20473/jatm.v2i2.53379 A Review: Artificial Intelligence Related to Agricultural Equipment Integrated with the Internet of Things <p><strong><em>Abstract</em></strong><strong>—The development of modern technology has brought progress to the agricultural sector. Previously, farming was carried out using traditional methods, resulting in lower crop production. Now the world is faced with various problems, there are challenges such as climate fluctuations and increasing human population. This problem causes food needs to increase drastically, so adopting Industry 4.0 technology in the agricultural sector is necessary. Artificial Intelligence (AI) and Internet of Things (IoT) are part of industrial technology advances 4.0 that can be applied to modern agriculture. This paper reviews several AI technologies used in the agricultural sector, such as Fuzzy Logic (FL), Artificial Neural Network (ANN), Machine Learning (ML), Deep Learning (DL), Genetic Algorithm (GA), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Decision Support System (DSS). The application form of integration between AI and IoT is divided into several categories: soil monitoring, agricultural irrigation, fertilizer spraying, pest and plant disease control, harvesting, forecasting, and yield monitoring. This review paper was created to provide a comprehensive overview of modern agriculture integrating AI and IoT. This form of application makes it possible to predict the future of agriculture so that it can manage resources more efficiently and run autonomously. This review aims to analyze and explore the latest developments in integrating AI and IoT in agricultural equipment in the period 2019 to 2023. Thus, it is hoped that this article can provide in-depth insight into future agricultural technology advances.</strong></p> <p>&nbsp;</p> <p><strong><em>Keywords</em></strong><strong>—Artificial Intelligence (AI), Internet of Things (IoT), Agriculture, Integration of AI and IoT, Smart farming.</strong></p> Juhen Wildan Copyright (c) 2023 Juhen Wildan 2023-12-31 2023-12-31 2 2 47 60 10.20473/jatm.v2i2.51440 Implementation of Artificial Intelligence in Healthcare <div> <p class="Abstract"><strong><span lang="EN">Health is one of the pillars in determining human performance in their daily activities. Someone with good health can work optimally because there are no health problems they have. On the other hand, artificial intelligence is a form of technology that is developing rapidly. This technology has various benefits that can be provided, especially in the health sector to help health workers. The technologies that are often used are expert systems and artificial neural networks because of their ease of operation and accuracy in carrying out the work of health workers. Various other technologies are being developed to facilitate the performance of health workers to lighten their workload, such as robots to help paralyzed patients, automatic operating robots, and other technologies that can help ease the burden on health workers' performance.</span></strong></p> </div> <div><em><span lang="EN-US">Keywords</span></em><span lang="EN-US">—health, artificial intelligence, neural network, expert system</span></div> Fariza Shielda Akzatria Copyright (c) 2023 Fariza Shielda Akzatria 2023-12-31 2023-12-31 2 2 61 66 10.20473/jatm.v2i2.47091 Optimization of SVC Placement and Capacity in the Electric Power System Transmission Networks using Multi-Objective Improved Sine Cosine Algorithm <p>Current technological developments are in line with the increasing consumption of electrical energy.&nbsp; There is a value of power losses of the electricity transmission process caused by an increase in the value of power losses, to overcome this, SVC (Static VAR Compensator) of the Flexible AC Transmission System (FACTS) can be used. From previous studies, the optimization of SVC placement in the transmission network has not been carried out to get better power losses. This research uses the Improved-Sine Cosine Algorithm (ISCA) that has a different function of r1 compared to the ordinary SCA, in which the use of the ISCA method is able to overcome the weaknesses of the SCA method. The determination of location and capacity can use more than one objective function. From the result, the optimization of SVC placement and capacity is able to reduce the value of power losses by up to 85%.</p> Muhammad Abdillah Ferbyansyah Gilang Maulana Teguh Aryo Nugroho Copyright (c) 2023 Muhammad Abdillah, Ferbyansyah Gilang Maulana, Teguh Aryo Nugroho 2023-12-31 2023-12-31 2 2 67 71 10.20473/jatm.v2i2.53423