IJITEE (International Journal of Information Technology and Electrical Engineering)
https://jurnal.ugm.ac.id/ijitee
International Journal of Information Technology and Electrical EngineeringDepartment of Electrical Engineering and Information Technology,Faculty of Engineering UGMen-USIJITEE (International Journal of Information Technology and Electrical Engineering)2550-0554<h3>Copyright Form IJITEE</h3>Please click <a href="/ijitee/pages/view/copyrightijitee">here</a><br /><p> </p><a href="http://creativecommons.org/licenses/by-nc-nd/4.0/" rel="license"><img style="border-width: 0;" src="https://i.creativecommons.org/l/by-nc-nd/4.0/88x31.png" alt="Creative Commons License" /></a><br />This work is licensed under a <a href="http://creativecommons.org/licenses/by-nc-nd/4.0/" rel="license">Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License</a>.Product Recommendation Based on Eye Tracking Data Using Fixation Duration
https://jurnal.ugm.ac.id/ijitee/article/view/58693
E-commerce can be used to increase companies or sellers’ profits. For consumers, e-commerce can help them shop faster. The weakness of e-commerce is that there is too much product information presented in the catalog which in turn makes consumers confused. The solution is by providing product recommendations. As the development of sensor technology, eye tracker can capture user attention when shopping. The user attention was used as data of consumer interest in the product in the form of fixation duration following the Bojko taxonomy. The fixation duration data was processed into product purchase prediction data to know consumers’ desire to buy the products by using Chandon method. Both data could be used as variables to make product recommendations based on eye tracking data. The implementation of the product recommendations based on eye tracking data was an eye tracking experiment at selvahouse.com which sells hijab and women modest wear. The result was a list of products that have similarities to other products. The product recommendation method used was item-to-item collaborative filtering. The novelty of this research is the use of eye tracking data, namely the fixation duration and product purchase prediction data as variables for product recommendations. Product recommendation that produced by eye tracking data can be solution of product recommendation’s problems, namely sparsity and cold start.Juni Nurma SariLukito Edi NugrohoPaulus Insap SantosaRidi Ferdiana
Copyright (c) 2021 IJITEE (International Journal of Information Technology and Electrical Engineering)
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2021-12-242021-12-245410911610.22146/ijitee.58693Eye Blink Classification for Assisting Disability to Communicate Using Bagging and Boosting
https://jurnal.ugm.ac.id/ijitee/article/view/63515
Disability is a physical or mental impairment. People with disability have more barriers to do certain activity than those without disability. Moreover, several conditions make them having difficulty to communicate with other people. Currently, researchers have helped people with disabilities by developing brain-computer interface (BCI) technology, which uses artifact on electroencephalograph (EEG) as a communication tool using blinks. Research on eye blinks has only focused on the threshold and peak amplitude, while the difference in how many blinks can be detected using peak amplitude has not been the focus yet. This study used primary data taken using a Muse headband on 15 subjects. This data was used as a dataset classified using bagging (random forest) and boosting (XGBoost) methods with python; 80% of the data was allocated for learning and 20% was for testing. The classified data was divided into ten times of testing, which were then averaged. The number of eye blinks’ classification results showed that the accuracy value using random forest was 77.55%, and the accuracy result with the XGBoost method was 90.39%. The result suggests that the experimental model is successful and can be used as a reference for making applications that help people to communicate by differentiating the number of eye blinks. This research focused on developing the number of eye blinks. However, in this study, only three blinking were used so that further research could increase these number.Luthfi ArdiNoor Akhmad SetiawanSunu Wibirama
Copyright (c) 2021 IJITEE (International Journal of Information Technology and Electrical Engineering)
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2021-12-242021-12-245411712310.22146/ijitee.63515Piezoelectric Energy Harvester for IoT Sensor Devices
https://jurnal.ugm.ac.id/ijitee/article/view/67120
Limited battery power is a major challenge for wireless sensor network (WSN) in internet of things (IoT) applications, especially in hard-to-reach places that require periodic battery replacement. The energy harvesting application is intended as an alternative to maintain network lifetime by utilizing environmental energy. The proposed method utilized piezoelectricity to convert vibration or pressure energy into electrical energy through a modular piezoelectric energy harvesting design used to supply energy to sensor nodes in WSN. The module design consisted of several piezoelectric elements, of which each had a different character in generating energy. A bridge diode was connected to each element to reduce the feedback effect of other elements when pressure was exerted. The energy produced by the piezoelectric is an impulse so that the capacitor was used to quickly store the energy. The proposed module produced 7.436 μJ for each step and 297.4 μJ of total energy with pressure of a 45 kg load 40 times with specific experiments installed under each step. The energy could supply WSN nodes in IoT application with a simple energy harvesting system. This paper presents a procedure for measuring the energy harvested from a commonly available piezoelectric buzzer. The specific configurations of the piezoelectric and the experiment setups will be explained. Therefore, the output energy characteristics will be understood. In the end, the potentially harvested energy can be estimated. Therefore, the configuration of IoT WSN could be planned.Noor Pratama ApriyantoEka FirmansyahLesnanto Multa Putranto
Copyright (c) 2021 IJITEE (International Journal of Information Technology and Electrical Engineering)
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2021-12-242021-12-245412412910.22146/ijitee.67120Optimal Capacity and Location Wind Turbine to Minimize Power Losses Using NSGA-II
https://jurnal.ugm.ac.id/ijitee/article/view/70161
Voltage deviations and power losses in the distribution network can be handled in various ways, such as adding diesel power plants and wind turbines. Adaut Village, Tanimbar Islands Regency, Maluku Province has installed a diesel power plant with a capacity of 1,200 kW, while the average hourly electricity load is 374.9 kW. Adaut Village has high wind potential that can be used for distributed generations namely wind turbine (WT). WT can be used to improve power quality in terms of power losses and voltage deviations. In adding WT, the capacity and location must be determined to get good power quality in terms of power loss and voltage deviation. The research applied an optimization technique for determining the capacity and location of WT using non-dominated sorting genetic algorithm II (NSGAII) with an objective function of power losses and voltage deviation. In addition, the economic aspects of the power plant were calculated using the levelized cost of energy (LCOE). The research used scenarios based on the number of WT installed. The best results were obtained in scenario IV or 4 WT with 1.38 kW on Bus 2, 422.43 kW on Bus 15, 834.33 kW on Bus 30, and 380.81 kW on Bus 31 which could reduce power losses by 80% with an LCOE value of Rp7,113.15/kWh. The addition of the WT could also increase the voltage profile to close to 1 pu, which means it can minimize the voltage deviation in the distribution network.Dieta Wahyu Asry NingtiasF. Danang WijayaLesnanto Putra Multanto
Copyright (c) 2021 IJITEE (International Journal of Information Technology and Electrical Engineering)
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2021-12-242021-12-245413013610.22146/ijitee.70161Factors Affecting Collaboration Portal Effectiveness of the Audit Board of Indonesia
https://jurnal.ugm.ac.id/ijitee/article/view/70144
The Audit Board of the Republic of Indonesia is known as Badan Pemeriksa Keuangan (BPK). In carrying out its duties and functions, it empowers and relies on information technology (IT) infrastructure that covers all aspects, including planning, procurement, service provision, information asset security, service continuity, and evaluation. BPK implements a collaboration portal to meet service needs and teamwork during the audit process, ad-hoc committees, and leader instructions to follow BPK’s strategic plan. BPK needs to assess the effect of the collaboration portal in supporting employee performance and improving IT services. As a result, this study aims to investigate the factors that influence the effectiveness of the BPK collaboration portal. This study used Delone and McLean model of information system success by looking at the relationship of system quality, information quality, service quality, facilitating conditions, and collaboration quality to user satisfaction and individual job performance. The research method used a quantitative approach with partial least squares-structural equation modeling (PLS-SEM). The sample data was collected from 60 respondents at BPK. The data obtained from the respondents were processed using the SmartPLS application. The study results show that information quality, facilitating conditions, and collaboration quality positively and significantly affect user satisfaction. There is a positive and significant influence of user satisfaction on individual job performance. In addition, system quality and service quality do not significantly influence user satisfaction with collaboration portal services.Afrialdi SyahputraPaulus Insap SantosaRudy Hartanto
Copyright (c) 2021 IJITEE (International Journal of Information Technology and Electrical Engineering)
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2021-12-242021-12-245413714410.22146/ijitee.70144Determining the Citizen Loyalty Factor of COVID-19 Website Using the Trust Model
https://jurnal.ugm.ac.id/ijitee/article/view/69894
<p class="Paragraf1">One of the information technology (IT) utilization by the government is the establishment of an official website for public access, designed to disseminate information about the COVID-19. Gaining public trust in the information dissemination is getting harder due to the amount of information, while the government is striving to provide reliable information. The service quality provided on the official website will affect the public’s trust and desire to use these services. Citizen loyalty is known when people intensively use the government electronic services because they believe in the government and its e-services based on perceived satisfaction and service quality. This research studied the effect of service quality, trust, and user satisfaction on user loyalty when using e-services by the Special Region of Yogyakarta (DIY) government. The study used a trust model developed by Alkraiji and Ameen and applied it to the official COVID-19 website. Data were collected from 100 respondents in the DIY who were in the productive age range. The experiment was carried out using explanatory and inferential techniques with multiple linear regression methods. The results of the study indicate that all model hypotheses are accepted. The relationship between antecedents and citizen loyalty was more influenced by trust in government and e-government. This finding explains why Yogyakarta citizen trust the government and its electronic services and will be loyal to use these services during the COVID-19 pandemic, as well as other facilities in the future.</p><div id="gtx-trans" style="position: absolute; left: -6px; top: -20px;"> </div>Azty Acbarrifha NourLukito Edi NugrohoPaulus Insap Santosa
Copyright (c) 2022 IJITEE (International Journal of Information Technology and Electrical Engineering)
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2021-12-312021-12-315414515110.22146/ijitee.69894Performance of MPSO-MPPT on PV-Based DC Microgrid in Partial Shading Conditions
https://jurnal.ugm.ac.id/ijitee/article/view/70449
Microgrid is a controllable decentralized group of energy resources and loads with the ability to operate both in grid-connected or island modes. Photovoltaic (PV) is one of the sources that are commonly used in microgrid. PV has a good ability to convert solar irradiation into electrical energy, especially under ideal condition, namely uniform irradiation or non-shading condition. However, PV often has some problems when facing partial shading condition. In this condition, PV does not produce optimal power because it stucks at the local maximum power point (MPP), thus it unables to track the global MPP. For this reason, it is necessary to implement a smart maximum power point tracker (MPPT) that can solve this problem. Furthermore, MPPT will be implemented in pulse width modulation (PWM) to control the buck converter. This study is focused on designing a laboratory scaled microgrid system with PV sources and controlled by modified particle swarm optimization (MPSO)-based MPPT. The 360 Wp PV array used consisted of two strings of three series modules Solarex MSX-60. The performance of the proposed method was compared with perturb and observe (P&O)-based MPPT, which was the commonly used method on MPPT. Furthermore, it was found that P&O and MPSO performed relatively similar accuracy (with difference of 0.04%) in non-shading condition. However, in partial shading condition, MPSO could perform better by producing greater output power so that it delivers better accuracy (98.74% to 99.11%) compared to P&O (57.95% to 71.87%). However, MPSO required a slightly longer time to converge because it had more complicated method and more computational load.Haneef Nouval Alannibras HumaidiMokhammad Isnaeni Bambang SetyonegoroSarjiya Sarjiya
Copyright (c) 2022 IJITEE (International Journal of Information Technology and Electrical Engineering)
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2021-12-302021-12-305415215810.22146/ijitee.70449Comparison of Electrical Conductivity Prediction Models Using Gaussian Process
https://jurnal.ugm.ac.id/ijitee/article/view/70684
<p class="Abstract"><span lang="EN-US">People living in coastal areas use clean water sourced from groundwater to support the household, agricultural, and industrial needs. However, human activities and natural factors can lead to a common problem in coastal areas, namely seawater intrusion. Seawater intrusion can be detected using water quality data. Today, one of the challenges in water resources management is the prediction of water quality parameters such as total dissolved solids (TDS), electrical conductivity (EC), and water turbidity. Incomplete EC data and limitations of direct measurements can affect the analysis. Machine learning models are known to provide the most accurate predictions. This research used EC parameter data to investigate the performance of algorithms, namely artificial neural networks (ANN), Gaussian processes (GP), and multiple regression (MLR). The prediction used seven hydrochemical parameters (K, Ca, Mg, Na, SO4, Cl, HCO3) and three physical parameters of groundwater (TDS, pH, EC). Performance measurement used R-squared (R2) and root mean squared error (RMSE). The testing showed the MLR model had R2 of 0.985 and RMSE of 0.030, which were slightly better than other models. Hence, it can be concluded that the MLR model can be a solution to difficult problems of EC prediction and incomplete data in the water resources management.</span></p>Zaenuri Putro UtomoIndriana HidayahMuhammad Nur Rizal
Copyright (c) 2022 IJITEE (International Journal of Information Technology and Electrical Engineering)
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2021-12-312021-12-315415916510.22146/ijitee.70684Load Flow Allocation to Improve the Fairness of MW-Mile Method
https://jurnal.ugm.ac.id/ijitee/article/view/70431
<p>In a deregulated power system, an appropriate wheeling cost is required to provide valuable economic information to market participants, such as generation and transmission companies. The load flow method is used in power wheeling to determine the condition of the existing system after the wheeling participant is added to the system. In the load flow method, it can be seen how much power is generated from a generator. However, the power flow method cannot determine wheeling generator allocation to the power flow in each transmission network. For this reason, power tracing will be used to determine the wheeling generator allocation. Power tracing is also a solution that could improve the fairness of determining wheeling costs. This paper discusses the power tracing method to determine load flow allocation for wheeling generators using the genetic algorithm (GA) method. GA is one of the optimization techniques, where in power tracing with GA, the load flow allocations (LFA) problem will be assumed as an optimization problem. Calculation with tracing and without tracing will be compared to demonstrate the benefits of the proposed technique. Experimental results showed that the MW-mile method with LFA yielded more expensive wheeling costs than the conventional method. The cost is more expensive due to the absence of cost reduction as in the conventional MW-mile method, and wheeling users pay wheeling costs based on the transmission usage. Although wheeling costs are high, the LFA method provides a fair price because wheeling users pay a fee based on the actual usage. In the future, another power tracing may be used to help determine wheeling costs.</p>M. Bagas SyaatnuartoroSasongko Pramono HadiSarjiya SarjiyaYusuf Susilo Wijoyo
Copyright (c) 2022 IJITEE (International Journal of Information Technology and Electrical Engineering)
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2021-12-312021-12-315416617210.22146/ijitee.70431