IJITEE (International Journal of Information Technology and Electrical Engineering)
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User Curiosity Factor in Determining Serendipity of Recommender System
Full text linkRecommender rystem (RS) is created to solve the problem by recommending some items among a huge selection of items that will be useful for the e-commerce users. RS prevents the users from being flooded by information that is irrelevant for them.Unlike information retrieval (IR) systems, the RS system's goal is to present information to the users that is accurate and preferably useful to them. Too much focus on accuracy in RS may lead to an overspecialization problem, which will decrease its effectiveness. Therefore, the trend in RS research is focusing beyond accuracy methods, such as serendipity. Serendipity can be described as an unexpected discovery that is useful. Since the concept of a recommendation system is still evolving today, formalizing the definition of serendipity in a recommendation system is very challenging.One known subjective factor of serendipity is curiosity. While some researchers already addressed curiosity factor, it is found that the relationships between various serendipity component as perceived by the users and their curiosity levels is still yet to be researched. In this paper, the method to determine user curiosity model by considering the variation of rated items was presented, then relation to serendipity components using existing user feedback data was validated. The finding showed that the curiosity model was related to some user-perceived values of serendipity, but not all. Moreover, it also had positive effect on broadening the user preference.
Piezoelectric Energy Harvester for IoT Sensor Devices
Full text linkLimited 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
Comparison of Electrical Conductivity Prediction Models Using Gaussian Process
Full text linkPeople 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
Dimmable High Power LED Driver Using Fuzzy Logic Controller
Full text linkThe use of lighting loads is one of the crucial matters which increases every year. The increasing use then leads to the development of brighter and longer-lasting sources. In addition, the conventional use of lighting loads today, which only emit light at its maximum intensity, does not allow the consumers to adjust the brightness level as needed. Consequently, this condition may cause energy wastage. The LED lighting system is gaining popularity as it is widely used in a wide range of applications. The advantages of LEDs, such as its compact size and varied lamp colors, replace conventional lighting sources. The linear setting of the driver topology using the flyback converter was aimed to control the LEDs with a constant current in order to adjust the variation of the LED light intensity. The closed-loop driver circuit with flyback converter topology was designed as an LED driver with a given load specification from the LED string. A dimmable feature was included for adjusting the intensity of the light produced by the LEDs. Eventually, the fuzzy logic controller (FLC) method was applied to the integrated change setting to obtain a dynamic response
The Evaluation of AR Mobile App as a Learning Media for Children
Full text linkA user evaluation stage is an integral part of designing an application. A practical evaluation can provide an overview of the problems that arise in the application and improve the user experience. The Kupuku application is an augmented reality (AR)-based game application for learning about butterflies. The Kupuku application is specifically intended for children aged 6-13 years. The user sample was selected using a purposive sampling method with the criteria for users of elementary school-age children for the child user segment and their companions as the adult user segment. This study aims to evaluate the usability of the Kupuku game application to users. User evaluation was carried out to measure the application’s usability. The evaluation process was conducted on two user segments, namely 20 child users and 16 adult users. Assessment of children employed the Fun Toolkit and usability factor-based question - Nielsen method. The obtained results showed positive feedbacks. In contrast, the assessment for adult users utilized the system usability scale (SUS) and the user experience questionnaire (UEQ). The SUS score of 76 was included in the good category, and the UEQ score produced an excellent average. The test results indicate that this application can be accepted by users, both children, and adults
Kalman Filter to Improve Performance of PID Control Systems on DC Motors
Full text linkA proportional–integral–derivative (PID) controller is a type of control system that is most widely applied in industrial world. Various tuning models have been developed to obtain optimal performance in PID control. However, the methods are designed under ideal circumstances. This means that the control system which has been built will not work optimally when noise exists. Noise can come from electrical vibrations, inference of electronic components, or other noise sources. Thus, it is necessary to design PID control system that can work optimally without being disturbed by noise. In this research, Kalman filter was used to improve the performance of PID controllers. The application of Kalman filter was used to reduce the noise of the input signal so that it could generate output signal which is in accordance with the expected output. Simulation result showed that the PID performance with Kalman filter was more optimal than the ordinary one to minimize the existing noise. The resulting speed of DC motor with Kalman filter had a lower overshoot than PID control without Kalman filter. This method resulted lower integral of absolute error (IAE) than ordinary PID controls. The IAE value for the PID controller with the Kalman filter was 25.4, the PID controller with the observer was 31.0, while the IAE value in the ordinary controller was only 60.9
A Microstrip Antenna Design Using an Heuristic Algorithm
Full text linkMicrostrip antennas have several advantages. Some of them are that they have a compact shape and small dimensions. Moreover, they are also easy to be fabricated and easily connected as well as integrated with other electronic devices. Currently, designing antennas conventionally is limited by time, energy, and experience as well as expertise. As an alternative, a way to design antennas with revolutionary methods is developed using algorithms and computing. Algorithm design techniques can overcome limitations and automatically find practical solutions that usually take a long time to discover. The particle swarm optimization algorithm and a genetic algorithm can find solutions from microstrip antennas. Objective functions play an essential role in heuristic algorithms. With a proper objective function, simulation results are obtained on the particle swarm optimization algorithm with a return loss value of -47.837, VSWR of 1.0083, and impedance of 46.805 Ω. In contrast, the genetic algorithm obtains return loss of -16.157 dB, impedance of 50.233 Ω, and VSWR of 1.3687
A Multi Criteria Decision Making to Support Major Selection of Senior High School
Full text linkSenior high school students need to select a specialization, such as Mathematics and Natural Sciences, Social Sciences, or Language and Culture. This selection process can be improved by using Multi Criteria Decision Making (MCDM) methods. When MCDM methods are implemented, AHP method has accuracy of 61%, whereas AHP-Fuzzy TOPSIS 1 and AHP-Fuzzy TOPSIS 2 have accuracy of 75%. This research implements tests and analyzes new MCDM method, which is Hybrid MCDM Model, in helping aforementioned specialization selection process. There are four basic steps in Hybrid MCDM Model: performing experimental design to obtain attributes' weight and criteria, evaluating MCDM with the three existing methods, performing RSM regression to derive mathematical model, and decision making. This research introduces data normalization to the mathematical model which results in better implementation of Hybrid MCDM Model in the senior high school students' specialization selection process. Hybrid MCDM Model in the senior high school student specialization selection has accuracy of 86%, which includes 11% accuracy improvements compared to other applied MCDM methods
The Effect of Parasitic Rings and Ground Plane on Helix Strip Antenna
Full text linkStrip helix antennas offer better performance at wide bandwidth and more compact in size than conventional helix antennas. However, strip helix antennas have a relatively low gain compared to conventional helix antennas. In this paper, a strip helix antenna with 2.4 GHz frequency was designed, simulated, fabricated, and measured. This strip helix antenna was added with several parasitic rings, and its ground plane size was reduced to increase the gain value and its performance. The best simulation results according to the desired parameters were with return loss 12 dB with the result of 8.9612 dB. Measured results showed that the helix strip antenna has a return loss of -10.37 dB and VSWR of 1.870. The parasitic rings addition can increase the strip helix antenna gain of 0.0201 dB and improves performances of return loss, VSWR, and bandwidth. Despite that, the ground plane size reduction actually decreases the gain value
Asymmetric-Slit Method on WiFi Antenna with 2.4 GHz and 5 GHz Frequency
Full text linkWireless Fidelity (WiFi) devices are often used to access the internet network, both for working and in information searching. Accessing the internet can be administered anywhere provided that the area is within the WiFi devices range. A WiFi device uses 2.4 GHz and 5 GHz operating frequencies. There were several methods employed in the previous studies so that an antenna design could work in two different frequencies, i.e., winding bowtie method, Sierpinski method, and double-circular method. This paper employed a simple method, the slit method. The objective of this paper is to discover a simple antenna model that works on 2.4 GHz and 5 GHz frequencies. This paper employed a square patch microstrip antenna with a slit method. The dimensions of the designed square patch microstrip antenna were 42.03 mm × 27.13 mm × 0.035 mm. The antenna worked at 2.4 GHz and 5 GHz frequencies. The obtained simulation results after the optimization showed that the square patch microstrip antenna using the slit method acquired a value of S11 (return loss) of -10.15 dB at a frequency of 2.4 GHz and -37.315 dB at a frequency of 5 GHz