Eye Blink Classification for Assisting Disability to Communicate Using Bagging and Boosting

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.

Product Recommendation Based on Eye Tracking Data Using Fixation Duration

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.

Factors Affecting Collaboration Portal Effectiveness of the Audit Board of Indonesia

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.

Optimal Capacity and Location Wind Turbine to Minimize Power Losses Using NSGA-II

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.

Piezoelectric Energy Harvester for IoT Sensor Devices

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.

The Evaluation of AR Mobile App as a Learning Media for Children

A 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

A 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.

User Curiosity Factor in Determining Serendipity of Recommender System

Recommender 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.

Topic Modeling in the News Document on Sustainable Development Goals

Indonesia is a developing country and supports the program of the Sustainable Development Goals (SDGs) which consist of 17 goals. SDGs is not only the government’s duty, but a shared duty from any elements. Online media has a crucial role in implementing goals of Indonesia’s SDG. Information published in online news related to the SDGs is an important consideration for the government, society, and all elements. Categorizing news manually to find out news topics is very time-consuming and done by the ability of news editors. News presented by online media on the news site can be used as topic modeling, where hidden topics can be found in the news on online media. Topic modeling will classify data based on a particular topic and determine the relationship between text. Latent Dirichlet allocation (LDA) is one of the methods on topic modeling to find out the trend of topics of SDGs news. Based on the result of this research, the implementation of LDA is the right choice for finding topics in a document. The result of topic modeling with k = 17 obtained the highest coherence score of 0.5405 on topic 8. Topic 8 discussed news related to the eighth SDGs goals, namely decent work and economic growth. This categorization was based on words formed after the LDA process. Then, topic 5 discussed the news on the 17th SDGs goals, namely partnerships for the goals. Topic 6 discussed the news of the first SDGs, namely no poverty.

Improving Data Quality and Data Governance Using Master Data Management: A Review

Master data management (MDM) is a method of maintaining, integrating, and harmonizing master data to ensure consistent system information. The primary function of MDM is to control master data to keep it consistent, accurate, current, relevant, and contextual to meet different business needs across applications and divisions. MDM also affects data governance, which is related to establishing organizational actors’ roles, functions, and responsibilities in maintaining data quality. Poor management of master data can lead to inaccurate and incomplete data, leading to lousy stakeholder decision-making. This article is a literature review that aims to determine how MDM improves the data quality and data governance and assess the success of MDM implementation. The review results show that MDM can overcome data quality problems through the MDM process caused by data originating from various scattered sources. MDM encourages organizations to improve data management by adjusting the roles and responsibilities of business actors and information technology (IT) staff documented through data governance. Assessment of the success of MDM implementation can be carried out by organizations to improve data quality and data governance by following the existing framework.