To prevent the spread of COVID-19, face-to-face meetings have moved online to avoid human contact. Although the online format has made it easier for people to participate in meetings, consensus building in meetings has become increasingly more difficult since the speakers are in different locations. Notably, there is a difference in the way people applaud in online meetings. In addition to clapping and making sounds as in face-to-face meetings, people have turned to new methods of communicating online, such as clapping and gesturing on the screen. For this study, we categorized online meetings into four categories: “with applause,” “without applause,” “gesture/mark presentation only,” and “with applause and a gesture/mark.” We then compared the effect of applause with the emotional information read from each person's face through microexpressions. The results indicate a significant difference in feelings of sadness over two kinds meetings as an effect of applause and gestures, which had a positive effect, facilitating future online communication. Keywords—clapping hands, online meeting, gesture, consensus, microexpression I. INTRODUCTION Applause is the most respectful way to express agreement and is considered to be the most respectful way to build consensus. With the rapid proliferation of online meetings in the midst of the COVID-19 crisis, the difference between a face-to-face meeting and an online meeting is fading. To compensate for this change, people in online meetings are using symbols, such as applause icons and pictographs, to express approval and supplement consensus building. In an example of remote applause, a remote-controlled robot clapping with a human has been reported to have a positive effect. Similarly, when clapping is presented remotely through a screen, humans are predicted to react positively [1]. Regarding the role of human emotions in social influence, Pankaj stated that participants in a meeting within a small network are influenced by the emotional information conveyed by people at influential nodes within that network, which is then transmitted to other participants in that network. In this study, we compared the effects of applause for four types of online meetings that appeared within the top three pages of a YouTube search: “with applause,” “without applause,” “gesture/mark presentation only,” and “with applause and a gesture/mark.” We then compared the effects of applause with the emotional information read from the faces through micro expressions. II. RELATED WORK First, as a consensus-building system in a meeting, Ito et al.'s system uses artificial intelligence to collect positive keywords and remove negative ones. To help people agree on a lecture, the system aggregates words from among the many opinions discussed in the meeting and suggests whether the words were hot topics. This system can be used in online meetings as well. The present study predicts that, by adding emotional information to the words uttered by humans in the consensus-building system, people's opinions can be compared not only based on words but also emotional information. For example, it is predicted that people will use heart symbols for favorable opinions and teardrop symbols for less favorable opinions. The analysis of human facial information from this YouTube meeting also serves as a preliminary experiment to provide emotional information to help people reach a consensus.
Using spreadsheet software, users may do some forms of programming using formula and function. However, formula definition is often considered correct after tested with only one or few inputs. This may be fine with simple formula, but for more complex ones, more testings should be performed, in order to prevent solution that riddled with errors. However, writing a formula test case in spreadsheet software is not a simple task, mainly because there is no standard way to do that. In this paper, a simple spreadsheet test case application is proposed. User can define a formula, with many input variants, along with expected results. After that, application will generate a spreadsheet document, with all the needed contents for testing, along with test result. That way, user may re-check the formula and make necessary modifications (then run the test, again). Using this method, a formula can be tested first, with many input as needed, before it put in real document. All of these will impact in more productive programmers, with less time spent for debugging.
Recently, there is a rapidly growth of digital startup companies in Indonesia, but at the same time many of which are not successful. One of the main factors is the implementation of the project management related for product and services. This paper discusses how project management as a model able to increase success rate of digital startup project. The research data was obtained from a questionnaire with the criteria of the company in the sector of digital content providers. In this study, researchers conducted a test model of project management combined 10 knowledge areas of Project Management with the Triple Constraints using smartPLS approach Start Equation Model (SEM) to determine the model tested is significant with the data available today can improve a project's success digital start-up company.
Object instance recognition enables the realization of many potential applications, such as information retrieval, scene understanding and human computer interaction. However, it is still a challenging problem in computer vision. The appearance of an object is affected by variations in illumination, viewpoint and occlusion. In this contribution, we propose an object instance recognition method based on Best Increasing Subsequence. It estimates a set of geometrically consistent feature pairs and at the same time, maximizes the total similarity score between test and train images. Our experimental results show that the proposed method outperforms the existing geometric verification methods, RANSAC Homography and Weighted LIS.
We picked up the “endophyte” business of Maekawa Mfg. (Maekawa). The “endophyte” is the generic name of a large number of microbes living together in the plant. Several types of endophytes are present in the plant, the plant will have become stronger effect on pests and diseases. Maekawa's business is one of the successful examples by the co-creation process. We have applied effectively the KJ method for the theme code search based on database of the Patent Information into the co-creation process between the three parties of the university, the industry and government. The KJ method has been developed as a scientific idea method of the field, we catch the F-term of the patent information classified as ecosystem. We inspected the effectiveness of the KJ method application for the collaborative theme search to lead to the discovery of the innovation opportunity with patent information. As a result, we showed the Availability of the KJ Method Application for the collaborative theme search based on database of the Patent Information in Maekawa's business.
Information involves in design process, and in fact designing is an activity of converting data, information and knowledge into a map and guidance of creating an artifact. Unfortunately, the existing instruments that supporting designers' information search do not fit to them in term of their naturally way of doing so. This research is aimed at developing an information search application purposely for designers especially in the creative design process. And this paper will focus on the development and implementation a so called Search Result Side Note application.
Nowadays, mobile operators are faced with difficult conditions, where subscriber growth rate is already at its peak. Revenue growth is also declined because legacy services are tend to decreased due to threat from OTTs. Therefore we need a strategy to be able to withstand these conditions, one of which is a glance at the digital market. Strategy to offer digital services is developed in order to increase operators' revenue through offering of Machine to Machine (M2M) services, where potential and digital ecosystem support of those services is promising. In reality, implementation of those digital services is not yielding significant effect on operators' revenue growth, thus they need new strategy with a new service innovation. This research aims to modeling an M2M services, into a Smart Connected Motorbike (SCM) services. Furthermore, this research also analyzes business model implementation of this service as a study case at PT.XYZ, where this service is expected to become a new revenue source. From system modeling result and business model analysis, it is revealed that implementation of Smart Connected Motorbike services practices multi-sided platform business model pattern that brings together two different groups of customers which are motorbike users/buyers and corporate customers. Moreover, this research analyses four business models approach to find appropriate implementation models of Smart Connected Motorbike services and additional revenue opportunities for PT.XYZ.
This article presents a data audit system, which confirms that proper use of data is performed on the iKaaS platform (intelligent Knowledge as a Service) platform. The proposed data audit system can alleviate ambiguous anxiety of data owner about unauthorized use by providing measures to understand that illegal use of data cannot occur. This achievement is expected to support the construction of the data use environment and encourage the discovery of novel knowledge.
For future success in business, students study diligently and acquire significant amounts of specialized knowledge at the university. In the real business world, specialized knowledge alone is insufficient to produce or find business solutions. Therefore, they must learn corporate management. Nevertheless, it is hard to teach corporate management to students during a short time at the university level using conventional teaching methods alone. As one of the methods to solve the problem, the authors attempt to apply BASE business games, participation-type education technique, to the teaching of elementary corporate management as experimental. In this paper, the authors introduce a concept of SCC and SCC2 games, which is one of BASE business games. As one trial case, the authors apply them to the lecture of SIIT Thammasat University and conduct the questionnaire research for checking the effectiveness of this teaching method. These results show that students learned elementary corporate management and acquired a holistic view of directorate as experimental. Therefore, this teaching method is suitable for grasping elementary corporate management.
Data visualizations are often generated to reflect the intentions of their creators. Readers of such visualizations cannot always obtain the information they want, because there is often a gap between the creators' intentions and readers' interests. To bridge such gaps, we propose passing the initiative of visualizing data to the readers. For most readers, who are not experts in visual representations, it can be difficult to design or to choose the appropriate options for visualizations that meet their needs; therefore, we consider a system that utilizes readers' interest. We organized problems to develop a framework for passing the initiative for visualizing data to readers. Moreover, we devised a method for express visual representations from the viewpoint of readers' interests. Through a thought experiment, we investigated the aspects of data that readers are interested in, and propose a formal expression for that interest.
This paper describes the design of a distributed brainstorming support tool focusing on gamification. In previous studies, there are very few studies focused on continuous creative activities. Gamification elements in the distributed brainstorming tool are aimed at maintaining intrinsic motivation toward continuous creative activities. The activities for gamification elements are earning points by idea generation, create a avatar with the earned points, and competing with other players for total points. We show interface design of gamification for distributed brainstorming, and then describe a plan of control experiments to demonstrate hypothetical effects of the gamification, such as maintenance of idea generation by intrinsic motivation.
Speed performance is important in the process of creating content on the Knowledge Management System. Bina Nusantara (BINUS) University has implemented Knowledge Management System (KMS) since 2002. This study examined the speed performance of content creation in four modules of BINUS University KMS: Documents, Video, Material, and Binuspedia. The examined to get mean value of speed performance was conducted in 3 location campuses of BINUS University: Anggrek Campus, Syahdan Campus and Alam Sutera Campus, each was done with five repetition. The speed performance was analyzed using Two-way ANOVA with interaction approach. According to the experiment results, F calculated for module is greater than F table, F calculated for campus is less than F table and F calculated for interaction is less than F table. Thus, the conclusions are: (1) there are differences in the average value of speed performance for each module, (2) there is no difference in the average value of speed performance for each campus, and (3) there is no interaction between campuses and modules on the speed performance.
This paper presents a preliminary study on debit card fraud transaction recognition, whose cards are issued by Indonesian bank, based on actual ATM transaction records. The premise of this research is fraudulent transaction contains ‘anomaly’ from the pattern of non-fraudulent transactions so that the anomalous pattern can be detected and separated at some point using classification models. Less availability dataset for research, non-stationary distribution of the data, highly imbalanced class distributions, and continuous streams of transactions become the main driven of using CHAID and k-NN classification method. Empiric result using actual debit card transaction using ATM services shows that Accuracy of CHAID model is 0.8 and F = 0.7; and k-NN model (for k=3) is 0.7 and F = 0.6 These results are comparable to previous studies using Hidden Markov Models.
Clustering is a task to divide objects into group depends on their similarity. The optimal of solving clustering problem occurs when the data joins in one group which has a similar category. This study combines Adaptive Genetic Algorithm, K-Means and Greedy Selection to solve clustering problem, named RAGKA. In first step, the centroid is determined by K-Means. Crossover and mutation are performed based on the fitness value of each centroid. At last, the greedy search is operated to get the better solution. To show the performance of RAGKA, five data sets of clustering problem are used. Moreover, RAGKA is compared with other methods as well. The result shows that RAGKA is successfully to solve cluster problem and outperforms than the others.
The research analyzed the existing infrastructure, designed and developed KMS required by company, designed KMS application prototype as a media to document knowledge and facility supporting a knowledge sharing culture at PT Bussan Auto Finance, as well as cultural organization and the main component of KM. Analysis of the process was done to determine business processes run on the main division. Analysis applied 7 first steps method defined by Tiwana in doing KMS application prototype. Data were obtained by observation, interviews with the division head, and distributing questioners that concerned with organizational culture, components of KM analysis, and prototype design evaluation. It can be concluded that the design of KMS prototype produces five modules such as, Document Library, Blog, Discussion Forum, Knowledge Base, and Helpdesk. The result of prototype evaluation indicates the value gains 37.14, it shows effective value that is above average, therefore, the design of the prototype KMS application has been able to meet for 74.29% of the purpose and benefits of the prototype. The prototype of KMS application needs a continuous improvement coordinated by the company's managers.
Cultural heritage plays an important role in preserving social characteristics and knowledge for future generations. To provide long-term access to these resources, many cultural materials are today archived digitally. The problem arises when each cultural archive, which has own a large database, has been collected with the same cultural types, but different proposes, Therefore, there are various metadata standards that come from each of these archives, making it difficult to enhance, refine, or even improve raw data. This necessitates the need for a novel framework to integrating various subjects and metadata standards as well as extracting relationship among archives for enriching information retrieval. In this paper, we propose a new approach for discovery semantic relations between entities from articles using Wikipedia and various cultural heritage archives as resources. There are (1) dictionary extraction patterns used for extracting terms and meaning for creating a cultural heritage dictionary and (2) semantic relation extraction for extraction relation following question words. For enriching cultural information, the method for enriching cultural heritage information with the result of semantic relation extraction is presented using semantic string similarity matching. An evaluation of different domains shows high performance of the proposed approach.
Bluetooth Low Energy (BLE) or Bluetooth Smart is a wireless device that can be connected to many wireless devices with many applications. In this paper, we analyzed the accuracy of BLE for measuring distance in order to build the indoor positioning application. The problem of BLE in distance measurement and indoor position are low accuracy that is caused by the fading effect. We discussed about the effect of changing the value of advertising interval to the accuracy of distance measurement by application, between BLE as a Transmitter and a Smartphone with Android OS as a receiver. The result showed that the accuracy of distance measurement will increase if the value of advertising interval is decreased.
Healthy lifestyle is an important requirement for people, which is obtained from balanced nutrition. Imbalanced nutrition increases risk of health problems. Balanced nutrition means the difference between nutrition needed and nutrition intake must be as minimum as possible. The condition in Indonesian, many people consume food with high carbohydrate; whereas nutrition consists of protein, carbohydrate, and fat. That nutrition obtains from five foods category, namely: main dish (MP), vegetable side dish (LN), meat (LH), vegetable (SY), and fruit (BH). Therefore, it needs a system to provide a suggestion for balanced nutrition. This research used Artificial Bee Colony (ABC) to obtain optimal nutrition, which contains five dimensions (MP, LH, LN, SY, BH). These dimension and variable are represented as food source, which will be optimized by bees. These bees are divided into employee bee (BN), onlooker bee (SN), and scout bee. BN will produce new food source, where if new food source has a better solution, it will replace the old one. SN performers based on the fitness value of each food source; if the food source has high probability, SN will produce new food source. While scout bee will determine a new food source, if the number of trials for releasing a food source is equal to the value of “limit”. The performance of ABC evaluated using twelve data of men and female. The result shows that ABC achieve 99.90% in giving a recommendation for portion and type of foods a day.
Universities are required to prepare the best quality graduate. Therefore, they will be ready to contend and to be an ambitious individual in the real world. All graduates are judged by their Grade Point Average (GPA). Therefore, in Indonesia, it is critical to maintaining a good GPA from the first semester until the graduation. Although the student is the main actor, it is not only their job to maintain the GPA. The good-grade university also needs to participate by helping them to get the best help and environment during the lecture. The university should able to create conducive learning environment to support and to help undergraduate students in maintaining a good GPA. The purposes of this paper are to identify and analyze the factors that affect a good performance of student's GPA, to give suggestions to education institution as a preventive action of low performance of student's GPA, and to design a successful model to achieve good GPA. Methodologies used in this paper are literature study, analysis at the University, model trial, and giving the result and solutions.
Automatic emotion recognition from human speech signal has many important practical applications. For the reason, a number of studies has been performed on the basis of English, German, Mandarin, Persian, and Danish languages. This work intends to develop automatic emotion recognition system on the basis of speech signal in Indonesia language. The study is limited to four emotional states, namely, happy, sad, angry, and fear. The speech data are collected from amateur actors and actresses, and are further quantified using Mel-Frequency Cepstral Coefficient to provide 48 emotion-related features. Finally, these features are used for emotion classification using Support Vector Machine method. The results suggest that the recognition can achieve about 86% of the level of accuracy.
