Bahtiar Saleh Abbas

A System for Real-Time Passenger Monitoring System for Bus Rapid Transit System

TransJakarta is a BRT-based mass transportation system operating in Jakarta, the capital of Indonesia. Currently, the system delivers rather low level of service; as a result, the number of passengers is rather low in comparison to that of the other BRT-based systems. In this work, we propose a design of the passenger counting system for BRT-based system, which is very important for the BRT fleet management to increase the system level of service. The counting system is established by deploying computer vision techniques. A few algorithms are evaluated and the Adaptive Median Filtering with the sampling rate of 13 produces the highest level of precision and recall.

EXPERT-SYSTEM BASED MEDICAL STROKE PREVENTION

Stroke always comes unexpected and the general public is not usually aware of its symptoms. Individual s who have had their first stroke with permanent dama ge could become an economic burden to their family and a social burden to the society due to their unp roductive nature. Stroke could be prevented and its risk factors have been identified. Through a stroke prev ention information system, the user could be made more aware of stroke risks and symptoms. An expert syste m would be able to direct and motivate users to kee p themselves healthy therefore preventing first and r ecurrent strokes. The expert system is built using an inference engine that provides stroke risk level ba sed on information provided by the user. Informatio n collected are self measured blood pressure, cigaret tes consumed, amount of physical activity and body mass index. Users are presented with suggested preventiv e tasks to reduce their stroke risk.

Innovation of Human Resources Development by M-Learning to Support Cross-border Tourism Event in Natuna

Natuna has a great potential of natural resources, and its main potential is tourism. The development of cross-border tourism is in line with Jokowi-Jusuf Kallas nine priorities. However, the obstacle in tourism is human resources who fluently speak foreign languages in marketing and communicating with foreign tourists, especially in the border area. Since Natuna is far and difficult to reach, no Natunas university educates their human resources to speak a foreign language and because Natuna is also lack of foreign teacher. Therefore, it needs a breakthrough in foreign language learning through mobile learning applications. As smartphones are commonly used in society, the solution of foreign language learning through smartphone application became an innovation in education and training. The research method was Focus Group Discussion (FGD) between officials of Natunas Regional Planning, Research, and Development Agency. The FGD was done by showing the design of interactive mobile applications for foreign language learning, especially English and Mandarin. The design of this application has been demonstrated in the FGD activities and has received a positive response. The conclusion of this research is Mobile Learning application is a foreign language learning solution to support tourism activities in Natuna.

Mobile usability: An antecedent for influencing purchase intention moderated by omni-channel integration quality

The new concept of omni-channel has inspired researchers to develop a model of consumer confusion to increase purchase intention. Previous studies were tested that the omni-channel integration quality can improve customer satisfaction. As a novelty, this study introduced omni-channel integration as a moderating variable that influence consumer confusion to the intention of purchase. This paper constituted a hypothetical development about the proposed omni-channel integration as a part of the e-quality service. This proposed research aimed to explore the effect of consumer confusion towards purchase intention moderated by omni-channel integration. Three hypotheses were modeled in this research proposal. The future results of this research are expected to be a significant contribution towards business, science, and society.

An Expert System to Assist with Early Detection of Schizophrenia

Schizophrenia is one of neurobiological disorders whose symptoms appear in young age. Psychiatrists use client-centered therapy to recognize five symptoms of schizophrenia. They comprise: delusions, hallucinations, negative symptoms, grossly disorganized or abnormal motor behavior, and disorganized thinking and speech. Patients experiencing their acute psychotic episode must be quarantined to prevent their unsocial behavior. An early detection of the schizophrenia symptoms is necessary to avoid acute psychotic episodes. An expert system to aid in diagnosing early schizophrenia symptoms is presented in the paper. The system represents psychiatrist knowledge in the form of rules, facts and events and uses them to assess whether a patient suffers from schizophrenia. The knowledge-base is displayed in the form of questions to the patient. The expert system uses forward chaining while gathering the answers from patient. All answers are transformed into facts and processed using Boolean reasoning to generate the diagnosis. The diagnosis states whether the patient has schizophrenia, and if so, it indicates also the type of schizophrenia.which

Online trust building through third party trust transfer and third party protection

The primary objective of this research is to develop an online trust building mechanism for SME (Small Medium Enterprise). Trust is very important in e-commerce. The nature of online shopping has a greater uncertainty than offline shopping. Seeing as there is an uncertainty that can produce risks, a prospective buyers trust is needed. A lot of peoples unwillingness to shop online is caused by their lack of trust toward e-commerce. E-commerce is said to be one of the ways for SME to compete with bigger companies. However, building trust requires immense time and cost. SME with limited resources may experience difficulties in building trust just with their own resources. Base on literature research that needs to be validated in next research, we found that trust can be built through trust transfer from the reputable and well-known trust-mark issuer, and third party protection such as escrow account service and credit card issuer.

The Role of Social Media User Experience as a Mediator for Understanding Social Media User Behavior in Indonesia?s Museum Industry: Literature Review

Social media has changed the interaction between the customer and the business, social media has proven to provide new opportunities in facilitating access to information, efficiency and ease of interaction between customers and businesses that are distributed geographically dispersed. Ease of interaction to improve access to information about products, services, and prices have proven to have a positive impact for consumers. The purpose of this article is to develop a conceptual model to test the effect of user motivation, user expectations, and online community involvement to the intention of behavior that is mediated by the use of social media museum experience. This article is a literature study on exploration of social media user experiences museum in Indonesia. Authors searched and examined 85 articles from google scholar with the following keywords: motivation, expectations, online communities, user experience, social media, Technology Acceptance Model, Experiential Marketing, Uses and Gratification Theory. Proposed data collection techniques are literature study, survey and observation. The sample used in this research is 400 respondents of social media users that follow the social media managed by Indonesias museum. The sampling technique are systematic sampling. We use Structural Equation Model with AMOS for analyze the data.

Recognizing debit card fraud transaction using CHAID and K-nearest neighbor: Indonesian Bank case

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.

Two-Way ANOVA with interaction approach to compare content creation speed performance in knowledge management system

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.

A New Method for Calibrating Gazis-Herman-Rothery Car-Following Model

Traffic simulation at the microscopic level utilizes car-following model to describe vehicle interactions on a vehicular lane. The most widely used car-following model is the Gazis-Herman-Rothery model, which contains two coefficients: m and l. The coefficients should be determined in calibration tests where the involved vehicles are tracked for their positions, velocities, and accelerations. The existing calibration methods are costly. This study proposes a calibration method using computer vision. Two computer vision algorithms are evaluated, namely, multilayer and Eigen background subtraction. The vehicle movement is tracked on a perspective plane and then is projected to an orthogonal plane. From the verification tests, we determine that the multilayer algorithm has 96.6 % accuracy for the vehicle position and 88.9 % for the velocity. The Eigen algorithm has 92.9 % accuracy for the vehicle position and 84.3 % for the velocity. The estimated model coefficients is 0.4 for m and 1.2 for l. These values are within the range of the most reliable coefficients according to many literatures.