ABSTRACT
Indonesia experienced a COVID-19 pandemic starting in 2020. Limited mobility impacts various sectors, including tourism. Alian Butterfly Park is one of those affected. Alternatives were made to attract visitors, such as developing Augmented Reality applications to educate visitors about the new normal. Previous research developed a similar application, namely butterfly education with Augmented Reality technology, but its implementation still uses markers. It makes the user have to visit in person. This research improves the previous application. The improvement such as adding the interaction in AR butterfly life cycle, a virtual tour to collect butterflies, and the AR object is developed markerless. The application is developed using the agile development method. The application that has been developed is tested on the target user of the application. Testing is done by giving a black box testing. The test method is carried out by the black box testing method on 3 students. From the tests carried out, from a total of 25 test scenarios, there are 23 successful test scenarios and 2 test scenarios that fail due to bugs. The success value of the entire test scenario is 92% and the bugs found are 156 only affect the appearance of the application and do not affect the application critically. In addition, 2 scenarios are successful but are given special note due to environmental factors that can affect the results of the test. © 2022 IEEE.
ABSTRACT
SMPN 174 Jakarta is a junior high school in East Jakarta that has 719 students and 22 classrooms, including being one of the schools with government programs in the form of assistance such as Smart Jakarta Card, Smart Indonesia Program, and School Operational Assistance. To meet educational needs and distribute to students who are entitled to assistance. Currently, the selection process for student beneficiaries at SMPN 174 Jakarta is still done manually, so there is a risk of making decisions that are not on target and require a longer time. Therefore, a decision support system was made to select students who receive assistance. The development of the decision support system used in this research is the Multi-Objective Optimization Method on the Basic of Ratio (MOORA). The tests include black-box testing and comparison testing of calculation results with manual calculations. The Decision Support System for Selection of Student Recipients for the Impact of COVID-19 has been successfully created, and the results of selecting recipients of this assistance are obtained based on the calculation of the highest optimization value. The verifier has approved them with a percentage of 66.7% strongly agreeing and 33.3% agreeing. © 2022 IEEE.
ABSTRACT
Covid-19 pandemic has set the world on fire. It has impacted every aspect of our society. One of the worst affected parts is the countries' health systems. Our goal is to provide a proof of concept for cost effective telemedicine system which can be used by hospitals for monitoring of thousands of patients at once, thus medical personnel exposure to the virus is minimized. In this paper we aim to put this system through the best practices of software testing so we can determine if it achieves its primary functions, keeping in line with the general idea of cost effectiveness. Black box testing with the exploratory approach was used for functionality and feature testing as it gives the most accurate real-world results. During the tests, several bugs were found and fixed. Because of the fact, that the testers were actual medical personnel, we have received valuable information on how to improve the quality of the product, so it can be even more ease to use and provide the necessary robustness and data visualization.