Development of Mobile Butterfly Application-Based Augmented Reality as an Alternative Learning Medium During Post COVID-19

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.

Collaborative and Content-Based Filtering Hybrid Method on Tourism Recommender System to Promote Less Explored Areas

The COVID-19 pandemic has significantly impacted various areas of life, including tourism. Currently, the tourism sector is starting to recover and start its activities. However, several tourist attractions have not been explored, thus making visitors less aware of information about these tours. This affects the number of tourist visits. Therefore, there is a need of an information technology approach to promote tourism objects, including a tourist recommendation system. This study proposed a hybrid recommendation system incorporating collaborative and content based filtering. This model is proven to be able to produce good rating predictions on a recommendation system. This hybrid method uses a linear combination by calculating the rating matrix and user profile as the first step in providing rating predictions. Collaborative filtering is calculated using the cosine similarity algorithm and weighted sum algorithm, while the content-based filtering method is performed by calculating the weight of each available feature. We apply this model to the Palembang tourism dataset to the the website. This system recommends existing historical tourist attractions based on visitor criteria. The results show the existing data's effective, efficient, and accurate results. The calculation result that the rating prediction using the hybrid method is 3.203. In addition, this method can also help overcome existing cold start problems. © Roman Science Publications Inc.

The Effect of The COVID-19 Pandemic and Google Trends on the Forecasting of International Tourist Arrivals in Indonesia

The tourism sector is a strategic industrial pillar that contributes to a country's economy. In future tourism development efforts, accurate tourism forecasting is needed. Despite its importance, tourism is also one of the most vulnerable industries. Since COVID-19 was declared a pandemic by WHO, social distancing has significantly impacted tourism development. It can be explored more deeply by including the COVID-19 pandemic in the forecast. In addition, it is necessary to include Google Trends, which is a product of the largest search engine in the world and is proven to improve forecasting accuracy. This study aimed to analyze the effect of the COVID-19 pandemic and search query data on the forecasting of foreign tourists to Indonesia. The methods used are ARIMAX and SARIMAX with the endogenous variables of foreign tourist visits to Indonesia. Meanwhile, the exogenous variables are Google Trends search query data and the COVID-19 pandemic. The performance of the two methods is then compared with the ARIMA and SARIMA methods, which do not use exogenous variables in forecasting. This study indicates that the exogenous variables increase the forecasting accuracy. Forecasting with the best accuracy is obtained by the SARIMAX method with the exogenous variable Google Trends. This method outperformed the other methods with MAPE = 5.4556, RMSE = 11041.0510 and MAE = 8479.6116. In addition, in this study, a framework was created to build a composite search index for Google Trends to improve forecasting accuracy.

Using Artificial Intelligence Technology for Decision Support System in Audit Risk Assessment: A Review Paper

Artificial Intelligence (AI) has a significant impact in the disruptive era. An audit is an area that is affected. The application of AI in internal audits comes from a need to make better-added value, a demand to overcome the traditional audit's limitation and adapt to the new way of working in the pandemic Covid-19. Risk assessment has a primary role in audit planning and has become a factor that affects the efficiency and effectiveness of the audit. This paper aims to create insight into AI implementation in auditing, especially in risk assessment, including models and algorithms. In addition, it is hoped that new perspectives are formed on how to build decision-making or to problem-solve in auditing through the relationship between the current availability of big data and AI, including data mining and machine learning. This review study showed that risk assessment in auditing became significantly easier using AI technology. The auditor can identify the riskiest audit areas by detecting or predicting, and minimizing audit risks using AI. Classification algorithms such as logistic regression, decision trees, neural networks, and support vector machines can be used to detect or predict. Moreover, another technique that can be utilized is combining it with expert systems or fuzzy theory. © 2021 IEEE.