The experimental results visualize the data using the boxplot for better understanding of attribute distribution. It benefits from the advantages of neutrosophic set theory not only to improve the performance of rough neural networks but also to achieve a better performance than the other algorithms. The proposed neutrosophic diagnostic system is an Interval Neutrosophic Rough Neural Network framework based on the backpropagation algorithm. Constructing good and efficient classifier via machine learning algorithms is necessary to help doctors in diagnosing the state of fetus heart rate. SVM is used to make a forecast for the next period which can be used as a basis for the government and the tourism industry in making decisions.Ĭardiotocography data uncertainty is a critical task for the classification in biomedical field.
The results of this study indicate the RMSE value of the SVM has the smallest RMSE value compared to the other two methods. This study aims to compare the accuracy between Linear Regression, Support Vector Machine (SVM), and Neural Network methods to forecast the number of foreign tourist arrivals to Indonesia using RapidMiner Studio and parameter of Root Mean Square Error (RMSE) to compare the accuracy of each method. There are various kinds of forecasting methods, but the problem is in choosing the best method for the problem and the desired output. Business Intelligence is one of the digital trends and the main digital marketing strategy for Digital Tourism by implementing data mining for data analysis, including forecasting. It is necessary to carry out development, planning strategies that appropriate, effective, and efficient to increase foreign tourist arrivals. One of the determining factors for tourism development is the number of foreign tourist arrivals.
The tourism sector is one of the largest foreign exchange contributors to the country's economic growth.
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