International Journal of Science and Research (IJSR)
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Research Paper | Computer Science | Philippines | Volume 10 Issue 11, November 2021

Tourists' Arrival Prediction Using Regression Techniques

John C. Amar [3]

Abstract: This study was conducted to predict the tourists' arrival in the Island of Boracay, Malay, Aklan, Philippines. It adopted the developmental type of research, for it is aimed to come up with a system to predict the arrival of tourist per year and determine the factors affecting such visit. It made use of Linear Regression technique in order to predict the arrival of tourists per year. It was found out to be precise and reliable. Also, it utilized the Multiple Linear Regression Technique in order to know the factors affecting the tourists' visit in the island. These mathematical tools are accorded with Linear Probability Plot, Normal Probability Plot, and Probability Plot. These were used in order to test the reliability of the variables used in the study, especially the 4 'As' of tourism which include, amenities, accommodation, accessibility, and attraction. It was found out that the use of this technique was found to be significant. Residual Plot Analysis was used in the study and found out to be effective and accurate. As proven, the results of the study would validate that when plots are scattered in the horizontal axis would mean that the analysis is found to be precise. Line Fit Plot Analysis was also used in the study, which proved that if there are increasing values of scattered points, it shows significant correlation between the independent and dependent variables. Normal Probability Plot was further utilized where it was proven that if the data are plotted in a theoretical normal and typical distribution in the sample percentile with regards to the number of tourists' arrivals form an approximate or estimated straight line. The general objective of the study was to develop an online application that will predict the tourists' arrival using regression techniques. Specific Objectives: 1. Apply linear regression to predict the tourist arrival per year. 2. Implement multiple linear regression to determine the factors affecting tourists' arrival. 3. Integrate these regression techniques to the developed online application. Findings: Linear Regression Analysis was used to predict the arrivals of tourists and was found out to be precise and reliable. Multiple Linear Regression Analysis was also utilized to determine the factors affecting tourists' arrivals. This was used in order to test the reliability of the variables used in the study, especially the 4 'As' of tourism which include, amenities, accommodation, accessibility, and attraction. The results proved that the use of this technique was found to be reliable and significant.

Keywords: Tourist, Prediction, Data Mining, Linear Regression, Multiple Linear Regression

Edition: Volume 10 Issue 11, November 2021,

Pages: 773 - 784