DEVELOPMENT OF A DECISION SUPPORT SYSTEM FOR HOTEL SELECTION USING ANN-TOPSIS

The rapid growth of information and technology today has majorly impacted various industry sectors all over the world, including in Indonesia. One of the most affected sectors is the tourism industry, where one of the problems caused by the advancement of technology is the abundance of hotel data...

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Bibliographic Details
Main Author: Rachman, Edwin
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/40008
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:The rapid growth of information and technology today has majorly impacted various industry sectors all over the world, including in Indonesia. One of the most affected sectors is the tourism industry, where one of the problems caused by the advancement of technology is the abundance of hotel data information available online. The great amount of data often makes it difficult for potential tourists to determine which hotel suits their particular needs the most. This hotel selection problem can be made easier to solve by using a Decision Support System (DSS). In this research, we will develop a web-based DSS application using a hybrid method of an Artificia Neural Network (ANN) with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method, called the ANN-TOPSIS method. The ANN part of the method is used to predict the weights of each hotel criteria (such as room price, star, review ratings, location ratings). Those weights will be then used by the TOPSIS part to calculate the priority score of each hotel alternatives. The ANN model was implemented using the Keras Machine Learning library, while the DSS web application was implemented using the Ruby on Rails framework. Based on those evaluations at the end of the research, it can be concluded that the proposed ANN-TOPSIS method has a slightly better accuracy compared to the only TOPSIS method for solving the aforementioned hotel selection problem.