Religious tourism in Indonesia is growing rapidly, along with the improvement of the community's economy. Culture and the community's beliefs are among the factors affecting it. Greater Malang has many potential and developable religious tourism destinations. Learning from the two well-known religious tourism destinations, we aim to uncover factors that make tourists loyal to these two religious tourism destinations. These factors are used for mapping and formulating marketing strategy. This research is essential and a novelty as there has not been any research discussing the same theme. These two wellknown religious tourism destinations do not have a marketing strategy in their management. They are simply run as they are and have not been professionally managed. With the qualitative method, the study results show that culture-based faith groups as a target market for religious tourism, the mystical and unique story as positioning, and showing routine attractions to build interest are the three main keys that attract tourists to come to religious tourism destinations repeatedly. The results of this study can be used as a reference to develop marketing strategies for existing religious tourism destinations and improve the potential of religious tourism in Greater Malang. Further research is essential to see whether this research's results apply to different areas or countries with the same community characteristics.
The purpose of this helpful in making decisions more quickly and precisely. Research methodology includes analysis study was to analyze the data base support in helping decisions making, identifying needs and designing a data warehouse. With the support of data warehouse, company leaders can be more of current systems, library research, designing a data warehouse using star schema. The result of this research is the availability of a data warehouse that can generate information quickly and precisely, thus helping the company in making decisions. The conclusion of this research is the application of data warehouse can be a media aide related parties on PT. Gajah Tunggal initiative in decision making.
The tourism industry has become a potential sector to leverage economic growth. Many attractions are detected on several platforms. Machine learning and data mining are some potential technologies to improve the service of tourism by providing recommendations for a specific attraction for tourists according to their location and profile. This research applied for a systematic literature review on tourism, digital tourism, smart tourism, and recommender system in tourism. This research aims to evaluate the most relevant and accurate techniques in tourism that focused on recommendations or similar efforts. Several research questions were defined and translated into search strings. The result of this research was promoting 41 research that discussed tourism, digital tourism, smart tourism, and recommender systems. All of the literature was reviewed on some aspects, in example the problem addressed, methodology used, data used, strength, and the limitation that can be an opportunity for improvement in future research. This study proposed some references for further study based on reviewed papers regarding tourism management, tourist experience, tourist motivation, and tourist recommendation system. The opportunities for a further research study can be conducted with more data usage especially for a smart recommender system in tourism through many types of recommendation techniques such as content-based, collaborative filtering, demographic, knowledge-based, community-based, and hybrid recommender systems.
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