A smart tourism recommendation system using the Simple Additive Weighting (SAW) method can significantly improve how tourists choose travel destinations in Biak Regency, Papua, according to new research conducted by Elvis Pawan from Cenderawasih University, Indonesia. The study found that digital decision-support technology can help travelers identify the most suitable tourist attractions based on cost, distance, cleanliness, safety, and destination popularity.
The research, titled “A Decision Support Framework for Smart Tourism Recommendation Using Simple Additive Weighting: Insights from Biak Island,” was published in the International Journal of Applied Research and Sustainable Sciences (IJARSS) in 2026. The study highlights the growing importance of information systems and smart tourism technologies in supporting regional tourism development in Indonesia, particularly in remote island destinations such as Biak.
According to Elvis Pawan from the Department of Information Systems, Faculty of Mathematics and Natural Sciences at Cenderawasih University, tourism has become one of the fastest-growing economic sectors in many Indonesian regions. However, tourists often struggle to choose destinations that match their preferences because of limited information, inconsistent recommendations, and the large number of available attractions.
The study explains that travelers frequently rely on personal judgment or incomplete online information when selecting tourist destinations. As a result, many visitors experience confusion, make inefficient travel decisions, or even cancel tourism activities altogether because of uncertainty about destination quality and suitability.
Biak Island itself is known for its rich tourism potential. Located in Papua, Indonesia, the region offers beaches, waterfalls, islands, caves, cultural sites, and historical landmarks related to World War II. Attractions such as Bosnik Beach, Wari Beach, Padaido Island, Wafsarak Waterfall, and the World War II Monument attract both domestic and international tourists. Despite these resources, digital tourism support systems in the region remain relatively limited.
To address this challenge, the research developed a smart tourism decision-support framework based on the Simple Additive Weighting method. SAW is a multi-criteria decision-making technique designed to rank alternatives by calculating weighted scores across several criteria simultaneously.
In this study, the system evaluated tourist destinations using five major criteria:
- Visit cost
- Distance to the destination
- Cleanliness
- Safety
- Popularity
Each criterion was assigned a specific weight according to its importance in the tourism decision-making process.
Cleanliness received the highest weight at 25 percent because it was considered one of the most important factors affecting tourist comfort and satisfaction. Visit cost, safety, and popularity each received a 20 percent weight, while travel distance accounted for 15 percent.
Researchers analyzed 19 tourist destinations in Biak Regency as sample alternatives within the recommendation system. The destinations included beaches, waterfalls, caves, parks, monuments, and cultural tourism sites. Each destination was coded and evaluated using the SAW calculation framework.
The system processed destination data through normalization and weighted preference calculations to generate tourism rankings. Researchers explained that the SAW approach is especially effective because it converts complex tourism variables into clear numerical rankings that are easier for users to understand and compare.
The results showed that the SAW-based recommendation system successfully produced optimal tourism rankings and destination recommendations for travelers visiting Biak Island. According to the study, the method enables tourists to make more objective, efficient, and personalized travel decisions based on measurable criteria rather than relying entirely on subjective impressions.
One of the study’s most significant findings involved system reliability and functionality.
Using black-box testing methods, researchers evaluated major application features including login systems, destination data management, recommendation printing, and create-read-update-delete functions. The testing showed that all major system components functioned successfully with 100 percent accuracy.
The research also demonstrated that the application interface was designed to be practical and user-friendly. The system included a login page, criteria management page, and tourism destination management page, allowing users to interact with recommendation data efficiently.
According to Elvis Pawan, smart tourism technologies such as decision-support systems can become important tools for improving regional tourism competitiveness in Indonesia. By integrating information systems with tourism services, local governments and tourism operators can provide travelers with faster, more accurate, and more personalized tourism information.
The study also emphasized that digital tourism development aligns with Indonesian tourism regulations, including Tourism Law Number 10 of 2009 and Government Regulation Number 50 of 2011 concerning national tourism development strategies. These regulations encourage the use of technology to improve tourism services, destination management, and tourism promotion.
Beyond helping tourists, the recommendation system may also support local economic development. Improved digital tourism services could increase tourist visits, strengthen destination promotion, and enhance local tourism-based businesses in Biak Regency.
The research recommended further development of Android-based tourism applications to improve accessibility for travelers using mobile devices. Elvis Pawan also suggested integrating SAW with other decision-making methods such as Analytical Hierarchy Process (AHP) and TOPSIS to improve recommendation accuracy and system sophistication in future tourism applications.
More broadly, the study demonstrates how digital decision-support technologies can contribute to the transformation of Indonesia’s tourism sector. As smart tourism becomes increasingly important worldwide, systems capable of combining data analysis, personalization, and user-friendly interfaces may become essential tools for improving tourist experiences and regional tourism management.
Author Profile
Elvis Pawan is an academic and researcher from the Department of Information Systems, Faculty of Mathematics and Natural Sciences, Cenderawasih University, Papua, Indonesia. His research focuses on decision-support systems, information systems, digital transformation, and smart technology applications for tourism and public services.
Source
Elvis Pawan. “A Decision Support Framework for Smart Tourism Recommendation Using Simple Additive Weighting: Insights from Biak Island.” International Journal of Applied Research and Sustainable Sciences (IJARSS), Vol. 4 No. 4, 2026, pp. 357–366. DOI: https://doi.org/10.59890/ijarss.v4i4.240
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