Modeling of a Tourism Group Decision Support System using Risk Analysis based Knowledge Base

Abstract

The increasing number of tourist destination becomes the main factor for export earning, job vacancy, business development, and infrastructure. The problem that occurs is the difference in regional income (GDP) that is quite significant in each region. Thus, it is necessary for the government to make a decision or policy in increasing tourist visits, mainly in Bali. In this case, choosing the most efficient decision from a number of decisions is for the government, tourists, community leaders, academics, and entrepreneurs in the tourism sector, especially in Bali. It is important to have a modeling decision support group (GDSS). GDSS modeling by integrating a knowledge-based (KB) risk analysis can determine decisions, extract information, and identify problems in the tourism sector especially, tourism objects in each region, more specifically. Problem identification in risk analysis modeling is determining decisions in handling risks and finding solutions from alternative tourism decisions that are potentially enlarged and knowledge gained from each decision-maker (DM). The process of identifying knowledge starts with comparing the assessment criteria on each tourism object and knowledge of tourism decision-makers. The results of GDSS modeling are subsequently integrated into knowledge-based risk analysis so that a decision is obtained in the form of an impact or risk and solution or recommendation in developing the specified tourism object. The purpose of combining the result is to understand the impacts or risks that may arise, and recommendations recommended so that the impacts or risks can be avoided.

Group Decision Support System Fuzzy Profile Matching Method With Organizational Citizenship Behaviour

“…first, 4 points for the second ranked candidate and so on, the last candidate receives 1 point, in other words where n candidates will receive n points for the first choice, n-1 for the second choice, n-2 for the 3rd choice, n-4 for the choice 5. Borda's calculation according to [25][26][27][28] is as follows, 1. Giving points by decision makers can be done by assigning a value of -1 for the first alternative choice, -2 for the second alternative choice, and a value of 0 is for the last alternative choice.…”

Group Decision Support System Using SMART-COPELAND SCORE Model In Choosing The Best Alternative Pair

“…Metode SMART juga digunakan dalam pemilihan metode kontruksi pada bangunan [15] dengan menggunakan 4 atribut dan 12 sub atribut pada tahap awal proses evaluasi kelayakan prefabrikasi bangunan. Sedangkan penelitian yang menerapkan GDSS dalam penentuan keputusan yaitu [16] mengungkapkan kombinasi metode AHP-BORDA dalam menentukan keputusan, mengekstrak informasi, dan mengidentifikasi masalah dalam sektor pariwisata khususnya objek wisata. Kombinasi metode AHP, TOPSIS dan Copeland Score digunakan dalam mengevaluasi kinerja proyek teknologi informasi dan komunikasidi instansi pemerintah daerah indonesia [17] dijelaskan Copeland Score dapat digunakan dalam melakukan agregasi berbasis kelompok pengambilan keputusan terhadap nilai preferesi yang diberikan menggunakan teknik voting [5][18].…”

Electronic Tourism Using Decision Support Systems to Optimize the Trips

“…The SAW method can optimize e-tourism-based tourism services by finding the weighted sum of the rating criteria for each alternative. With the implementation of DSS in e-tourism, it will be very easy for tourists to plan and do the right calculations to get their holiday packages [22] because tourists can know the amount of costs that must be paid when traveling to the city of Pagar Alam, besides that, tourists also know accurate information regarding the distance to tourist locations and also the travel distance, this will make it easier for tourists to make decisions about traveling to tourist locations. So by optimizing e-tourism-based services with DSS, we can increase the number of tourists visiting the city of Pagar Alam, resulting in an increase in regional income for the city of Pagar Alam, as well as making a positive contribution to the development of the tourism industry in Indonesia.…”