Pengelompokan Jumlah Wisatawan Nusantara Menggunakan Fuzzy Learning Vector Quantization - Fauzan, Fauzan; Yulianto, Tony; Faisol, Faisol; Yudistira, Ira; ku, Kuzairi (Mathematics Department, Faculty of Mathematics and Sciences Unisda Lamongan, 2024)
Tourism is a variety of tourist activities and support from facilities and services provided by interested parties, such as the community, entrepreneurs and the goverment. Tourists are people who visit a destination outside of their daily activities within a certain period of time. There are several provinces that are classified as having minimal tourists, so they require government evaluation in providing good services in order to increase tourists in terenst in provinces that are classified as having minimal tourists. Therefore, to group the number of tourists, research will be carried out using a combination of data mining and fuzzy logic, namely the fuzzy learning vector quantization method. The research results obtained: For Euclidean Distance, there are 10 provinces in cluster 1 and there are 24 provinces in cluster 2. For squareeuclidean distance, there are 32 provinces in cluster 1 and there are 2 provinces in cluster 2. For city block distance there is 1 province which is included in cluster 1 and there are 33 provinces which are included in cluster 2. For the Chebychev distance there are 10 provinces which are included in cluster 1 and there are 24 provinces which are included in cluster 2. The final result which was chosen as the best is Euclidean however after checking the validity method it is in the formula squareeuclidean with value of PC= 8.32165E+26, CE=-8.94064E+14, and IFV= -1.4892E+13