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The death rate in the world per year is 17.9 million due to cardiovascular disease, including heart and blood vessel disorders. This needs to be given more attention to anticipate the possible risk of a heart attack. One of the contributions in the field of technology to provide useful information about the risk of heart disease is by using a data processing approach or data mining technique by classifying the vulnerability to heart disease risk. The classification method used is Support Vector Machine and Naïve Bayes. The classification method will be carried out in a comparative process and the method that has the best accuracy will be sought. The scenarios used are 2 test scenarios, namely dividing the training data by 20% in scenario 1 and 40% in scenario 2. The final results of the research obtained are the best accuracy in the Support Vector Machine with scenario 1 of 87%.

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Local craft industry is now starting to compete with other industries in the process of advancing the region and even the country's economy. Yogyakarta, as a tourism destination known for its traditional cultural values would be more interesting if the culture of local crafts can be more openly introduced. The high interest in the local craft makes tourists want to see, and even to try the process of making of local crafts in Yogyakarta. Traveling Salesman Problem (TSP) with genetic algorithm method works by providing Yogyakarta's local craft location recommendation, from closest to farthest location that can be visited by tourists with the use of Global Positioning System (GPS) on their smartphones. Traveling Salesman Problem (TSP) with genetic algorithm (GA) method provides the best traveling route for tourists who want to find and visit Yogyakarta's local craft location in one hand.