Analisis Sentimen Pengguna Twitter Menggunakan Support Vector Machine Pada Kasus Kenaikan Harga BBM

Twitter is one of the social media with the most active users, which is 24 million active users. Information published on twitter contains comments from users on an object. Sentiment analysis is used to determine whether the data includes negative comments or positive comments because the comments taken on twitter are textual data. The method used in this sentiment analysis is Support Vector Machine (SVM) about public comments on fuel price increases on twitter. The comment data used was 258 data on September 4, 2022 because on that date it was exactly the day after the fuel price increase. First, preprocessing is done to remove unnecessary words or information. Then the data is divided into training data by 80% and testing data by 20%. The accuracy rate is 82.69%, sensitivity is 100%, and specificity is 79.07%. Then from the results of testing 52 data obtained the results of 43 negative comments and 9 positive comments so that it can be concluded that more people disagree with the increase in fuel prices

Economic Valuation of Marina Beach, Bantaeng Regency

This study aims to determine the factors that influence the frequency of tourist visits and to determine the economic value of Marina Beach based on the analysis of travel costs using the Travel cost method. This research was carried out at Marina Beach, Bantaeng Regency from February to March 2021 with a sample of 38 people. The research location was chosen purposively with the consideration that Marina Beach is one of the tourism objects whose exact economic value is not known based on the Travel Cost Method, while the sampling is by non-random sampling or non-random sampling/non-probability sampling. Analysis of the data used is multiple linear regression and analysis of economic value based on travel costs. Factors that have a significant influence on the intensity of visits at Marina Beach are the attractiveness of the beach, the location of the beach. While the factors that do not have a significant effect on the intensity of visits at Marina Beach are travel costs, facilities, accessibility, distance from houses, and the level of cleanliness of Marina Beach attractions. Meanwhile, based on the calculation results, it is known that the consumer surplus based on the individual travel cost method (Individual Travel Cost) is a minimum income of Rp. 42,570.65.- per individual per year, and then the economic value of the Marina Beach tourist attraction is Rp. 1,393,484,222 -/year.