The value of bitcoin currency is very volatile, hard to guess for every hour, so many of the bitcoin traders suffer losses because they are wrong in managing their bitcoin assets. Changes in the price of bitcoin itself are influenced by many things such as the closing of the bitcoin market in a country, the occurrence of hacker attacks on the bitcoin blockchain and the emergence of new coins that use technology similar to bitcoin. But when a stable market situation changes the price of bitcoin is purely influenced by market forces. By implementing an artificial neural network using backpropagation method, it will be able to predict the price of bitcoin by giving a form of predictive results that are strengthened with a fairly good value of accuracy. This research begins by determining prediction variables with target values that can be determined based on previous bitcoin prices. This artificial neural network process is able to conduct training and testing of data based on network patterns that have been formed, then the results of training and testing of the network will be analysed again, so that at the last stage the best network patterns will be used in the prediction process.
Bukittinggi City is known as a tourist destination that is very attractive in foreign tourist interest. Diverse types of tours are presented naturally and man-made the beauty of mountains, valleys and the beauty of the existing architectural buildings is Bukittinggi Clock Tower. Not only that, the type of culinary tourism and traditional market snacks are also an attraction for foreign tourists to travel in the city of Bukittinggi. In this study, the problem that will be discussed is the process of predicting tourist visits conducted by foreign tourists to the city of Bukittinggi. The prediction process uses the concept of artificial neural network backpropagation algorithm. The data set that will be used as a discussion is the data foreign tourist visits recorded in the Tourism Office of Bukittinggi City from 2018 to 2019. The prediction results generated with the concept of artificial neural network backpropagation algorithm produce output numbers of number of visits with an accuracy value of 95,64% and level value the resulting error is 4,36%. The benefits generated from this research are helping the government of the city of Bukittinggi especially the Tourism Office in providing input to manage the tourism sector.
SMAN 10 Padang is one of the leading schools in the city of Padang State School which has two majors, namely Science (Science Knowledge) and Social Sciences (Social Sciences). A distinctive feature of this school is one of the international standard pilot schools (RSBI) by implementing bilingual and accelerating classes. On average students lack understanding in the selection of majors according to their abilities. Many people fail in the way they have found. To facilitate the determination of majors, a Decision Making System (SPK) is needed to find criteria. In SPK there are several methods in searching criteria, which are usually used by SAW with MFED. Based on the research carried out, by comparing the two methods, the data are grouped into three criteria, namely the value of the Natural Sciences National Examination, Psychology tests, and Interests. The results of this study show about MFEP method take a high accuration between SAW. An accuration of SAW have 38.3 % and MFEP have 70.5%.
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