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Data mining is related to searching data to find patterns or knowledge from the whole data. It turns out that a large data set can produce a data whose results can provide new knowledge information. Data mining is an important step in the process of finding knowledge. In this study will be discussed about data mining design using C4.5 algorithm to...
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Fluency in reciting the Koran is learning the recitation of the Qur'an in a tartil way. Based on the observations of researchers, the learning of tajwid in recitation and at school has not been effective so far. Because of this, both teachers and students at recitation or at school need improvement by finding out what can increase fluency in reciti...
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... Binary features have only two different values, while categorical features have values of categorical type (nominal or ordinal) that might have several different values, and numeric features have numeric type values with the condition that testing in nodes is done by comparison testing. The C4.5 algorithm for building a decision tree goes like this [11], [16], [19] a. Choose an attribute to be the root. b. ...
Purpose: This research was conducted to create a classification model in the form of the most optimal decision tree. Optimal in this case is the combination of parameters used that will produce the highest accuracy compared to other parameter combinations. From this best model, it will be used to predict the nutritional status class for the new data.Methods/Study design/approach: The dataset used is from Nutritional Status Monitoring in 2017 in Riau Province, Indonesia. From the dataset, the Knowledge Discovery in Database (KDD) stages were carried out to build several classification models in the form of decision trees. The decision tree that has the highest accuracy will then be selected to predict the class for the new data. Predictions for new data (unclassified data) will be made in a web-based system.Result/Findings: Particle Swarm Optimization is used to find optimal parameters. Before PSO is used, there are 213 parameters in the dataset that can be used to do classification. However, using many such parameters is time-consuming. After PSO is used, the optimal parameters found are the combination of 4 parameters, which can produce the most optimal decision tree. The 4 chosen parameters are gender, age (in months), height, and the way to measure the height (either stand up or lie down). The most optimal decision tree has an accuracy of 94.49%. From the most optimal decision tree, a web-based system was built to predict the class for new data (unclassified data).Novelty/Originality/Value: Particle Swarm Optimization (PSO) is a method that can help to select the most optimal parameters, or in other words produce the highest classification accuracy. The combination of parameters selected has also been confirmed by the nutritionist. The prediction system has been declared feasible to be used by nutritionists through the User Acceptance Test (UAT).
Sabilillah Educational Cash Unit is a unit within the sabilillah educational foundation which is engaged in education. The stored cash processing data will be utilized using data mining so that it can be used as a decision support for finding information that is useful in evaluating the data used. Various methods contained in the data mining, the authors will make a comparison of the method techniques from the data mining. The use of the decision tree and, K-means method is implemented using the Rapid Miner application, which will later be analysed of each of these methods to determine the strategy to look for students who have the potential to save the hajj savings. This research was conducted with a group of data to determine the percentage value of precision, recall and accuracy. The results of this study that the C.4.5 method has a better value than other methods on the recall and accuracy, while the K-Means method has a precision value better than the other methods.
Indonesia is a developing country in which poverty is one of the problems faced by each province. The government continues to strive to overcome this problem of poverty to be able to create conditions for a prosperous society. The government's efforts to poverty alleviation are by providing some assistance programs. Therefore, it is necessary to build a decision support system that is useful to help the government to make a decision. This decision support system applies the EXPROM II (The Extended Promethee II) method with the weight of objective criteria. There are 15 criteria used based on SUSENAS data from the Statistics Indonesia of East Kalimantan Province. This research resulted in a decision support system that can give priority order of the level of family welfare so that it can be considered or referred by the local government or related agencies in distributing assistance to the society.
