Syukriyanto latif - Academia.edu (original) (raw)
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Papers by Syukriyanto latif
English language journals. This research uses a system of text mining technology that extracts te... more English language journals. This research uses a system of text mining technology that extracts text data to search information from a set of documents. Abstract content of 120 data downloaded at www.computer.org. Data grouping consists of three categories: DM (Data Mining), ITS (Intelligent Transport System) and MM (Multimedia). Systems built using naive bayes algorithms to classify abstract journals and feature selection processes using term weighting to give weight to each word. Dimensional reduction techniques to reduce the dimensions of word counts rarely appear in each document based on dimensional reduction test parameters of 10%-90% of 5.344 words. The performance of the classification system is tested by using the Confusion Matrix based on comparative test data and test data. The results showed that the best classification results were obtained during the 75% training data test and 25% test data from the total data. Accuracy rates for categories of DM, ITS and MM were 100%, 100%, 86%. respectively with dimension reduction parameters of 30% and the value of learning rate between 0.1-0.5.
The purpose of this research is to know dimension reduction parameter value at feature selection ... more The purpose of this research is to know dimension reduction parameter value at feature selection so as to improve accuracy and reduce computation time. This system uses text mining technology that extracts text data to find information from a set of documents. Word weighting and Term Reduction Technique The term Frequency Thresholding is used in the feature selection process, while in the classification process using the Naive Bayes algorithm. the abstract of the journal is categorized into 3 namely Data Mining (DM), Intelligent Transport System (ITS) and Multimedia (MM). The total number of test data and training data is 150 data. The best classification results are obtained when the dimension reduction parameter value is 30%. At that condition obtained an average accuracy of 87.33% with a computation time of 4 minutes 12 seconds.
English language journals. This research uses a system of text mining technology that extracts te... more English language journals. This research uses a system of text mining technology that extracts text data to search information from a set of documents. Abstract content of 120 data downloaded at www.computer.org. Data grouping consists of three categories: DM (Data Mining), ITS (Intelligent Transport System) and MM (Multimedia). Systems built using naive bayes algorithms to classify abstract journals and feature selection processes using term weighting to give weight to each word. Dimensional reduction techniques to reduce the dimensions of word counts rarely appear in each document based on dimensional reduction test parameters of 10%-90% of 5.344 words. The performance of the classification system is tested by using the Confusion Matrix based on comparative test data and test data. The results showed that the best classification results were obtained during the 75% training data test and 25% test data from the total data. Accuracy rates for categories of DM, ITS and MM were 100%, 100%, 86%. respectively with dimension reduction parameters of 30% and the value of learning rate between 0.1-0.5.
The purpose of this research is to know dimension reduction parameter value at feature selection ... more The purpose of this research is to know dimension reduction parameter value at feature selection so as to improve accuracy and reduce computation time. This system uses text mining technology that extracts text data to find information from a set of documents. Word weighting and Term Reduction Technique The term Frequency Thresholding is used in the feature selection process, while in the classification process using the Naive Bayes algorithm. the abstract of the journal is categorized into 3 namely Data Mining (DM), Intelligent Transport System (ITS) and Multimedia (MM). The total number of test data and training data is 150 data. The best classification results are obtained when the dimension reduction parameter value is 30%. At that condition obtained an average accuracy of 87.33% with a computation time of 4 minutes 12 seconds.