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Comparative Study of Decision Tree Method and Fuzzy Decision Tree on the Land Cover Classification. This research is a comparative study of the performance of decision tree method with fuzzy decision tree classification of land cover to help manage natural resources. The decision tree method is a simple technique and provides optimal results, but often have difficulty on incomplete data (missing value), the data enumerated, or vague, often found on land cover datasets. While the fuzzy decision tree method for implementing fuzzy concepts in the branch formation so as to produce a complete and expected to accommodate the shortage. Some land cover datasets are selected. Then two methods of performance measurement in some test by grouping the input data and the results compared with the actual classification. The results showed that the fuzzy decision tree method can provide the level of recognition by the 4.96%, but it takes much longer computation 38.13%. The classification method with data recognition capabilities that are incomplete or not clear with time computing is fast becoming a good contribution to be implemented on the application of Geographic Information System.
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