Skripsi
KLASIFIKASI DATA KUALITAS UDARA MENGGUNAKAN PENERAPAN FUZZY NAIVE BAYES BERDASARKAN BOOTSTRAP SAMPLING
Air is very important for life and is a basic requirement for the life of every creature on earth. Therefore, good air quality is needed, not polluted by pollution, or harmful to health so that the activities of living things can run smoothly. Therefore, research is needed that discusses the classification of air quality. The purpose of this study is to classify air quality data using the naïve Bayes and fuzzy naïve Bayes methods based on bootstrap sampling. The usefulness of the fuzzy method is to minimize errors in classification and get a better level of accuracy. The data used in this study is the Air Quality Dataset in the city of Shanghai, China, which totals 2502 data and 21 variables. The results of this study indicate that fuzzy naïve Bayes classifies better than naïve Bayes. Classification using fuzzy naïve Bayes produces a level of accuracy with an accuracy value of 72.78%, macro precision of 26.09%, macro recall of 26.15%, macro fscore of 26.12%, and for micro precision, micro recall, and micro fscore have values the same value of 31.79%. While the classification using naïve Bayes produces a level of accuracy with an accuracy value of 72.31%, macro precision of 24.58%, macro recall of 25.09%, macro fscore of 24.84%, and for micro precision, micro recall, and micro fscore has the same value of 30.78%. Kata Kunci: Air quality, Fuzzy set, Naïve Bayes, Fuzzy Naïve Bayes, Bootstrap Sampling
Inventory Code | Barcode | Call Number | Location | Status |
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2307004736 | T126451 | T1264512023 | Central Library (Referens) | Available |
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