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PREDIKSI TINGKAT PENCEMARAN UDARA MENGGUNAKAN FUZZY INFERENCE SYSTEM TSUKAMOTO
Air is a very important factor in life. In this modern era, along with the increase in population and development in urban areas and industrial centers, this causes air quality. The presence of air pollutants is caused by air pollutant substances such as Particulate Matter (PM10), Sulfur Dioxide (SO2), Nitrogen Dioxide (NO2), Carbon Monoxide (CO) and Ozone (O3). Therefore, the air quality has changed. From the beginning, the fresh and clean air was now dirty, smoky and dusty. To predict the level of air pollution, the method used is the Fuzzy Inference System model Tsukamoto. This method was chosen because the Tsukamoto fuzzy is a flexible method and has an error tolerance of existing data. Where fuzzy Tsukamoto has a rule in the form of IF-THEN which will be presented in the form of a fuzzy set with a monotonic membership function. The test was carried out using 182 air pollution data and the quality of the accuracy value was 87.36% and the Mean Absolute Percentage Error (MAPE) value was 19.612%. Based on the range of MAPE values described in Palmer's research, it shows that the prediction results obtained are included in the category of accurate predictions.
Inventory Code | Barcode | Call Number | Location | Status |
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2207001987 | T73335 | T733352022 | Central Library (Referens) | Available but not for loan - Not for Loan |
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