IMPLEMENTASI METODE FUZZY TIME SERIES CHENG UNTUK FORECASTING KONSENTRASI GAS NO₂ DI UDARA
Proses peramalan sangat penting pada data time series karena diperlukan dalam proses pengambilan keputusan. Dalam penentuan kualitas udara peramalan dapat digunakan untuk memantau gas NO₂ di udara. Pada penelitian ini metode Fuzzy Time Series Cheng digunakan untuk memprediksi gas NO2 di udara, diman...
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2016-08.
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Online Access: | http://eprints.undip.ac.id/51286/ |
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LEADER | 04010 am a22002893u 4500 | ||
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001 | repository_undip_51286_ | ||
042 | |a dc | ||
100 | 1 | 0 | |a FATHONI, M. Yoka |e author |
700 | 1 | 0 | |a SURYONO, Suryono |e author |
700 | 1 | 0 | |a WIDODO, Catur Edi |e author |
245 | 0 | 0 | |a IMPLEMENTASI METODE FUZZY TIME SERIES CHENG UNTUK FORECASTING KONSENTRASI GAS NO₂ DI UDARA |
260 | |c 2016-08. | ||
500 | |a http://eprints.undip.ac.id/51286/1/02_Halaman_Pengesahan.pdf | ||
500 | |a http://eprints.undip.ac.id/51286/2/04_DAFTAR_ISI.pdf | ||
500 | |a http://eprints.undip.ac.id/51286/3/05_BAB_I.pdf | ||
500 | |a http://eprints.undip.ac.id/51286/4/06_BAB_II.pdf | ||
500 | |a http://eprints.undip.ac.id/51286/5/07_BAB_III.pdf | ||
500 | |a http://eprints.undip.ac.id/51286/6/08_BAB_IV.pdf | ||
500 | |a http://eprints.undip.ac.id/51286/7/09_BAB_V.pdf | ||
500 | |a http://eprints.undip.ac.id/51286/8/010_Daftar_Pustaka.pdf | ||
500 | |a http://eprints.undip.ac.id/51286/9/012_Lampiran.pdf | ||
520 | |a Proses peramalan sangat penting pada data time series karena diperlukan dalam proses pengambilan keputusan. Dalam penentuan kualitas udara peramalan dapat digunakan untuk memantau gas NO₂ di udara. Pada penelitian ini metode Fuzzy Time Series Cheng digunakan untuk memprediksi gas NO2 di udara, dimana pada proses akuisisi data gas NO2 terintegrasi dengan Multichannel-Multistasion Menggunakan Teknologi Wireless Sensor Network Melalui Internet Broadband yang kemudian dikirimkan dan disimpan dalam bentuk online database pada web server untuk selanjutnya dilakukan prediksi. Data gas NO₂ hasil akuisisi diperoleh dari sensor yang dikirim ke web server dalam basis data dalam jaringan (online) untuk selanjutnya di prediksi menggunakan Fuzzy Time Series Cheng yang menerapkan pembagian ulang (re-divide) terhadap hasil interval partisi pertama dari nilai semesta pembicaraan (universe of discourse) dengan melakukan fuzzifikasi data historis untuk menentukan Fuzzy Logical Relationship dan Fuzzy Logical Relationship Group, sehingga didapat hasil nilai prediksi konsentrasi gas NO2. Dengan menggunakan 36 data sampel dari gas NO2 diperoleh nilai root of mean squared error (RMSE) sebesar 2.08%. Hal ini mengindikasikan bahwa Fuzzy Time Series Cheng cukup baik untuk digunakan dalam memprediksi Gas NO2. Kata Kunci : Forecasting, Time Series, Wireless Sensor, Gas NO₂ Forecasting process is very important in the time series data because it is really needed in the decision making process. In determining the air quality forecasting can be used to monitor the NO2 gas in the air. In this research Fuzzy Time Series Cheng method is used to predict NO2 gas in the air, where the data acquisition process NO2 gas integrated with Multichannel-Multistasion using Wireless Sensor Network Technology through The Internet Broadband which is then transmitted and stored in the form of an online database on the web server for further will be done the predictions. Acquisition result of NO2 gas data is obtained from the sensor which is sent to the web server in the data base in the network (on line) then for futher it is predicted using fuzzy time series Cheng applying reapportionment (re-divide) to the results of intervals the first partition of the value of the universe of discourse ( universe of discourse) by doing historical data fuzzification to determine Fuzzy Logical Relationship dan Fuzzy Logical Relationship Group, so that is obtained result value prediction of NO2 gas concentration. ). By using 36 sample data of NO2 gas, it is obtained that the value of root of mean squared error (RMSE) of 2.08%. This indicates that Fuzzy Time Series Cheng is good enough to be used in predicting the NO2 gas. Key Words : Forecasting, Time Series, Wireless sensor, NO₂ Gas. | ||
690 | |a Computer engineering. Embedded system. Network. Softwares. Robotics. Multimedia | ||
655 | 7 | |a Thesis |2 local | |
655 | 7 | |a NonPeerReviewed |2 local | |
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856 | 4 | 1 | |u http://eprints.undip.ac.id/51286/ |