Suryowicaksono, Handy (2021) Pengembangan Perancangan Sistem Prediktor Logika Fuzzy untuk Laju Pertambahan Covid 19 Berdasarkan Cuaca dan Polutan: Studi Kasus di Kota Surabaya. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
COVID 19 merupakan penyakit yang diakibatkan oleh virus SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2). Virus ini dapat menyebar antar manusia dengan media droplets. Pergerakan droplets dapat dipengaruhi oleh beberapa faktor lingkungan seperti cuaca dan polutan. Pada riset penelitian ini dirancang sebuah model sistem prediksi delta kasus konfirmasi COVID 19 di Kota Surabaya berdasarkan data cuaca dan polutan berbasis logika fuzzy. Penggunaan sistem logika fuzzy ini didasarkan pada kemampuan fuzzy yang mampu mengatasi permasalahan bersifat nonlinearitas. Unsur nonlinearitas pada penelitian ini terdapat pada data kasus COVID 19. Data didapatkan dari berbagai sumber seperti BMKG, NASA dan Satgas COVID 19 Kota Surabaya. Data cuaca dan polutan yang digunakan berdasarkan uji korelasi pada penelitian ini adalah PM 2.5, kecepatan angin, durasi penyinaran matahari dan delta kasus konfirmasi hari sebelumnya. Nilai koefisien korelasi masing-masing yaitu PM 2.5 sebesar 0.296 kategori lemah, kecepatan angin sebesar 0.413 kategori cukup, durasi penyinaran matahari sebesar 0.313 kategori cukup dan delta konfirmasi hari sebelumnya sebesar 0.749 kategori kuat. Dari hasil perancangan model terbaik didapatkan menggunakan metode ANFIS (Adaptive Neuro Fuzzy Inference System) dengan nilai MAPE yaitu sebesar 17.67%. Hasil ini apabila diinterpretasikan dalam pengukuran kinerja sistem prediksi dengan indikator MAPE tergolong sistem prediksi yang cukup bagus.
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COVID 19 is a disease caused by the SARS-CoV-2 virus (Severe acute respiratory syndrome coronavirus 2). This virus can spread between humans through droplets. The movement of droplets can be influenced by several environmental factors such as weather and pollutants. In this research, a model prediction system for delta of confirmed cases of COVID 19 in the city of Surabaya was designed based on weather and pollutant data based on fuzzy logic. The use of this fuzzy logic system is based on fuzzy capabilities that are able to overcome uncertainty. The element of uncertainty in this study is contained in the COVID 19 data. The data was obtained from various sources such as BMKG, NASA, and the Surabaya City COVID 19 Task Force. Based on the correlation test in this study, weather and pollutant data were PM 2.5, wind speed, duration of sunlight, and delta of confirmed cases the previous day. The correlation coefficient values of each are PM 2.5 in the weak category of 0.296, the wind speed of 0.413 in the excellent category, the duration of solar radiation in the 0.313 categories in the good category, and the confirmation delta previous day of 0.749 in the strong category. The results of designing the best model were obtained using the ANFIS (Adaptive Neuro-Fuzzy Inference System) method with a MAPE value of 17.67%. When interpreted in measuring the performance of the prediction system with the MAPE indicator, this result is a pretty good prediction system.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Uncontrolled Keywords: | COVID 19, Fuzzy Logic, Weather, Pollutants, COVID 19, Fuzzy Logic, Cuaca, Polutan |
| Subjects: | Q Science > QA Mathematics > QA336 Artificial Intelligence Q Science > QA Mathematics > QA76.87 Neural networks (Computer Science) Q Science > QA Mathematics > QA9.64 Fuzzy logic Q Science > QC Physics > QC866.5 Climatology--Forecasting. R Medicine > RA Public aspects of medicine > RA644.C67 COVID-19 (Disease) T Technology > T Technology (General) > T174 Technological forecasting |
| Divisions: | Faculty of Industrial Technology and Systems Engineering (INDSYS) > Physics Engineering > 30201-(S1) Undergraduate Thesis |
| Depositing User: | Handy Suryowicaksono |
| Date Deposited: | 18 Aug 2021 14:35 |
| Last Modified: | 18 Aug 2021 14:35 |
| URI: | http://repository.its.ac.id/id/eprint/88139 |
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