OPTIMASI FUZZY INFERENCE SYSTEM METODE MAMDANI DENGAN ANT COLONY OPTIMIZATION(ACO) UNTUK MENGHITUNG CURAH HUJAN

SAFTIAN, MARGONO and Rini, Dian Palupi and Miraswan, Kanda Januar (2019) OPTIMASI FUZZY INFERENCE SYSTEM METODE MAMDANI DENGAN ANT COLONY OPTIMIZATION(ACO) UNTUK MENGHITUNG CURAH HUJAN. Undergraduate thesis, Sriwijaya University.

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Abstract

The rainy season that occurs in Indonesia between October to April with the highest rainfall peak in December. But there is a possibility of weather anomalies and even climate deviations. This is marked by changes in peak rainfall. If these conditions are ignored, it can cause flooding in several cities, especially Palembang. The characteristics of rain itself are very difficult to predict. In this study, using Fuzzy Inference System (FIS) optimization with ant colony optimization (ACO) to calculate rainfall. Rainfall is predicted by applying the rules of basic reasoning and fuzzy logic by applying the Fuzzy Inference System method. This study uses three input variables that affect the occurrence of rain in the form of air temperature, relative humidity and wind speed. The results showed that the application of the Fuzzy Inference System (FIS) method with Ant Colony Optimization (ACO) could be applied. Data for 2015 has a value of Root Mean Square Error (RMSE) of at least 1.2588262938361 Musim penghujan yang terjadi di Indonesia antara bulan Oktober hingga April dengan puncak curah hujan tertinggi di bulan Desember. Namun terdapat kemungkinan terjadinya anomali cuaca bahkan penyimpangan iklim. Hal tersebut ditandai dengan berubahnya puncak curah hujan. Jika kondisi tersebut diabaikan, maka dapat mengakibatkan banjir di beberapa kota khususnya Palembang. Ciri-ciri hujan itu sendiri sangat sulit diprediksi. Dalam penelitian ini, menggunakan optimasi Fuzzy Inference Sistem (FIS) dengan ant colony optimization (ACO) untuk menghitung curah hujan. Curah hujan diprediksikan dengan menerapkan aturan penalaran dasar dan logika fuzzy dengan menerapkan metode Fuzzy Inference System. Penelitian ini menggunakan tiga variable input yang mempengaruhi terjadinya hujan berupa suhu udara, kelembaban relative dan kecepatan angin. Hasil penelitian menunjukkan bahwa penerapan metode Fuzzy Inference Sistem (FIS) dengan Ant Colony Optimization (ACO) dapat diterapkan. Data Tahun 2015 memiliki nilai Root Mean Square Error (RMSE) paling kecil 1,2588262938361

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	optimasi, Fuzzy Inference System, Logika Fuzzy, Prediksi Curah Hujan, ant colony optimization
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Users 4508 not found.
Date Deposited:	20 Jan 2020 06:15
Last Modified:	20 Jan 2020 06:15
URI:	http://repository.unsri.ac.id/id/eprint/24559

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