PERKIRAAN CUACA DI KOTA PALEMBANG DENGAN ALGORITMA JARINGAN SYARAF TIRUAN HOPFIELD

ROSITA, INDAH and Rini, Dian Palupi and Marieska, Mastura Diana (2020) PERKIRAAN CUACA DI KOTA PALEMBANG DENGAN ALGORITMA JARINGAN SYARAF TIRUAN HOPFIELD. Undergraduate thesis, Sriwijaya University.

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Abstract

Hopfield Neural Network Algorithm is an algorithm that is often used in pattern recognition and is also often used in forecasting. The existence of this research is used to forecast the weather by finding the output criteria pattern of weather, namely sunny, cloudy and rainy with the Hopfield Artificial Neural Network algorithm. The weather elements used in this study are temperature, humidity, air pressure, and wind speed. The weather element used will be the input value and then after going through the calculation process, the resulting output will be used as input again. The Hopfield Neural Network Algorithm is implemented as an application in weather forecasting. The results of this estimate are then measured for accuracy. Tests were carried out on 365 BMKG weather data in 2015 and it was found that the accuracy obtained was 30.68%. This accuracy is low, so it can be concluded that this algorithm is not suitable for predicting the weather.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Perkiraan Cuaca, Jaringan Syaraf Tiruan, Algoritma Hopfield, Suhu,Kelembaban Udara, Tekanan Udara, Kecepatan Angin
Subjects: Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
T Technology > T Technology (General) > T1-995 Technology (General)
T Technology > TJ Mechanical engineering and machinery > TJ1125-1345 Machine shops and machine shop practice > TJ1180 Machining, Ceramic materials--Machining-Strength of materials-Machine tools-Design and construction > TJ1180.I34 Machining-Machine tools-Numerical control-Computer integrated manufacturing systems-Artificial intelligence
Divisions: 09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User: Indah rosita
Date Deposited: 05 Oct 2020 01:49
Last Modified: 05 Oct 2020 01:49
URI: http://repository.unsri.ac.id/id/eprint/36035

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