Klasifikasi Kondisi Cuaca Menggunakan Convolutional Neural Network Berbasis Citra Berwarna

Mulyanto, Ahmad Zakiy (2023) Klasifikasi Kondisi Cuaca Menggunakan Convolutional Neural Network Berbasis Citra Berwarna. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Cuaca ekstrim yang berubah – ubah belakangan ini sering terjadi dan sangat menganggu aktivitas sehari – hari. Berdasarkan kondisi geotermal saat ini pendeteksian cuaca menjadi hal yang krusial dalam pengaplikasian beberapa disiplin ilmu dan aktivitas manusia. Mencari metode untuk mendeteksi kondisi cuaca dalam satu waktu dengan image processing adalah inovasi baru yang muncul dalam pemodelan cuaca saat ini. Hal ini didorong oleh kebutuhan yang tinggi dari berbagai pihak untuk melakukan otomatisasi dan digitalisasi dalam mendeteksi suatu kondisi secara teliti dan akurat tanpa harus mengamatinya secara langsung.
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Extreme weather that has changed recently often occurs and greatly disrupts daily activities. Based on the current geothermal conditions, weather detection is crucial in the application of several scientific disciplines and human activities. Looking for a method to detect weather conditions at one time with image processing is a new innovation that appears in weather modeling today. This is driven by the high need from various parties to perform automation and digitization in detecting a condition carefully and accurately without having to observe it directly.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Cuaca, CNN, Cerah, Berawan, Hujan, Weather, Sunny, Cloudy, Rainy, CNN
Subjects:	Q Science > Q Science (General) > Q325.5 Machine learning.
Divisions:	Faculty of Electrical Technology > Computer Engineering > 90243-(S1) Undergraduate Thesis
Depositing User:	Ahmad Zakiy Mulyanto
Date Deposited:	17 Feb 2023 10:34
Last Modified:	17 Feb 2023 10:34
URI:	http://repository.its.ac.id/id/eprint/97467

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