PENERAPAN ALGORITMA NAIVE BAYES CLASSIFIER DALAM KLASIFIKASI CURAH HUJAN DKI JAKARTA

IRHAMNA, AHMAD SYAUQI (2022) PENERAPAN ALGORITMA NAIVE BAYES CLASSIFIER DALAM KLASIFIKASI CURAH HUJAN DKI JAKARTA. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

Rainfall is one of the elements in the climate. High rainfall intensity or what is often called extreme rain can result in flooding. To minimize the occurrence of floods caused by rainfall, a daily rainfall forecast is needed. Rainfall forecasting has become one of the most scientific and technologically challenging problems around the world in the last century. The Naïve Bayes Classifier (NBC) method, a classification method that can be used for rainfall forecasting in this study. The data used came from the BMKG of all stations in DKI Jakarta province from 2017 to 2021 with four independent variables, namely Average Temperature (°C), Average Humidity (%), Irradiation Duration (hours), and Average Wind Speed (knots). The results of the study showed that the NBC method training data produced an accuracy of 0.96710 or 96.710%. Key words: Rainfall,Classification, Naïve Bayes Classifier. Curah hujan termasuk salah satu elemen pada iklim. Intensitas curah hujan yang tinggi atau yang sering disebut hujan ekstrem dapat mengakibatkan terjadinya banjir. Untuk meminimalisir terjadinya banjir yang diakibatkan oleh curah hujan, maka diperlukan prakiraan curah hujan harian. Prakiraan curah hujan telah menjadi salah satu masalah yang paling ilmiah dan teknologi menantang seluruh dunia pada abad terakhir. Metode Naïve Bayes Classifier (NBC), metode klasifikasi yang dapat digunakan untuk prakiraan curah hujan pada penelitian ini. Data yang digunakan berasal dari BMKG seluruh stasiun di provinsi DKI Jakarta dari tahun 2017 hingga tahun 2021 dengan empat variabel independen yaitu Rata-rata Suhu (°C), Rata-rata Kelembaban (%), Lama Penyinaran (jam), dan Rata-rata Kecepatan Angin (knot). Hasil dari penelitian menunjukkan untuk data training metode NBC menghasilkan akurasi sebesar 0,96710 atau sebesar 96,710%. Kata kunci: Curah Hujan, Klasifikasi Naïve Bayes Classifier.

Item Type: Thesis (S1)
Call Number CD: FIK/INFO. 22 174
Call Number: SIK/15/22/084
NIM/NIDN Creators: 41518010034
Uncontrolled Keywords: Curah Hujan, Klasifikasi Naïve Bayes Classifier.
Subjects: 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika
000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 020 Library and Information Sciences/Perpustakaan dan Ilmu Informasi > 025 Operations, Archives, Information Centers/Operasional Perpustakaan, Arsip dan Pusat Informasi, Pelayanan dan Pengelolaan Perpustakaan > 025.4 Subject Analysis and Control/Subjek Analisis dan Kontrol Perpustakaan > 025.46 Classification of Specific Subject/Klasifikasi Khusus
500 Natural Science and Mathematics/Ilmu-ilmu Alam dan Matematika > 510 Mathematics/Matematika > 518 Numerical Analysis/Analisis Numerik, Analisa Numerik > 518.1 Algorithms/Algoritma
Divisions: Fakultas Ilmu Komputer > Informatika
Depositing User: ADELINA HASNA SETIAWATI
Date Deposited: 08 Nov 2022 03:10
Last Modified: 08 Nov 2022 03:10
URI: http://repository.mercubuana.ac.id/id/eprint/71405

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