ANALISIS KLASIFIKASI SENTIMEN TERHADAP PEMBELAJARAN ONLINE PADA ORANG TUA MURID SDN KAMAL MUARA 01 MENGGUNAKAN ALGORITMA NAIVE BAYES DAN SVM

WARSONO, TEGUH (2023) ANALISIS KLASIFIKASI SENTIMEN TERHADAP PEMBELAJARAN ONLINE PADA ORANG TUA MURID SDN KAMAL MUARA 01 MENGGUNAKAN ALGORITMA NAIVE BAYES DAN SVM. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

Since the outbreak of the Covid-19 virus, social restrictions have been implemented in all aspects of Indonesian society, including the education sector. Therefore, the Department of Education has implemented online learning to mitigate the spread of Covid-19. Online learning has evoked various emotions or sentiments among the community, ranging from negative, positive, to neutral. The purpose of this research is to classify the sentiments related to this policy, specifically focusing on the sentiments of parents/guardians of SDN Kamal Muara 01 students, using Google Form as the distribution method. In this study, sentiment classification is conducted using Naïve Bayes and SVM algorithms, achieving an accuracy score of 0.6790123456790124 for Naïve Bayes and 0.8395061728395061 for SVM. The sentiment data consists of 401 instances, with 249 instances of negative sentiment, 126 instances of positive sentiment, and 26 instances of neutral sentiment. Keywords: Covid-19, Indonesia, Online Learning, Classification, Sentiment Semenjak adanya wabah virus Covid-19 terjadi pembatasan sosial dalam segala aspek kehidupan masyarakat Indonesia, tidak terkecuali dalam aspek belajar mengajar. Maka dari itu Dinas Pendidikan menerapkan pembelajaran daring guna mengatasi penyebaran Covid-19 ini. Pada pembelajaran daring ini banyak menimbulkan berbagai macam emosi atau sentimen pada masyarakat, mulai dari yang negatif, positif maupun netral. Tujuan dari penelitian ini sendiri adalah untuk mengklasifikasi sentimen-sentimen terkait kebijakan tersebut yang mengacu secara rinci ke sentimen orang tua/wali murid SDN Kamal Muara 01, dengan penyebaran melalui Google Form. Pada penelitian ini untuk melakukan klasifikasi sentimen menggunakan Naïve Bayes dan SVM dengan nilai akurasi sebesar 0.6790123456790124 untuk Naïve Bayes dan 0.8395061728395061 untuk SVM. Dengan data sentimen sebanyak 401 terbagi atas sentimen negatif sebanyak 249, sentimen positif sebanyak 126 dan sentimen netral sebanyak 26. Kata Kunci : Covid-19, Indonesia, Pembelajaran Daring, Klasifikasi, Sentimen

Item Type: Thesis (S1)
Call Number CD: FIK/INFO. 23 112
NIM/NIDN Creators: 41519010136
Uncontrolled Keywords: Covid-19, Indonesia, Pembelajaran Daring, Klasifikasi, Sentimen
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 > 003 Systems/Sistem-sistem
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 > 003 Systems/Sistem-sistem > 003.5 Computer Modeling and Simulation/Model dan Simulasi Komputer
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 > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika > 004.1 General Works on Specific Types of Computers/Karya Umum tentang Tipe-tipe Khusus Komputer
Divisions: Fakultas Ilmu Komputer > Informatika
Depositing User: CALVIN PRASETYO
Date Deposited: 04 Oct 2023 08:16
Last Modified: 05 Oct 2023 04:02
URI: http://repository.mercubuana.ac.id/id/eprint/81979

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