ANALISIS SENTIMEN OPINI MASYARAKAT DI TWITTER TENTANG PENERAPAN KURIKULUM MERDEKA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE

INTAN RAMADHANTI, . (2023) ANALISIS SENTIMEN OPINI MASYARAKAT DI TWITTER TENTANG PENERAPAN KURIKULUM MERDEKA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE. Sarjana thesis, UNIVERSITAS NEGERI JAKARTA.

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Abstract

Pada tahun 2022 Kepala Badan Standar, Kurikulum, Asesmen Pendidikan (BSKAP) No. 044/H/KR/2022 mengeluarkan Surat Keputusan (SK) tentang Satuan Pendidikan Pelaksanaan Implementasi Kurikulum Merdeka pada Tahun Ajaran 2022/2023 pada 140 ribu satuan pendidikan di Indonesia. Penerapan kurikulum baru ini menimbulkan berbagai opini masyarakat pada media sosial Twitter. Oleh karena itu dilakukan penelitian analisis sentimen masyarakat terhadap penerapan kurikulum merdeka. Tweet yang diambil adalah tweet dengan sentimen positif dan negatif, kemudian data diolah menggunakan Jupyter Notebook dan bahasa pemrograman Python serta menggunakan algoritma SVM. Penelitian ini bertujuan apakah algoritma SVM baik dalam melakukan klasifikasi teks untuk analisis sentimen penerapan kurikulum merdeka dengan melihat nilai akurasi yang didapatkan dan mendeskripsikan bagaimana sentimen masyarakat pada media sosial Twitter tentang penerapan kurikulum merdeka. Data yang digunakan adalah dataset sebanyak 1.186 tweet, yaitu 363 tweet positif dan 823 tweet negatif. Hasil penelitian didapatkan nilai akurasi algoritma Support Vector Machine dengan kernel linear, polynomial, dan sigmoid adalah 91,82% juga kernel RBF sebesar 89,88%. Serta dilihat dari hasil analisis sentimen penerapan kurikulum merdeka lebih banyak respon negatif salah satunya mengenai terlalu banyaknya tugas dan proyek yang membuat peserta didik merasa capai dan stres. ***** In 2022 the Head of Standards, Curriculum, Education Assessment (BSKAP) No. 044/H/KR/2022 issued a Decree (SK) regarding Education Units for the Implementation of the kurikulum merdeka in the 2022/2023 Academic Year in 140 thousand educational units in Indonesia. The implementation of this new curriculum raises various public opinions on social media Twitter. Therefore, research on the analysis of public sentiment on the implementation of the independent curriculum was carried out. The tweets taken are tweets with positive and negative sentiments, then the data is processed using Jupyter Notebook and the Python programming language and using the SVM algorithm. This study aims to see whether the SVM algorithm is good at carrying out text classification for sentiment analysis of the implementation of the kurikulum merdea by looking at the accuracy value obtained and describing how public’s sentiment on social media Twitter is about implementing the kurikulum merdeka. The data used is a dataset of 1,186 tweets, that is 363 positive tweets and 823 negative tweets. The results showed that the accuracy of the Support Vector Machine algorithm with linear, polynomial, and sigmoid kernels was 91.82% and the RBF kernel was 89.88%. As well as seen from the results of the sentiment analysis of implementing the kurikulum merdeka there were more negative responses, one of which was regarding too many assignments and projects that made students feel tired and stressed.

Item Type:	Thesis (Sarjana)
Additional Information:	1). Dr. Widodo, S.Kom., M.Kom. ; 2). Murien Nugraheni, S.T., M.Cs.
Subjects:	Teknologi dan Ilmu Terapan > Teknik Komputer
Divisions:	FT > S1 Pendidikan Teknik Informatika Komputer
Depositing User:	Users 19296 not found.
Date Deposited:	31 Aug 2023 05:03
Last Modified:	31 Aug 2023 05:03
URI:	http://repository.unj.ac.id/id/eprint/40107

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