Analisis Sentimen Masyarakat Tentang Naiknya Harga BBM Dengan Metode Fasttext dan Naïve Bayes
DOI:
https://doi.org/10.29407/inotek.v7i1.3405Abstract
Pada 3 September 2022, pemerintah menginformasikan melalui media sosial bahwa penyesuaian harga BBM dilakukan karena kenaikan harga minyak dunia dan subsidi BBM yang tidak tepat sasaran. Tidak sedikit masyarakat memberikan komentar tentang naiknya harga BBM dengan opini yang berbeda-beda sehingga sulit diklasifikasi. Berdasarakan uraian tersebut peneliti tertarik melakukan analisis sentimen masyarakat tentang naiknya harga BBM dengan metode vektorisasi Fasttext dan Gaussian Naïve Bayes yang bertujuan untuk mengklasifikasi komentar. Data komentar berasal dari komentar Youtube CNN Indonesia sebanyak 3000 komentar. Proses pemberian label dilakukan oleh sistem yang berdasar pada perhitungan nilai polarity menggunakan Vader Sentiment. Validasi k-fold dimana k=10 mendapat hasil terbaik dengan akurasi sebesar 73,67% dan data negatif lebih mendominasi model.
Keywords:
Analisis Sentimen, Fasttext, Naïve Bayes##plugins.themes.default.displayStats.downloads##
References
S. Kemp, “Digital 2022: Indonesia — DataReportal – Global Digital Insights,” Global Digital Insights. pp. 1–103, 2022. Accessed: Oct. 24, 2022. [Online]. Available: https://datareportal.com/reports/digital-2022-indonesia
F. A. Nugraha, N. H. Harai, and R. Habibi, Analisis Sentimen Terhadap Pembatasan Sosial Menggunakan Deep Learning. Bandung: Kreatif Industri Nusantara, 2020. Accessed: Nov. 19, 2022. [Online].
S. Mujahidin, B. Prasetio, and M. C. C. Utomo, “Implementasi Analisis Sentimen Masyarakat Mengenai Kenaikan Harga BBM Pada Komentar YoutubeDengan Metode Gaussian naïve bayes,” J. Vocat. Tek. Elektron. dan Inform., vol. 10, no. 3, pp. 17–24, 2022, [Online].
M. Al Khadafi, K. P. Kartika, and F. Febrinita, “PENERAPAN METODE NAÏVE BAYES CLASSIFIER DAN LEXICON BASED UNTUK ANALISIS SENTIMEN CYBERBULLYING PADA BPJS,” J. Mhs. Tek. Inform., vol. 6, no. 2, pp. 725–733, 2022.
D. Duei Putri, G. F. Nama, and W. E. Sulistiono, “Analisis Sentimen Kinerja Dewan Perwakilan Rakyat (DPR) Pada Twitter Menggunakan Metode Naive Bayes Classifier,” J. Inform. dan Tek. Elektro Terap., vol. 10, no. 1, pp. 34–40, 2022, doi: 10.23960/jitet.v10i1.2262.
C. F. Hasri and D. Alita, “Penerapan Metode Naïve Bayes Classifier Dan Support Vector Machine Pada Analisis Sentimen Terhadap Dampak Virus Corona Di Twitter,” J. Inform. dan Rekayasa Perangkat Lunak, vol. 3, no. 2, pp. 145–160, 2022, [Online].
A. Nurdin, B. Anggo Seno Aji, A. Bustamin, and Z. Abidin, “Perbandingan Kinerja Word Embedding Word2Vec, Glove, Dan Fasttext Pada Klasifikasi Teks,” J. Tekno Kompak, vol. 14, no. 2, p. 74, 2020, doi: 10.33365/jtk.v14i2.732.
Siti Khomsah, Rima Dias Ramadhani, and Sena Wijaya, “The Accuracy Comparison Between Word2Vec and FastText On Sentiment Analysis of Hotel Reviews,” J. RESTI (Rekayasa Sist. dan Teknol. Informasi), vol. 6, no. 3, pp. 352–358, 2022, doi: 10.29207/resti.v6i3.3711.
D. M. K. Oshadi and S. Thelijjagoda, “AppGuider: Feature Comparison System using Neural Network with FastText and Aspect-based Sentiment Analysis on Play Store User Reviews,” 3rd Int. Conf. Smart Electron. Commun. ICOSEC 2022 - Proc., pp. 1148–1155, 2022, doi: 10.1109/ICOSEC54921.2022.9952093.
E. Budianita, M. Fikry, and F. Yanto, “Klasifikasi Sentiment Review Aplikasi MyPertamina Menggunakan Word Embedding FastText dan SVM ( Support Vector Machine ),” J. Sist. Komput. dan Inform., vol. 4, pp. 526–534, 2023, doi: 10.30865/json.v4i3.5695.
M. Ramdhan, Metode Penelitian. Surabaya, 2021. Accessed: Nov. 05, 2022. [Online].
D. Nicolaus, Metodologi Penelitian Kuantitatif: Beberapa Konsep Dasar Untuk Penulisan Skripsi & Analisis Data dengan SPSS. 2019. Accessed: Nov. 05, 2022. [Online].
T. Sanubari, P. Cahyo, and N. Riza, “Odol (one desa one product unggulan online) penerapan metode Naive Bayes pada pengembangan aplikasi e-commerce menggunakan Codeigniter,” Kreatif, 2020.
S. Siyoto and M. A. Sodik, “Dasar Metodologi Penelitian.” Literasi Media Publising, Yogjakarta, pp. 68–70, 2015. Accessed: Nov. 05, 2022. [Online].
A. Beheshti, S. Ghodratnama, M. Elahi, and H. Farhood, Social Data Analytics. CRC press, 2022. doi: 10.1201/9781003260141.
A. Sanjaya and S. D. Sasongko, “UJI KEMIRIPAN KALIMAT MENGGUNAKAN FUNGSI TERBILANG PADA PRE-PROCESSING DAN COSINE SIMILARITY DALAM BAHASA INDONESIA,” J. Ilm. Nero, vol. 7, no. 2, pp. 95–104, 2022.
J. Bhattacharjee, fastText Quick Start Guide: Get started with Facebook’s library for text representation and classification. Packt Publishing, 2018.
A. Kedia and M. Rasu, Hands-On - Python Natural Language Processing. 2020.
J. Brownlee, “Master Machine Learning Algorithms: Discover how they work and implement them from scratch.,” Mach. Learn. Mastery, pp. 1–163, 2016, [Online].
T. T. Wong and P. Y. Yeh, “Reliable Accuracy Estimates from k-Fold Cross Validation,” IEEE Trans. Knowl. Data Eng., vol. 32, no. 8, pp. 1586–1594, Aug. 2020, doi: 10.1109/TKDE.2019.2912815.
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