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All Journal Indonesian Journal of Educational Studies LaGeografiA Phinisi Integration Review Jurnal Environmental Science SEIKO : Journal of Management & Business Referensi : Jurnal Ilmu Manajemen dan Akuntansi PINISI Discretion Review JEKPEND Jurnal Ekonomi dan Pendidikan Panrannuangku Jurnal Pengabdian Masyarakat International Journal of Social Science, Education, Communication and Economics Journal of Management, Accounting, General Finance and International Economic Issues (MARGINAL) Economics and Business Journal Journal of Artificial Intelligence and Digital Business ARMADA : Jurnal Penelitian Multidisiplin Innovative: Journal Of Social Science Research Journal of Economic Education and Entrepreneurship Studies Journal of Economics, Entrepreneurship, Management Business and Accounting Teknovokasi : Jurnal Pengabdian Masyarakat Pinisi Journal of Entrepreneurship Review Jurnal Sipakatau: Inovasi Pengabdian Masyarakat Nusantara Economics and Entrepreneurships Journals META - JOURNAL
Muhammad Rakib
Universitas Negeri Makassar
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Journal : Innovative: Journal Of Social Science Research

 1 
Sentiment Analysis of Electric Vehicles on Twitter Using Machine Learning Prameswari, Gusti Ayu Sri Adinda; Rakib, Muhammad; Aris, Valentino
Innovative: Journal Of Social Science Research Vol. 4 No. 4 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i4.12455

Abstract

Penelitian ini bertujuan untuk menganalisis sentimen pengguna Twitter terhadap kendaraan listrik menggunakan teknik pembelajaran mesin. Data dikumpulkan dari Twitter dengan menggunakan kata kunci terkait kendaraan listrik. Data yang diperoleh diolah melalui beberapa tahap seperti pembersihan data, tokenisasi, dan stemming. Selanjutnya, data dianalisis menggunakan tiga algoritma pembelajaran mesin: Support Vector Machine (SVM), Naive Bayes Classifier (NBC), dan Random Forest. Hasil penelitian menunjukkan bahwa algoritma SVM memberikan akurasi terbaik dalam mengklasifikasikan sentimen pengguna. Berdasarkan analisis diagram tulang ikan, ditemukan bahwa sentimen negatif pengguna terutama disebabkan oleh delapan faktor utama: baterai, infrastruktur pengisian daya, biaya awal, jangkauan, dukungan kebijakan, kinerja, variasi model, dan keandalan. Temuan ini diharapkan dapat memberikan wawasan bagi produsen kendaraan listrik untuk meningkatkan kualitas produk dan kepuasan pelanggan.
Co-Authors Abdul Rahman Ahmad, M. Ihsan Said Ainun Jariyah Amal Arfan, Amal Amalia, Syafira Ayu Andi Anggi Kemalasari Andi Naila Quin Azisah Aliasyahbana Andika Isma Andriani, Rusni Anwar Ramli Aryuniasari Asrib, Aman Rasyad Chalid Imran Musa Dewi Fatmarani Surianto Fajar, Akhmad Hajar Dewantara Halim, Nur Hasri Hasri Hasyim, Sitti Hajerah Imran, Chalid M. Ihsan Said M. Miftach Fakhri Marhawati, Marhawati Mufida, Nurul Muhammad Azis Muhammad Hasan Muhammad Jafar, Muhammad Muhammad Jufri Multhazam, Riana MUSTARI Najamuddin Najamuddin, Najamuddin Nasuha, Najamuddin Netti Herawati Nurdin Nurdin Nurhidayanti S. pabubung, Afrilya liliani Prameswari, Gusti Ayu Sri Adinda Rahmatullah Rahmatullah Rahmatullah Rahmatullah Rahmawati, Rahmawati Reni Reni, Reni Romansyah Sahabuddin Sari, Rosvika Sarinikmah, Sarinikmah Septiani, Ina Sholihah, Mahmudatus Suciyanti, Nurafni Sudarmi Sudarmi Sulolipu, Andi Annisa Supri Syafruddin Side Syam, Agus Tahir, Sumiati Taufikrahman, Taufikrahman Tawe, Amiruddin Valentino Aris, Valentino Wahidah Sanusi Yahya, Nurul Fajriah Yunus, Muchtar Yusuf SAP, Andi Muhammad Ridho Zulkarnain, Muhammad Qadafi