Analisis Sentimen Terhadap Bantuan Langsung Tunai (BLT) Bahan Bakar Minyak (BBM) Menggunakan Support Vector Machine
Sentiment Analysis of Cash Direct Assistance Distribution for Fuel Oil Using Support Vector Machine
DOI:
https://doi.org/10.57152/malcom.v3i1.590Keywords:
Beban Ekonomi, BBM, Pemerintah, Sentiment, Support Vector MachineAbstract
Bahan bakar minyak (BBM) merupakan salah satu kebutuhan pokok masyarakat. Namun, harga BBM yang tinggi dapat menyebabkan beban ekonomi bagi masyarakat yang tidak mampu. Dalam rangka mengatasi masalah ini, pemerintah telah menerapkan program Bantuan Langsung Tunai (BLT) sebagai bentuk bantuan bagi masyarakat yang mengalami ketidakseimbangan ekonomi. Tujuan dari penelitian ini adalah untuk menganalisis sentimen masyarakat terhadap program Bantuan Langsung Tunai (BLT) Bahan Bakar Minyak (BBM). Penelitian ini menggunakan teknik pengumpulan data scraping, yaitu mengambil data dari media sosial Instagram. Jumlah yang digunakan sebanyak 356 data. Proses klasifikasi yang digunakan berdasarkan model pembelajaran dari Support Vector Machine (SVM) dan evaluasi dengan confusion matrix. Dari hasil perhitungan, terlihat bahwa proses klasifikasi sentimen menggunakan metode SVM didapatkan tingkat accuracy 85,98%, rata-rata nilai precision 82,25%, nilai rata-rata recall 66,35%, dan nilai rata-rata f-measure 73,44%. Hasil yang diperoleh menunjukkan bahwa sentimen negatif lebih banyak daripada sentimen positif, dengan masing-masing persentase 78.61% dan 21.34%. Dari analisis sentimen yang dilakukan, ditemukan bahwa sentimen negatif adalah yang paling banyak muncul, hal ini menunjukkan bahwa masyarakat tidak puas dengan bantuan langsung tunai BBM. Sebagai respon terhadap sentimen negatif yang dominan, perlu diterapkan strategi untuk melakukan pemerataan bantuan langsung tunai dan pendata’an yang terstruktur agar tingkat kekecewaan masyarakat dapat diminimalisir.
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