ANALISIS EFEKTIVITAS METODE SUPPORT VECTOR MACHINE (SVM) DALAM MENGURANGI BERITA HOAX BENCANA ALAM DARI DATA TWITTER
DOI:
https://doi.org/10.33143/jics.v10i1.3952Abstract
Bencana alam merupakan fenomena yang sering terjadi di kepulauan negara Indonesia. Berdasarkan data dari Badan Nasional Penanggulangan Bencana (BNPB), sejak awal tahun hingga bulan Januari 2022, telah terjadi 1.296 bencana alam. Dampak dari bencana alam ini mencakup kehancuran fasilitas umum, jalan, jembatan, serta kerusakan pada rumah dan alat transportasi seperti mobil dan sepeda motor. Kerusakan yang disebabkan oleh bencana alam bersifat pasti, sehingga masyarakat cenderung aktif mencari dan memberikan informasi terkait bencana tersebut. Media sosial, khususnya Twitter, telah dimanfaatkan sebagai media penyampaian informasi yang lebih cepat dibandingkan televisi dan radio. Namun, tidak semua informasi yang dibagikan oleh pengguna Twitter adalah benar, terdapat berita hoax atau palsu terkait bencana alam yang beredar. Oleh karena itu, diperlukan sebuah Sistem Penunjang Keputusan untuk menyaring informasi bencana alam dari media sosial Twitter menggunakan Metode Support Vector Machine (SVM) berbasis website. Penelitian ini bertujuan untuk mengembangkan sebuah sistem yang dapat membantu masyarakat dalam memverifikasi keakuratan informasi mengenai bencana alam. Sistem ini memanfaatkan Twitter API Stream untuk mengumpulkan data, kemudian menggunakan metode SVM untuk mengklasifikasikan informasi tersebut sebagai hoax atau valid. SVM dipilih karena memiliki performa yang baik dalam kasus klasifikasi, dengan akurasi yang lebih tinggi dibandingkan metode lainnya. Hasil dari penelitian ini adalah sebuah Sistem Penunjang Keputusan Bencana Alam dari Data Media Sosial Twitter menggunakan Metode Support Vector Machine Berbasis Website. Sistem ini diharapkan dapat memberikan kontribusi positif dalam upaya mengantisipasi dan merespons bencana alam dengan menyediakan informasi yang akurat dan dapat diandalkan.
Kata Kunci: Bencana Alam, Twitter, Support Vector Machine (SVM), Support Vector Machine (SVM), Sistem Penunjang Keputusan, Berita Hoax.
Natural disasters are a frequent phenomenon in the archipelago of Indonesia. According to data from the National Disaster Management Agency (BNPB), 1,296 natural disasters occurred from the beginning of the year until January 2022. The impact of these natural disasters includes the destruction of public facilities, roads, bridges, as well as damage to houses and means of transportation such as cars and motorcycles. The damage caused by natural disasters is certain, prompting the public to actively seek and provide information related to these events. Social media, particularly Twitter, has been utilized as a faster means of information dissemination compared to television and radio. However, not all information shared by Twitter users is accurate; there are hoax or fake news about natural disasters circulating. Therefore, a Decision Support System is needed to filter natural disaster information from Twitter using the Support Vector Machine (SVM) method based on a website. This study aims to develop a system that can assist the public in verifying the accuracy of information regarding natural disasters. The system leverages the Twitter API Stream to collect data and then uses the SVM method to classify the information as either hoax or valid. SVM was chosen due to its strong performance in classification cases, offering higher accuracy for Twitter data compared to other methods. The result of this research is a Decision Support System for Natural Disasters from Twitter Data Using a Website-Based Support Vector Machine Method. This system is expected to provide a positive contribution in anticipating and responding to natural disasters by offering accurate and reliable information.
Keywords: Natural Disasters, Twitter, Support Vector Machine (SVM), Decision Support System, Hoax News.
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