Analisis Sentimen Opini Masyarakat Terhadap Pinjaman Online Menggunakan IndoBERTweet

Albaar, Fathimah Azzahra (2024) Analisis Sentimen Opini Masyarakat Terhadap Pinjaman Online Menggunakan IndoBERTweet. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Layanan pinjaman online (pinjol) di Indonesia mengalami pertumbuhan pesat seiring dengan globalisasi dan transformasi digital, didorong oleh meningkatnya kebutuhan akses pembiayaan yang cepat dan mudah. Namun, dalam perkembangannya, praktik ilegal yang merugikan masyarakat dalam layanan pinjaman ini semakin marak, sehingga menjadi sorotan di berbagai platform media sosial, terutama Twitter. Merespon hal tersebut, pada November 2023, Otoritas Jasa Keuangan (OJK) menerbitkan regulasi baru yang mengatur penyelenggaraan Financial Technology (Fintech) peer-to-peer (P2P) lending, termasuk layanan pinjol, untuk meningkatkan perlindungan konsumen dan menjaga keseimbangan industri Fintech. Penelitian ini menganalisis opini masyarakat di Twitter setelah penerapan regulasi tersebut menggunakan model IndoBERTweet, yang dioptimalkan untuk pemrosesan teks Twitter berbahasa Indonesia. Model ini berhasil mencapai akurasi sebesar 74% dan F1-macro sebesar 70% dalam klasifikasi sentimen. Hasil analisis menunjukkan kecenderungan sentimen negatif terhadap pinjol, dengan mayoritas tweet mengungkapkan ketidakpuasan terkait perlindungan konsumen dan keamanan data pribadi. Hal ini mengindikasikan bahwa meskipun regulasi baru telah diterapkan, masih terdapat kesenjangan antara regulasi dan implementasinya di lapangan. Isu-isu seperti keamanan data dan penyalahgunaan identitas masih menjadi kekhawatiran Utama masyarakat. Penelitian ini memberikan informasi penting mengenai efektivitas regulasi terbaru dan dapat menjadi dasar dalam penyesuaian kebijakan untuk meningkatkan perlindungan konsumen, memperbaiki praktik industri pinjol, dan membangun kepercayaan masyarakat terhadap layanan tersebut.
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Online lending services (pinjol) in Indonesia are experiencing rapid growth in line with globalization and digital transformation, driven by the increasing need for quick and easy access to financing. However, in its development, illegal practices that harm the public in this loan service are increasingly widespread, which has become a highlight on various social media platforms, especially Twitter. In response, in November 2023, the Financial Services Authority (OJK) issued new regulations governing the implementation of Financial Technology (Fintech) peer-to-peer (P2P) lending, including pinjol services, to improve consumer protection and maintain a balanced Fintech industry. This study analyzes public opinion on Twitter after the implementation of the regulation using the IndoBERTweet model, which is optimized for Indonesian Twitter text processing. The model achieved 74% accuracy and 70% F1-macro in sentiment classification. The analysis results showed a trend towards negative sentiment towards pinjol, with the majority of tweets expressing dissatisfaction regarding consumer protection and personal data security. This indicates that although new regulations have been implemented, there is still a gap between regulations and their implementation on the ground. Issues such as data security and identity misuse are still major concerns for the public. This research provides important information on the effectiveness of the new regulations and can serve as a basis for policy adjustments to enhance consumer protection, improve lending industry practices, and build public trust in these services.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Pinjaman Online, Analisis Sentimen, IndoBERTweet, OJK, Online Lending, Sentiment analysis
Subjects:	H Social Sciences > HG Finance H Social Sciences > HJ Public Finance Q Science > QA Mathematics > QA76.87 Neural networks (Computer Science) Q Science > QA Mathematics > QA76.9.D343 Data mining. Querying (Computer science)
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Mathematics > 44201-(S1) Undergraduate Thesis
Depositing User:	Fathimah Azzahra Albaar
Date Deposited:	11 Sep 2024 04:17
Last Modified:	11 Sep 2024 04:17
URI:	http://repository.its.ac.id/id/eprint/114492

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