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All Journal Indonesian Journal of Data and Science Jurnal Pengabdian Kepada Masyarakat Abdi Putra
wiguna, sindy indira
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Humanities Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Mathematics Public Health

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Optimalisasi Teknologi Informasi Dalam Affiliate Marketing Untuk Strategi Promosi Digital wiguna, sindy indira; Erfina, Adhitia
Jurnal Pengabdian Kepada Masyarakat Abdi Putra Vol. 5 No. 3 (2025): September 2025
Publisher : Universitas Nusa Putra & Persatuan Insinyur Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52005/kpcpsx39

Abstract

Intership merupakan kegiatan belajar langsung yang dilakukan oleh mahasiswa, dengan tujuan untuk mengembangkan kemampuan. Dalam program Intership, mahasiswa mendapatkan pengalaman langsung di bawah bimbingan dan pengawasan dosen pembimbing yang memiliki kompetensi dan pengalaman profesional. Internship merupakan salah satu jalur ‘Study Completion’ bagi mahasiswa Universitas Nusa Putra, program internship ini dapat dilaksanakan di dalam negri maupun luar negeri, penulis berkesempatan Intership di PT Sogeh Bareng. Pada kegiatan ini penulis ditugaskan sebagai Affiliate Marketing, Program affiliate marketing di PT Sogeh Bareng dirancang untuk mendukung peningkatan penjualan, margin keuntungan, serta efisiensi transaksi, baik untuk perusahaan maupun mitra yang berpartisipasi. Pada kegiatan ini penulis berperan dalam bertugas mempromosikan layanan dan fitur aplikasi kepada calon pengguna di PT Sogeh Bareng, baik melalui media sosial, blog, atau kampanye digital lainnya ke dalam media sosial untuk menarik minat pengguna.
Sentiment Analysis of Public Opinion on Pi Network on Reddit Using FinBERT Wiguna, Sindy Indira; Erfina, Adhitia; Warman, Cecep
Indonesian Journal of Data and Science Vol. 6 No. 3 (2025): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v6i3.342

Abstract

The rapid growth of blockchain technology has led to the emergence of new cryptocurrencies, including Pi Network, which emphasizes accessibility through mobile-based mining. This study aims to answer the research question of whether FinBERT, a financial domain-specific transformer model, can effectively classify public sentiment in informal Reddit discussions related to Pi Network. FinBERT was first evaluated on a labeled financial sentiment dataset to assess its performance in a structured financial context before being applied to Reddit data. Model performance was measured using accuracy, precision, recall, and F1-score. After validation, the model was used to analyze one thousand twenty Reddit comments discussing Pi Network. Text preprocessing included cleaning, case folding, tokenization, stopword removal, stemming, and sequence standardization. The evaluation results show that FinBERT achieved an accuracy of eighty-five point ninety-eight percent on the financial validation dataset, with strong precision and recall across sentiment classes. When applied to Reddit comments, neutral sentiment was the most dominant, followed by positive and negative sentiments. Pi Network was selected as the case study because, unlike more established cryptocurrencies, it is still in an early stage of development and relies heavily on community participation, making public opinion particularly important for understanding its adoption and credibility
Co-Authors Adhitia Erfina Cecep Warman