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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer
Victory, Timotius
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Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering

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Review of Peer-to-Peer (P2P) Lending Based on Blockchain Victory, Timotius; Yazid, Setiadi
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 9 No. 4 (2023): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i4.27671

Abstract

Peer-to-Peer (P2P) lending is a financing business model that has gained popularity in recent years due to the ease of loan application, disbursement, and repayment processes. The volume of Peer-to-Peer (P2P) Lending transactions have a significant growth. One of the reasons for the popularity of Peer-to-Peer (P2P) lending is its utilization of technology in both the application and loan repayment processes. One such technology gaining traction in Peer-to-Peer (P2P) lending is blockchain technology. The popularity of blockchain technology lies in its ability to enhance the transparency of the transaction process. This literature study aims to address three main questions: What are the characteristics of blockchain suitable for Peer-to-Peer (P2P) lending , the benefits of implementing blockchain technology in Peer-to-Peer (P2P) lending and the challenges of Peer-to-Peer (P2P) lending based on blockchain. The findings reveal that there are characteristics of blockchain that can be applied to Peer-to-Peer (P2P) lending, bringing numerous benefits to the overall Peer-to-Peer (P2P) lending process. However, challenges persist in the implementation of blockchain technology in Peer-to-Peer (P2P) lending. The insights gained from this literature review are intended to guide researchers interested in studying the application of blockchain technology in the context of Peer-to-Peer (P2P) lending.
Analisis Sentimen Ulasan Pengguna pada Aplikasi Tunaiku dengan Pendekatan Machine Learning Timotius Victory; Dwi Diana Wazaumi
REMIK: Riset dan E-Jurnal Manajemen Informatika Komputer Vol. 10 No. 1 (2026): Volume 10 Nomor 1 Januari 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/remik.v10i1.15839

Abstract

Aplikasi Tunaiku, layanan pinjaman online dari Amar Bank, telah diunduh oleh lebih dari 10 juta pengguna dan memiliki lebih dari 1,2 juta ulasan. Ulasan tersebut berperan penting dalam meningkatkan kualitas layanan, karena mencerminkan pengalaman dan umpan balik pengguna. Penelitian ini menganalisis sentimen ulasan pengguna menggunakan pendekatan machine learning untuk mengidentifikasi tren sentimen positif dan negatif. Dataset terdiri dari 5.000 ulasan yang diambil dari Google Play Store. Setelah pre-processing dan pembobotan kata menggunakan TF-IDF, tiga model machine learning digunakan: Support Vector Machine (SVM), Logistic Regression, dan Naive Bayes. Evaluasi dilakukan dengan metrik akurasi, precision, recall, dan F1-score. Hasilnya menunjukkan bahwa SVM memiliki performa terbaik dengan akurasi 96,85%, diikuti Logistic Regression dengan 95,74%, dan Naive Bayes dengan 95,63%.
Co-Authors Dwi Diana Wazaumi Setiadi Yazid, Setiadi