<?xml version='1.0' encoding='UTF-8'?><metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns="http://dublincore.org/documents/dcmi-terms/"><dcterms:title>Analysis of Financial Literacy Level from Shoopeepay and OVO E-Wallet user using LDA-Based Topic Modelling</dcterms:title><dcterms:identifier>https://doi.org/10.34820/FK2/OQYEQX</dcterms:identifier><dcterms:creator>IRADIANTY, ALDILLA</dcterms:creator><dcterms:publisher>Telkom University Dataverse</dcterms:publisher><dcterms:issued>2022-04-27</dcterms:issued><dcterms:modified>2022-04-27T04:17:07Z</dcterms:modified><dcterms:description>Konten dalam social media dimanfaatkan untuk mengetahui tingkat literasi keuangan pengguna Shopeepay dan OVO, dengan metode text mining yaitu topic modeling dengan pendekatan latent dirichlet allocation (LDA)</dcterms:description><dcterms:subject>Business and Management</dcterms:subject><dcterms:subject>e-wallet, user generated content, topic modelling, latent dirichlet allocation, financial literacy</dcterms:subject><dcterms:contributor>IRADIANTY, ALDILLA</dcterms:contributor><dcterms:dateSubmitted>2022-04-27</dcterms:dateSubmitted><dcterms:license>CC0</dcterms:license><dcterms:rights>CC0 Waiver</dcterms:rights></metadata>