使用集成投票方法预测PrivyID应用程序评论作为电子文档(e-doc)使用

Riza Fahlapi, H. Hermanto, T. Asra, A. Y. Kuntoro, R. O. Nitra, L. Effendi
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引用次数: 0

摘要

印度尼西亚正在通过使用电子文件开发一种更高效和有效的金融技术(Fintek)支持服务创新。被金融科技公司用作参考和利用的电子文档提供商业务是PrivyID。在本研究中,是如何在评论方面使用PrivyID应用程序进行数字签名服务,使其成为合法的电子文档。“私钥通”所开发的电子文件,是社会所需的商业及个人交易的服务供应商,要使用电子文件,必须有基于网络的应用平台及流动应用程序。基于818个PrivyID应用程序用户数据,对PrivyID应用程序作为电子文档(e-doc)使用时的评论预测进行了更深入的研究。该研究将3(3)种算法(k-Nearest Neighbor, Na¨ıve Bayes和C4.5)结合在Ensembles Vote方法中,得到了准确率为86.80的最佳预测评论值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction of PrivyID Application Comments Use as an Electronic Document (e-doc) using the Ensemble Vote method
Indonesia is developing one of the more efficient and effective Financial Technology (Fintek) support services innovations by using electronic documents. The Electronic Document provider business that is used as a reference and utilized by fintech companies is PrivyID. In this study, how is the commentary aspect of using the PrivyID application for digital signature services to become a legal electronic document. Web-based application platforms and mobile applications in the community are indispensable for the use of Electronic Documents developed by PrivyID as a service provider in business and personal transactions that are needed by the community. More in-depth research regarding the Prediction of PrivyID Application Comments in Its Use as an Electronic Document (e-doc) taken from 818 data of PrivyID application users. The research was conducted by combining 3 (three) algorithms (k-Nearest Neighbor, Na¨ıve Bayes, and C4.5) in the Ensembles Vote method which resulted in the best Prediction Comment value with an accuracy of 86.80. 
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