Prototyping of Machine Learning at Traditional Market as Option for Sales and Purchasing Transaction

Michel Farrel Tomatala, Mihuandayani
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Abstract

Traditional market is an important part of the regional economy. Sales and purchasing transaction in traditional markets in any country is closely related to transactions which are done or executed in physical places. These days, along with technology enhancement, most things may be transformed into virtual reality. Artificial Intelligence technology in the application of machine learning is a potential that can make a significant contribution in various aspects, including the sales system. This study focuses on designing the prototyping of a machine learning application that is purposely used for sales and purchase transactions in the traditional market. This prototyping provides an alternative to traditional market traders who are focused on selling their goods at physical places. This study builds an application that provides a virtual platform for sales and purchase transactions. This study uses Convolutional Neural Networks (CNN) as one of the categories in Deep Learning which is part of Machine Learning. This study finds that the prototyping of machine learning applications for sales and purchase transactions at traditional markets might be a proper and beneficial solution for both traders and customers.
传统市场中机器学习作为买卖交易选项的原型
传统市场是区域经济的重要组成部分。在任何一个国家,传统市场上的销售和采购交易都与在实体场所进行或执行的交易密切相关。如今,随着技术的进步,大多数东西都可能变成虚拟现实。人工智能技术在机器学习中的应用是一种潜力,可以在包括销售系统在内的各个方面做出重大贡献。本研究的重点是设计一个机器学习应用程序的原型,该应用程序专门用于传统市场的销售和购买交易。这种原型为专注于在实体场所销售商品的传统市场交易者提供了另一种选择。本研究构建了一个应用程序,为销售和购买交易提供虚拟平台。本研究使用卷积神经网络(CNN)作为机器学习的一部分深度学习中的一个类别。本研究发现,在传统市场中,机器学习应用于销售和购买交易的原型可能对交易者和客户都是一个合适且有益的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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