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Designing and Implementing an Organoleptic Test Application for Food Products Using Android Based Decision Tree Algorithm

机译:使用基于Android的决策树算法设计和实施食品的感官试验应用

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The development of food and beverage products increases over the years. The high level of food consumption led to the presence of new food and beverage brands produced in Salatiga. In accordance with this fact, Organoleptic Tests or in other words evaluation of food products could be conducted well if the obtained dataset had a complete, rapid, and accurate information. The required information could be clarified into the dataset that was used to calculate the testing. Manually calculating the process was a problem that usually appeared. As a result, losing or having a broken report on the organoleptic test often occurred. Mileage of the research setting became another problem that appeared when the research conducted out of the town, Salatiga. A combination of R&D method and application of algorithm was implemented in this research by using the performed stages. These stages started from the identification of problems to the testing of the systems. During the process of organoleptic testing, Weka 3.8.2 was used as a tool to test the C4.5 algorithm and an implementation of the applied algorithm on the android. The results of this study revealed that the average classification accuracy of the J48 algorithm in Weka could achieve above 90% accuracy and average score of hedonic scaling system was in “agree” category. It also showed that the algorithm and the testing of the systems which implemented on android has a credible performance in classifying data.
机译:食品和饮料产品的开发多年来增加。高水平的食物消耗导致萨拉格拉生产的新食品和饮料品牌。根据这一事实,如果获得的数据集具有完整,快速和准确的信息,可以很好地对食品的感官测试或食物的评估。可以澄清所需信息,用于计算测试的数据集。手动计算该过程是通常出现的问题。结果,经常发生对感官测试的破裂或有破裂的报告。研究环境的里程变成了另一个出现的另一个问题,这些问题出现在城镇,Salatiga。通过使用所执行的阶段,在该研究中实施了R&D方法和算法应用的组合。这些阶段从识别系统的测试时开始。在感官测试过程中,Weka 3.8.2用作测试C4.5算法的工具和Android上应用算法的实现。本研究的结果表明,魏卡J48算法的平均分类准确性可以达到90%以上的精度,蜂窝缩放系统的平均得分是“同意”类别。它还表明,在Android上实现的系统的算法和测试在分类数据中具有可靠的性能。

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