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WEB BASED AUTOMATED ESSAY GRADING SYSTEM USING LATENT SEMANTIC ANALYSIS METHOD FOR INDONESIAN LANGUAGE

机译:基于Web的自动论文分级系统对印尼语言的潜在语义分析方法

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Grading system is a mechanism used to determine student's ability of the given material of the studying process. Essay is one form of grading, where there are no choices of answer, and student must answer in sentence. Essay answers may vary greatly between each exam participant, depending on their own thought. Methods used in automated essay grading system nowadays are still under research because they need to follow some specific rules. Some of the methods are Natural Language Processing, Statistical Approach, Bayesian Text Classification, and Latent Semantic Analysis [1]. One of the grading methods, i.e. Latent Semantic Analysis (LSA), which uses matrix algebra to compare between expected answer and student's essay answer [2]. In this paper, we are using the LSA technique for Web Based Automated Essay Grading for Indonesian Language (Bahasa) and prove that we achieve 83% for the agreement with Human Raters.
机译:评分系统是用于确定学生学习过程的材料能力的机制。论文是一种评分的一种形式,没有选择的选择,学生必须在句子中回答。在每位考试参与者之间,论文答案可能因自己的想法而变化。现在,自动论文分级系统中使用的方法仍在研究中,因为他们需要遵循一些具体规则。一些方法是自然语言处理,统计方法,贝叶斯文本分类,潜在语义分析[1]。其中一个分级方法,即潜在语义分析(LSA),它使用矩阵代数来比较预期的答案和学生的论文答案[2]。在本文中,我们正在为印度尼西亚语(巴哈萨)的基于Web的自动论文分级使用LSA技术,并证明我们与人类评估者协议达到83%。

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