A Proposed Framework for Essay Answer Processing based on Computational

Autor: Indra Hidayatulloh, Yunita Sari, Mardhani Riasetiawan, Bambang Nurcahyo Prastowo, Teguh Bharata Adji, Isna Alfi Busthoni, Guntur Budi Herwanto
Rok vydání: 2018
Předmět:
Zdroj: ICEAP Proceeding Book Vol 2.
DOI: 10.26499/iceap.v2i1.96
Popis: This paper proposed processing framework in essay answer for Automatic Scoring System based on computational. Framework is built with the initial process by normalizing through stop words removal, building case homogeneous, stemming, common spelling mistakes correction, and acronym and common abbreviation analysis. The next step is to examine the similarity by carrying out similarity and classification analysis. The process in the Framework that has been built using reference essay answers as references that will be examined for similarity with the answer to the question. Similarities are matched by using features generated in the features extraction process. Then the training classification process is carried out to produce the model. The model is used to determine the classification score. Classification scores are validated by looking at the value of accuracy and the resulting similarity scores. This framework can be used to process essay problem patterns which have 2 predetermined classification classes, although for more classifications it can be handled with an improved algorithm implemented.
Databáze: OpenAIRE