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CREATION
Title : UKARA: A Fast and Simple Automatic Short Answer Scoring System for Bahasa Indonesia
Author :

Guntur Budi Herwanto, S.Kom., M.Cs. (1) Yunita Sari, S.Kom., M.Sc., Ph.D. (2) Drs. Bambang Nurcahyo Prastowo, M.Sc. (3) Dr. Mardhani Riasetiawan, SE Ak, M.T. (4) Isna Alfi Bustoni, S.T., M.Eng. (5) Indra Hidayatullah (6)
Date : 0 2019
Keyword : Automatic assessment, Bahasa Indonesia, Machine Learning, Natural Language Processing Automatic assessment, Bahasa Indonesia, Machine Learning, Natural Language Processing
Abstract : This paper presents UKARA, a fast and simple automatic short-answer scoring system for Bahasa Indonesia. Automatic short-answer scoring holds an important role in speeding up automatic assessment process. Although this area has been widely explored, only very limited number of previous work have studied Bahasa Indonesia. One of the major challenges in this field is the different type of questions which require different assessments. We are addressing this problem by implementing a combination of Natural Language Processing (NLP) and supervised machine learning techniques. Our system works by training a classifier model on human-labeled data. Using three different types of Programme for International Student Assessment (PISA) student responses, our system successfully produced the F1-score above 97% and 70% on dichotomous and polytomous scoring types respectively. Moreover, UKARA provides a user-friendly interface which is simple and easy to use. UKARA offers a flexibility for human grader to do re-scoring and re-training the model until the optimal performance is obtained.
Group of Knowledge :
Level : Internasional
Status :
Published
Document
No Title Document Type Action
1 105-119-1-PB.pdf
Document Type : Seminar Sampul Prosiding
Seminar Sampul Prosiding View
2 ARTIKEL.pdf
Document Type : Artikel dan Sertifikat/Bukti Kehadiran/Pasport (jika tidak ada sertifikat)
Artikel dan Sertifikat/Bukti Kehadiran/Pasport (jika tidak ada sertifikat) View
3 ICEAP_PUSPENDIK.pdf
Document Type : [PAK] Full Dokumen
[PAK] Full Dokumen View
4 prosiding_2061646_d41c28e8132208dc25ec171141a880a0.pdf
Document Type : Cek Similarity
Cek Similarity View