Pelatihan Lecturer Optimize Questions and Answers (LOQA) untuk Mahasiswa Berkebutuhan Khusus
Abstract
About 15 percent of the world's population are people with disabilities. They are considered the largest minority group in the world. About 82 percent of people with disabilities. Every individual in this world has the same position, rights, obligations and opportunities and roles in all aspects of life and livelihood as other individuals. Persons with disabilities as part of Indonesian citizens (WNI) have the same guarantee for respect, protection and fulfillment of the rights of persons with disabilities, especially the right to education. The obstacles and challenges of studying in higher education for students with special needs are definitely greater than the difficulties faced by regular students. In addition to the limited disability service units in universities, another cause is communication between lecturers and students with special needs. Communication plays a very important role in relation to the formation of society, the communication situation is considered important because the process takes place in a dialogical manner. Taking into account this background and fulfilling the request and/or expectations, the Lecturer Optimize Questions and Answers (LOQA) Training for Students with Special Needs is carried out, assistive technology (assistive technology) which we propose as a form of commitment to realizing inclusive services for students with special needs at Lancang University. Yellow, in this case, facilitates hearing impaired students in accessing lectures by collaborating Chatbot with the E-Learning system, so that problems and obstacles in communicating by students with special needs that are currently felt can be accommodated through the LOQA application.
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References
Amrizal, V. (2018). Penerapan Metode Term Frequency Inverse Document Frequency (Tf-Idf) Dan Cosine Similarity Pada Sistem Temu Kembali Informasi Untuk Mengetahui Syarah Hadits Berbasis Web (Studi Kasus: Hadits Shahih Bukhari-Muslim). Jurnal Teknik Informatika, 11(2), 149–164. https://doi.org/10.15408/jti.v11i2.8 623
Andita Dwiyoga Tahitoe, D. P. (2010). Implementasi Modifikasi Enhanced Confix Stripping Stemmer Untuk Bahasa Indonesia Dengan Metode Corpus Based Stemming. Jurnal Ilmiah, 1–15.
Feng, X., Li, S., Yuan, C., Zeng, P., & Sun, Y. (2018). Prediction of Slope Stability using Naive Bayes Classifier. KSCE Journal of Civil Engineering, 22(3), 941–950. https://doi.org/10.1007/s12205-018-1337-3
H, A. T. J. (2015). Preprocessing Text untuk Meminimalisir Kata yang Tidak Berarti dalam Proses Text Mining. Informatika UPGRIS, 1, 1–9.
Hengki, M., & Wahyudi, M. (2020). Klasifikasi Algoritma Naïve Bayes dan SVM Berbasis PSO Dalam Memprediksi Spam Email Pada Hotline-Sapto. Paradigma - Jurnal Komputer Dan Informatika, 22(1), 61–67. https://doi.org/10.31294/p.v22i1.78 42
Kang, H., Yoo, S. J., & Han, D. (2012). Senti-lexicon and improved Naïve Bayes algorithms for sentiment analysis of restaurant reviews. Expert Systems with Applications, 39(5), 6000–6010. https://doi.org/10.1016/j.eswa.2011.11.107
Nwankwo, W. (2018). Interactive Advising with Bots: Improving Academic Excellence in Educational Establishments. American Journal of Operations Management and Information Systems, 3(1), 6. https://doi.org/10.11648/j.ajomis.20 180301.12
Rusmarasy, B., Priyambadha, B., & Pradana, F. (2019). Pengembangan Chat Bot pada CoMa untuk Memberikan Motivasi Kepada Pengguna Menggunakan AIML. Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer, 3(5), 4484–4490.
Smith, D. (2006). Informa . on Retrieval. Utari, M. I., & Medyawati, H. (2020). Classification of News Types By Implementing Enhanced Confix Stripping Stemmer. International Journal of Engineering Technologies and Management Research, 6(5), 135–141. https://doi.org/10.29121/ijetmr.v6.i 5.2019.380
