Scopus Citedness

  • OCTAVIANUS, Ronaldo Cristover et al. Pengembangan Perangkat Microservices untuk Analisis Media Sosial sebagai Pendukung Pelacakan Penyebaran Tuberculosis. Jurnal Linguistik Komputasional, [S.l.], v. 5, n. 1, p. 24 - 33, apr. 2022. ISSN 2621-9336.
    1. P. L. L. Belluano, A. F. Mashar, A. W. M. Gaffar, A. R. Manga, and Purnawansyah, Support Vector Machine for Sentiment Analysis of COVID-19 Vaccine. CRC Press, 2024.
  • INDAH RAHAJENG, Mahanti; PURWARIANTI, Ayu. Indonesian Question Answering System for Factoid Questions using Face Beauty Products Knowledge Graph. Jurnal Linguistik Komputasional, [S.l.], v. 4, n. 2, p. 59 - 63, sep. 2021. ISSN 2621-9336.
    1. D. Sebastian, H. D. Purnomo, and I. Sembiring, “BERT for Natural Language Processing in Bahasa Indonesia,” in 2022 2nd International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2022, 2022, pp. 204 – 209, doi: 10.1109/ICICyTA57421.2022.10038230.
    2. M. R. Rizqullah, A. Purwarianti, and A. F. Aji, “QASiNa: Religious Domain Question Answering Using Sirah Nabawiyah,” in 2023 10th International Conference on Advanced Informatics: Concept, Theory and Application, ICAICTA 2023, 2023, doi: 10.1109/ICAICTA59291.2023.10390123.
  • MUHAMMAD, Ali; KAMARIAH, Kamariah. Pengurai Kalimat Bahasa Banjar Dengan Menggunakan Parser PC-PATR. Jurnal Linguistik Komputasional, [S.l.], v. 3, n. 1, p. 20 - 24, mar. 2020. ISSN 2621-9336.
    1. S. Yora and A. M. Barmawi, “Strengthening INORMALS Using Context-based Natural Language Generation,” J. ICT Res. Appl., vol. 16, no. 2, pp. 101 – 122, 2022, doi: 10.5614/itbj.ict.res.appl.2022.16.2.1.
  • HAIDIR, Muh Habibi; PURWARIANTI, Ayu. Short Answer Grading Using Contextual Word Embedding and Linear Regression. Jurnal Linguistik Komputasional, [S.l.], v. 3, n. 2, p. 54 - 61, sep. 2020. ISSN 2621-9336.
    1. A. A. S. Mukti, S. A. I. Alfarozi, and S. S. Kusumawardani, “Transformers Based Automated Short Answer Grading with Contrastive Learning for Indonesian Language,” in 2023 15th International Conference on Information Technology and Electrical Engineering, ICITEE 2023, 2023, pp. 133 – 138, doi: 10.1109/ICITEE59582.2023.10317785.
    2. S. Cahyawijaya et al., “NusaCrowd: Open Source Initiative for Indonesian NLP Resources,” in Proceedings of the Annual Meeting of the Association for Computational Linguistics, 2023, pp. 13745 – 13819, [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174793222&partnerID=40&md5=12ba309e7925e474062d453dfec49dd2.
    3. S. I. G. Situmeang, R. M. G. T. Sihite, H. Simanjuntak, and J. Amalia, “A Deep Learning-Based Regression Approach to Indonesian Short Answer Grading System,” in ACM International Conference Proceeding Series, 2023, pp. 201 – 209, doi: 10.1145/3626641.3626929.
    4. Z. H. Amur, Y. Kwang Hooi, H. Bhanbhro, K. Dahri, and G. M. Soomro, “Short-Text Semantic Similarity (STSS): Techniques, Challenges and Future Perspectives,” Appl. Sci., vol. 13, no. 6, 2023, doi: 10.3390/app13063911.
    5. P. Shweta and K. Adhiya, “Comparative Study of Feature Engineering for Automated Short Answer Grading,” in Proceedings - 2022 IEEE World Conference on Applied Intelligence and Computing, AIC 2022, 2022, pp. 594 – 597, doi: 10.1109/AIC55036.2022.9848851.
    6. H. R. Salim, C. De, N. D. Pratamaputra, and D. Suhartono, “Indonesian automatic short answer grading system,” Bull. Electr. Eng. Informatics, vol. 11, no. 3, pp. 1586 – 1603, 2022, doi: 10.11591/eei.v11i3.3531.
    7. M. Maslim, H.-C. Wang, C. D. Putra, and Y. D. Prabowo, “A Trustworthy Automated Short-Answer Scoring System Using a New Dataset and Hybrid Transfer Learning Method,” Int. J. Interact. Multimed. Artif. Intell., vol. 8, no. 5, pp. 37 – 45, 2024, doi: 10.9781/ijimai.2024.02.003.
    8. D. H. Alhamed, A. M. Alajmi, T. A. Alqahtani, Y. H. Alali, M. R. Alnassar, and D. A. Alabbad, “iGrade: an automated short answer grading system,” in ACM International Conference Proceeding Series, 2022, pp. 110 – 116, doi: 10.1145/3582768.3582790.
  • RAHMAN, Arief; PURWARIANTI, Ayu. Dense Word Representation Utilization in Indonesian Dependency Parsing. Jurnal Linguistik Komputasional, [S.l.], v. 3, n. 1, p. 12 - 19, mar. 2020. ISSN 2621-9336.
    1. F. Koto, A. Rahimi, J. H. Lau, and T. Baldwin, “IndoLEM and IndoBERT: A Benchmark Dataset and Pre-trained Language Model for Indonesian NLP,” in COLING 2020 - 28th International Conference on Computational Linguistics, Proceedings of the Conference, 2020, pp. 757 – 770, [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149645196&partnerID=40&md5=136d3eac74aea4a049cbe65a40bb5092.
  • RAMADHANTI, Febyana; WIBISONO, Yudi; SUKAMTO, Rosa Ariani. Analisis Morfologi untuk Menangani Out-of-Vocabulary Words pada Part-of-Speech Tagger Bahasa Indonesia Menggunakan Hidden Markov Model. Jurnal Linguistik Komputasional, [S.l.], v. 2, n. 1, p. 6 - 12, mar. 2019. ISSN 2621-9336.
    1. S. K. Nambiar, A. Leons, S. Jose, and Arunsree, “Natural Language Processing Based Part of Speech Tagger using Hidden Markov Model,” in Proceedings of the 3rd International Conference on I-SMAC IoT in Social, Mobile, Analytics and Cloud, I-SMAC 2019, 2019, pp. 782 – 785, doi: 10.1109/I-SMAC47947.2019.9032593.
    2. W. Gata, S. Surohman, and H. M. Nawawi, “Twitter in analysis of policy sentiments of the omnibus law work creative design,” in AIP Conference Proceedings, 2023, vol. 2714, doi: 10.1063/5.0128546.
  • NAF'AN, Muhammad Zidny; BURHANUDDIN, Auliya; RIYANI, Ade. Penerapan Cosine Similarity dan Pembobotan TF-IDF untuk Mendeteksi Kemiripan Dokumen. Jurnal Linguistik Komputasional, [S.l.], v. 2, n. 1, p. 23 - 27, mar. 2019. ISSN 2621-9336.
    1. Sintia, S. Defit, and G. W. Nurcahyo, “PRODUCT CODEFICATION ACCURACY WITH COSINE SIMILARITY AND WEIGHTED TERM FREQUENCY AND INVERSE DOCUMENT FREQUENCY (TF-IDF),” J. Appl. Eng. Technol. Sci., vol. 2, no. 2, pp. 14 – 21, 2021, doi: 10.37385/jaets.v2i2.210.
    2. N. Royani, C. Edi Widodo, and B. Warsito, “Sentiment Analysis on Movie Streaming Services on Twitter Using LDA and SVM Methods,” in E3S Web of Conferences, 2023, vol. 448, doi: 10.1051/e3sconf/202344802032.
    3. A. Irsyad and N. A. Rakhmawati, “Community detection in twitter based on tweets similarities in indonesian using cosine similarity and louvain algorithms,” Regist. J. Ilm. Teknol. Sist. Inf., vol. 6, no. 1, pp. 22 – 31, 2020, doi: 10.26594/register.v6i1.1595.
  • AFIF, Irfan; PURWARIANTI, Ayu. Employing Dependency Tree in Machine Learning Based Indonesian Factoid Question Answering System. Jurnal Linguistik Komputasional, [S.l.], v. 2, n. 1, p. 28 - 33, mar. 2019. ISSN 2621-9336.
    1. Sintia, S. Defit, and G. W. Nurcahyo, “PRODUCT CODEFICATION ACCURACY WITH COSINE SIMILARITY AND WEIGHTED TERM FREQUENCY AND INVERSE DOCUMENT FREQUENCY (TF-IDF),” J. Appl. Eng. Technol. Sci., vol. 2, no. 2, pp. 14 – 21, 2021, doi: 10.37385/jaets.v2i2.210.
  • HIDAYATULLAH, Ahmad Fathan et al. Identifikasi Konten Kasar Pada Tweet Bahasa Indonesia. Jurnal Linguistik Komputasional, [S.l.], v. 2, n. 1, p. 1 - 5, mar. 2019. ISSN 2621-9336.
    1. E. D. S. Mulyani, N. N. F. SM, A. Darmawan, R. A. Wiyono, R. D. Saputra, and D. Rohpandi, “Keyword-Based Hadith Grouping Using Fuzzy C-Means Method,” in 2020 2nd International Conference on Cybernetics and Intelligent System (ICORIS), 2020, pp. 1–6.
    2. I. Ayuningtias, I. Jaya, and M. Iqbal, “Identification of yellowfin tuna (Thunnus albacares), mackerel tuna (Euthynnus affinis), and skipjack tuna (Katsuwonus pelamis) using deep learning,” in IOP Conference Series: Earth and Environmental Science, 2021, vol. 944, no. 1, doi: 10.1088/1755-1315/944/1/012009.
    3. A. M. Shiddiqi, D. H. Fudholi, and A. Zahra, “A Social Media Analytics on How People Feel about Their Cancelled Homecoming during Covid-19 Pandemic,” in Proceedings - 4th International Conference on Vocational Education and Electrical Engineering: Strengthening Engagement with Communities through Artificial Intelligence Application in Education, Electrical Engineering and Information Technology, ICVEE 2021, 2021, doi: 10.1109/ICVEE54186.2021.9649721.
  • ASPARILLA, Muhammad Gerdy; SUJAINI, Herry; NYOTO, Rudy Dwi. Perbaikan Kualitas Korpus Untuk Meningkatkan Kualitas Mesin Penerjemah Statistik (Studi Kasus : Bahasa Indonesia Jawa Krama). Jurnal Linguistik Komputasional, [S.l.], v. 1, n. 2, p. 66 - 74, sep. 2018. ISSN 2621-9336.
    1. H. Sujaini, “Improving the role of language model in statistical machine translation (Indonesian-Javanese),” Int. J. Electr. Comput. Eng., vol. 10, no. 2, pp. 2102 – 2109, 2020, doi: 10.11591/ijece.v10i2.pp2102-2109.
  • PUTRA, Fatra Nonggala; EFFENDI, Ari; ARIFIN, Agus Zainal. Pembobotan Kata berdasarkan Kluster untuk Peringkasan Otomatis Multi Dokumen. Jurnal Linguistik Komputasional, [S.l.], v. 1, n. 1, p. 17-22, mar. 2018. ISSN 2621-9336.
    1. D. Soyusiawaty and D. H. R. Wolley, “Hybrid Spelling Correction and Query Expansion for Relevance Document Searching,” Int. J. Adv. Comput. Sci. Appl., vol. 12, no. 8, pp. 332 – 339, 2021, doi: 10.14569/IJACSA.2021.0120838.
    2. F. N. Putra and C. Fatichah, “Klasifikasi jenis kejadian menggunakan kombinasi neuroner dan recurrent convolutional neural network pada data twitter,” Regist. J. Ilm. Teknol. Sist. Inf., vol. 4, no. 2, pp. 81 – 90, 2018, doi: 10.26594/register.v4i2.1242.
    3. E. Tanuwijaya, S. Adam, M. F. Anggris, and A. Z. Arifin, “Query expansion menggunakan word embedding dan pseudo relevance feedback,” Regist. J. Ilm. Teknol. Sist. Inf., vol. 5, no. 1, pp. 47 – 54, 2019, doi: 10.26594/register.v5i1.1385.
  • MANDASARI, Miranti Indar; FIRMANTO, Angga Dwi; FATHURRAHMAN, Fadjar. Kalibrasi Rasio kemungkinan pada Sistem Rekognisi Pengucap Otomatis untuk Aplikasi Forensik di Indonesia. Jurnal Linguistik Komputasional, [S.l.], v. 2, n. 2, p. 39 - 46, sep. 2019. ISSN 2621-9336.
    1. R. J. Rouf and D. Arifianto, “Speaker forensic identification using joint factor analysis and i-vector,” in Journal of Physics: Conference Series, 2021, vol. 1896, no. 1, doi: 10.1088/1742-6596/1896/1/012026.