Permodelan Topik pada Layanan Akademik Perguruan Tinggi dengan Menggunakan N-Gram
DOI:
https://doi.org/10.32627/internal.v7i2.1192Keywords:
Ekstraksi Topik, Layanan Akademik, N-Gram, Praproses, Term FrequencyAbstract
Automation of generating information in academic services are expected to provide convenience in providing academic services to students. Relevant topics can be extracted from social media by calculating the frequency of words asked by social media users. The research focuses on generating question topics on academic services at universities. Topic extraction are obtained through data taken from Instagram social media, so that relevant topics are obtained to get information that is most frequently asked by the public. The N-Gram and Term Frequency are approach to extract the topic. The initial stages in this study include conducting Web Scraping taken from Instagram social media. In this study, text preprocessing was carried out in several stages, namely cleansing, casefolding, stopwords removal and tokenizing, and stemming. The N-Gram approach is carried out by comparing three types, namely unigrams, bigrams and trigrams. The results obtained in this study prove that the bigram produces relevant word pairs in determining academic service topics on social media. This approach produces word pairs that are relevant to academic service topics including graduation list, paying UKT, independent admission, SPANPTKIN and independent test.
References
M. Jamil, S. F. Saputra, M. I. Wahid, and D. Riana, “Evaluasi Metode ISO/IEC 9126 Pada Kinerja Website Sistem Informasi Akademik Perguruan Tinggi,” Inform. Mulawarman J. Ilm. Ilmu Komput., vol. 16, no. 1, Art. no. 1, Mar. 2021, doi: 10.30872/jim.v16i1.5209.
Afnibar and D. F. N, “Pemanfaatan Whatsapp Sebagai Media Komunikasi Antara Dosen dan Mahasiswa dalam Menunjang Kegiatan Belajar (Studi Terhadap Mahasiswa UIN Imam Bonjol Padang),” AL MUNIR J. Komun. Dan Penyiaran Islam, vol. 0, no. 0, pp. 70–83, Jun. 2020, doi: 10.15548/AMJ-KPI.V0I0.1501.
W. C. Indhiarta, “Penggunaan N-Gram pada Analisa Sentimen Pemilihan Kepala Daerah Jakarta Menggunakan Algoritma Naïve Bayes.”
N. L. Lavenia and R. Permatasari, “Sentiment Analysis on Twitter Social Media Regarding Depression Disorder Using the Naive Bayes Method,” CoreID J., vol. 1, no. 2, pp. 66–74, Jul. 2023, doi: 10.60005/COREID.V1I2.14.
A. Apriani, H. Zakiyudin, and K. Marzuki, “Penerapan Algoritma Cosine Similarity dan Pembobotan TF-IDF System Penerimaan Mahasiswa Baru pada Kampus Swasta,” J. Bumigora Inf. Technol. BITe, vol. 3, no. 1, pp. 19–27, Jul. 2021, doi: 10.30812/BITE.V3I1.1110.
S. A. Sugianto, Liliana, and S. Rostianingsih, “Pembuatan Aplikasi Predictive Text Menggunakan Metode N-Gram-Based,” J. Infra, vol. 1, no. 2, p. 125-p.130, Jul. 2013.
E. L. Amalia, A. J. Jumadi, I. A. Mashudi, and W. Wibowo, “Analisis Metode Cosine Similarity Pada Aplikasi Ujian Online Otomatis (Studi Kasus JTI POLINEMA),” J. Teknol. Inf. Dan Ilmu Komput., vol. 8, no. 2, pp. 343–348, Mar. 2021, doi: 10.25126/JTIIK.2021824356.
“Algoritma Multinomial Naïve Bayes Untuk Klasifikasi Sentimen Pemerintah Terhadap Penanganan Covid-19 Menggunakan Data Twitter | Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi).” Accessed: Nov. 28, 2024. [Online]. Available: https://jurnal.iaii.or.id/index.php/RESTI/article/view/3146
M. F. Juna and M. Hayaty, “The observed preprocessing strategies for doing automatic text summarizing,” Comput. Sci. Inf. Technol., vol. 4, no. 2, pp. 119–126, Jul. 2023, doi: 10.11591/CSIT.V4I2.P119-126.
M. K. K. Insan, U. Hayati, and O. Nurdiawan, “Analisis Sentimen Aplikasi Brimo pada Ulasan Pengguna di Google Play Menggunakan Algoritma Naive Bayes ANALISIS SENTIMEN APLIKASI BRIMO PADA ULASAN,” JATI J. Mhs. Tek. Inform., vol. 7, no. 1, pp. 478–483, Mar. 2023, doi: 10.36040/JATI.V7I1.6373.
Y. Zhang and Z. Rao, “N-BiLSTM: BiLSTM with n-gram Features for Text Classification,” Proc. 2020 IEEE 5th Inf. Technol. Mechatron. Eng. Conf. ITOEC 2020, pp. 1056–1059, Jun. 2020, doi: 10.1109/ITOEC49072.2020.9141692.
C. Supriadi, H. D. Purnomo, I. Sembiring, and J. O. N. B. Sidorejo, “Sensitivitas Sistem Pencarian Artikel Bahasa Indonesia Menggunakan Metode n-gram Dan Tanimoto Cosine,” J. Transform., vol. 18, no. 1, pp. 63–70, Jul. 2020, doi: 10.26623/TRANSFORMATIKA.V18I1.2184.
S. Azizurahman, Y. Firdaus, and A. A. Suryani, “Analisis Dan Implementasi Metode N-Gram Pada Information Retrieval,” Tugas Akhir Fak. Tek. Inform. Univ. Telkom, 2011.
E. K. Susanto, M. B. Subkhi, A. Z. Arifin, M. Maryamah, R. W. Sholikah, and R. Indraswari, “Metode Pembobotan Hibrida untuk Ekstraksi Frasa Kunci Bahasa Arab,” INSYST J. Intell. Syst. Comput., vol. 4, no. 2, pp. 93–101, Oct. 2022, doi: 10.52985/INSYST.V4I2.255.
M. Irfan, Jumadi, W. B. Zulfikar, and Erik, “Implementation of Fuzzy C-Means algorithm and TF-IDF on English journal summary,” in 2017 Second International Conference on Informatics and Computing (ICIC), Nov. 2017, pp. 1–5. doi: 10.1109/IAC.2017.8280646.
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