User Opinion Polarization on IPDN Jatinangor
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B. P. Statistik, “Statistik Telekomunikasi Indonesia 2022,” pp. 7823–7830, 2023.
J. I. Robbins and C. L. Tieso, “What is Conflict?,” Engag. with Hist. Classr., no. October 2013, pp. 27–32, 2021, doi: 10.4324/9781003234906-2.
A. C. Eberendu, “Unstructured Data: an overview of the data of Big Data,” Int. J. Comput. Trends Technol., vol. 38, no. 1, pp. 46–50, 2016, doi: 10.14445/22312803/ijctt-v38p109.
C. Blockeel, P. Drakopoulos, N. P. Polyzos, H. Tournaye, and J. A. García-Velasco, “Review the ‘peer review,’” Reprod. Biomed. Online, vol. 35, no. 6, pp. 747–749, 2017, doi: 10.1016/j.rbmo.2017.08.017.
W. J. Reynolds, “Compliance,” Saf. Heal. Stage, pp. 66–108, Jan. 2020, doi: 10.4324/9781351136983-4.
Nurnajihah Rosli & Syafiqah Md Nayan, “Why Customer First?,” J. Undergrad. Soc. Sci. Technol., vol. 2, no. 2, pp. 505–524, 2020.
A. Agarwal, V. Sharma, G. Sikka, and R. Dhir, “Opinion mining of news headlines using SentiWordNet,” 2016 Symp. Colossal Data Anal. Networking, CDAN 2016, 2016, doi: 10.1109/CDAN.2016.7570949.
T. Wilson, J. Wiebe, and P. Hoffmann, “Recognizing contextual polarity: An exploration of features for phrase-level sentiment analysis,” Comput. Linguist., vol. 35, no. 3, pp. 399–433, 2009, doi: 10.1162/coli.08-012-R1-06-90.
N. A. M. Razali et al., Opinion mining for national security: techniques, domain applications, challenges and research opportunities, vol. 8, no. 1. Springer International Publishing, 2021. doi: 10.1186/s40537-021-00536-5.
P. Assiroj, A. Kurnia, and S. Alam, “The performance of Naïve Bayes, support vector machine, and logistic regression on Indonesia immigration sentiment analysis,” Bull. Electr. Eng. Informatics, vol. 12, no. 6, pp. 3843–3852, 2023, doi: 10.11591/eei.v12i6.5688.
B. Batrinca and P. C. Treleaven, “Social media analytics: a survey of techniques, tools and platforms,” AI Soc., vol. 30, no. 1, pp. 89–116, 2015, doi: 10.1007/s00146-014-0549-4.
A. Go, R. Bhayani, and L. Huang, “Twitter Sentiment Classification using Distant Supervision,” Processing, vol., pp. 1–6, 2009.
F. Romadoni, Y. Umaidah, and B. N. Sari, “Text Mining Untuk Analisis Sentimen Pelanggan Terhadap Layanan Uang Elektronik Menggunakan Algoritma Support Vector Machine,” J. Sisfokom (Sistem Inf. dan Komputer), vol. 9, no. 2, pp. 247–253, Jul. 2020, doi: 10.32736/sisfokom.v9i2.903.
R. Akbani and N. Japkowicz, “Applying support vector machines to imbalanced datasets,” Lect. Notes Artif. Intell. (Subseries Lect. Notes Comput. Sci., vol. 3201, no. September, pp. 39–50, 2004, doi: 10.1007/978-3-540-30115-8_7.
V. Singh and S. K. Dubey, “Opinion mining and analysis: A literature review,” Proc. 5th Int. Conf. Conflu. 2014 Next Gener. Inf. Technol. Summit, pp. 232–239, 2014, doi: 10.1109/CONFLUENCE.2014.6949318.
L. Zhang and B. Liu, Sentiment Analysis and Opinion Mining, vol. 3, no. 1959. 2017. doi: 10.1007/978-1-4899-7687-1.
N. Gupta and R. Agrawal, Application and techniques of opinion mining. INC, 2020. doi: 10.1016/B978-0-12-818699-2.00001-9.
IPDN, “Institut Pemerintahan Dalam Negeri,” 2024. https://www.ipdn.ac.id/lokasi_ipdn (accessed Jan. 31, 2024).
C. M. Chew, “Pandemics in the age of Twitter: Content analysis of tweets during the 2009 H1N1 outbreak,” PLoS One, vol. 5, no. 11, 2010, doi: 10.1371/journal.pone.0014118.
R. Moraes, J. F. Valiati, and W. P. Gavião Neto, “Document-level sentiment classification: An empirical comparison between SVM and ANN,” Expert Syst. Appl., vol. 40, no. 2, pp. 621–633, Feb. 2013, doi: 10.1016/j.eswa.2012.07.059.
P. S. Reddy, D. R. Sri, C. S. Reddy, and S. Shaik, “Sentimental Analysis using Logistic Regression,” no. July, 2021, doi: 10.9790/9622-1107023640.
M. Wankhade, A. Chandra, S. Rao, S. Dara, and B. Kaushik, “A Sentiment Analysis of Food Review using Logistic Regression,” vol. 2, no. 7, pp. 251–260, 2017.
M. M. Altawaier and S. Tiun, “Comparison of machine learning approaches on Arabic twitter sentiment analysis,” Int. J. Adv. Sci. Eng. Inf. Technol., vol. 6, no. 6, pp. 1067–1073, 2016, doi: 10.18517/ijaseit.6.6.1456.
C. Troussas, M. Virvou, K. J. Espinosa, K. Llaguno, and J. Caro, “Sentiment analysis of Facebook statuses using Naive Bayes Classifier for language learning,” IISA 2013 - 4th Int. Conf. Information, Intell. Syst. Appl., pp. 198–205, 2013, doi: 10.1109/IISA.2013.6623713.
D. A. Muthia, “Sentiment Analysis of Hotel Review Using Naïve Bayes Algorithm and Integration of Information Gain and Genetic Algorithm As Feature Selection Methods,” Int. Semin. Sci. Issues Trends, pp. 25–30, 2014.
Martiti and C. Juliane, “Implementation of Naive Bayes Algorithm on Sentiment Analysis Application,” Proc. 2nd Int. Semin. Sci. Appl. Technol. (ISSAT 2021), vol. 207, pp. 193–200, 2021, doi: 10.2991/aer.k.211106.030.
M. Ahmad and S. Aftab, “Analyzing the Performance of SVM for Polarity Detection with Different Datasets,” Int. J. Mod. Educ. Comput. Sci., vol. 9, no. 10, pp. 29–36, 2017, doi: 10.5815/ijmecs.2017.10.04.
D. Gunawan and A. Amalia, “The Design of Lexical Database for Indonesian Language,” J. Phys. Conf. Ser., vol. 755, no. 1, 2017, doi: 10.1088/1742-6596/755/1/011001.
N. A. Salsabila, Y. A. Winatmoko, A. A. Septiandri, and A. Jamal, “Colloquial Indonesian Lexicon Nikmatun,” 2018 Int. Conf. Asian Lang. Process., pp. 226–229, 2018.
Gunawan and A. Saputra, “Building synsets for Indonesian WordNet with monolingual lexical resources,” Proc. - 2010 Int. Conf. Asian Lang. Process. IALP 2010, pp. 297–300, 2010, doi: 10.1109/IALP.2010.69.
F. Bond, L. T. Lim, E. K. Tang, and H. Riza, “The Combined Wordnet Bahasa,” NUSA Linguist. Stud. Lang. around Indones., vol. 57, no. December, pp. 83–100, 2014.
O. University, “The Oxford Handbook of Corpus Phonology,” Oxford Handb. Corpus Phonol., Aug. 2014, doi: 10.1093/OXFORDHB/9780199571932.001.0001.
J. Dunn, Natural Language Processing for Corpus Linguistics. Cambridge University Press, 2022. doi: 10.1017/9781009070447.
F. Koto, “InSet: Indonesia Sentiment Lexicon,” 2023. https://github.com/fajri91/InSet (accessed Feb. 01, 2024).
F. Koto and G. Y. Rahmaningtyas, “Inset lexicon: Evaluation of a word list for Indonesian sentiment analysis in microblogs,” Proc. 2017 Int. Conf. Asian Lang. Process. IALP 2017, vol. 2018-Janua, no. December, pp. 391–394, 2017, doi: 10.1109/IALP.2017.8300625.
Y. Azhar, “METODE LEXICON-LEARNING BASED UNTUK IDENTIFIKASI TWEET OPINI BERBAHASA INDONESIA,” 2017.
DOI: http://dx.doi.org/10.52155/ijpsat.v43.2.6108
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