Klasifikasi Helpdesk Menggunakan Metode K-Nearest Neighbor dan TF-ABS
Abstract
Keywords
Full Text:
PDFReferences
M. ALTINTA? and A. C. TANTU?, “Machine learning based software development,” vol. 21, no. 3, pp. 33–44, 2014.
T. A. Herawan, Y. H. Chrisnanto, and A. I. Hadiana, “Klasifikasi Helpdesk Universitas Jenderal Achmad Yani Menggunakan Concept Frequency-Inverse Document Frequency (CF-IDF) dan K-Nearest Neighbor,” Pros. SNST, vol. 7, pp. 108–113, 2016.
C. F. Suharno, M. A. Fauzi, and R. S. Perdana, “Klasifikasi Teks Bahasa Indonesia Pada Dokumen Pengaduan Sambat Online Menggunakan Metode K-Nearest Neighbors Dan Chi-square,” Syst. Inf. Syst. Informatics J., vol. 3, no. 1, pp. 25–32, 2017, doi: 10.29080/systemic.v3i1.191.
M. R. A. Nasution and M. Hayaty, “Perbandingan Akurasi dan Waktu Proses Algoritma K-NN dan SVM dalam Analisis Sentimen Twitter,” J. Inform., vol. 6, no. 2, pp. 226–235, 2019, doi: 10.31311/ji.v6i2.5129.
M. A. Kurniawan, Y. Sibaroni, and K. L. Muslim, “Kategorisasi Berita Menggunakan Metode Pembobotan TF.ABS dan TF.CHI,” Indones. J. Comput., vol. 3, no. 2, p. 83, 2018, doi: 10.21108/indojc.2018.3.2.236.
V. C. Gandhi and J. A. Prajapati, “Review on Comparison between Text Classification Algorithms,” Int. J. Emerg. Trends Technol. Comput. Sci., vol. 1, no. 3, pp. 1–4, 2012.
A. H. Aliwy and E. H. A. Ameer, “Comparative study of five text classification algorithms with their improvements,” Int. J. Appl. Eng. Res., vol. 12, no. 14, pp. 4309–4319, 2017, doi: 10.113/J.0973-4562.
M. A. Rosid, A. S. Fitrani, I. Ratna, and I. Astutik, “Improving Text Preprocessing For Student Complaint Document Classification Using Sastrawi,” 2020, doi: 10.1088/1757-899X/874/1/012017.
L. A. Matsunaga and N. F. F. Ebecken, “Two Novel Weighting for Text Categorization,” in Data Mining IX - Data Mining, Protection, Detection and other Security Technologies, IX., A. Zanasi, D. Almorza Gomar, N. F. . Ebecken, and C. . Brebbia, Eds. Rio de Janeiro, Brazil: WITPRESS, 2008, pp. 105–114.
J. Li et al., “Feature selection: A data perspective,” ACM Comput. Surv., vol. 50, no. 6, 2017, doi: 10.1145/3136625.
P. Bafna, D. Pramod, and A. Vaidya, “Document clustering: TF-IDF approach,” Int. Conf. Electr. Electron. Optim. Tech. ICEEOT 2016, no. March 2016, pp. 61–66, 2016, doi: 10.1109/ICEEOT.2016.7754750.
J. Han, M. Kamber, and J. Pei, Data Mining Concepts and Techniques - third edition. 2012.
D. Yuliana and C. Supriyanto, “Klasifikasi Teks Pengaduan Masyarakat Dengan Menggunakan Algoritma Neural Network,” UPI YPTK J. KomTekInfo, vol. 5, no. 3, pp. 92–116, 2019.
L. A. Andika, P. A. N. Azizah, and R. Respatiwulan, “Analisis Sentimen Masyarakat terhadap Hasil Quick Count Pemilihan Presiden Indonesia 2019 pada Media Sosial Twitter Menggunakan Metode Naive Bayes Classifier,” Indones. J. Appl. Stat., vol. 2, no. 1, p. 34, 2019, doi: 10.13057/ijas.v2i1.29998.
DOI: https://doi.org/10.33633/tc.v20i4.5094
Article Metrics
Abstract view : 388 timesPDF - 339 times
Refbacks
- There are currently no refbacks.
Diterbitkan Oleh :
Jurnal Techno.Com terindex di :
Jurnal Teknologi Informasi Techno.Com (p-ISSN : 1412-2693, e-ISSN : 2356-2579) diterbitkan oleh LPPM Universitas Dian Nuswantoro Semarang. Jurnal ini di bawah lisensi Creative Commons Attribution 4.0 International License.