ASPECT BASED SENTIMENT ANALYSIS DATA KUESIONER DI RUMAH SAKIT MUHAMMADIYAH LAMONGAN MENGGUNAKAN ALGORITMA K-NN.
DOI:
https://doi.org/10.30736/jti.v6i2.677Abstract
Kesulitan untuk mengorganisir data kuesioner yang bersifat konvensional melatarbelakangi penelitian ini. Oleh karena itu dibuat sistem yang memudahkan pengelompokan data kuesioner secara otomatis yang lengkap dengan sentimen yang terkandung didalamnya. Dataset yang digunakan dalam penelitian ini adalah data kuesioner rumah sakit Muhammadiyah lamongan. Penelitian ini hanya menangani kuesioner yang berbentuk teks. Data dengan fisik kertas direkap kemudian diinput ke database lengkap dengan kategori unit kerja dan sentiment. Selanjutnya dataset tersebut di dilakukan pre-prosesing yang meliputi penanganan negasi case folding, tokenizing, filtering dan stemming. Sebagai data uji komentar dari kuesioner akan dilakukan pre-prosesing selanjutnya dihitung tingkat kemiripan document dengan menggunakan metode K- Nearest Neighbor dan Vector Space Model. Jumlah data yang ditangani mempengaruhi performa system terutama dari akurasi dan kecepatan pada saat proses klasifikasi. Hasil dari sistem yang dibuat berupa ranking dokumen yang paling mirip dengan dataset berdasarkan urutan nilai cosine similarity. Ujicoba klasifikasi berdasarkan kelas kategori menghasilkan nilai akurasi 91 %. Ujicoba berdasarkan Kelas Sentimen sebesar 94 %.dari kombinasi keduanya system berhasil mendapat akurasi sebesar 86 %Downloads
References
Admin.2017.“Algoritma K-Nearest Neighbor (K-NN)†informatikalogi.com.https://informatikalogi.com/algoritma-k-nn-k-nearest-neighbor) dia akses 03 Juli 2017.
Ilyantanto.2011. Stemming Bahasa Indonesia dengan Algoritma Nazief dan Andrianiâ€.28-juni2011. (https://liyantanto.wordpress.com/2011/06/28/stemming-bahasa-indonesia-dengan-algoritma-nazief-dan-andriani). Diakses 03 juli 2017.
Li Baoli, Yu Shiwen, and Lu Qin, An Improved k-Nearest Neighbor Algorithm for Text Categorization, Department of Computer Science and Technology
Peking University, Beijing, P.R. China, 100871, 2003.
Lu Qin, An Improved k-Nearest Neighbor Algorithm for Text Categorization, Department of Computer Science and Technology. Peking University, Beijing, P.R. China, 100871, 2003.
Mohammad Rezwanul Huq, Ahmad Ali, Anika Rahman. 2017. "Sentiment Analysis on Twitter Data using KNN and SVM". Vol. 8, No. 6, 2017. (IJACSA) International Journal of Advanced Computer Science and Applications.Dhaka, Bangladesh.
Mesariya.P, Madia.N, Kumar.A. 2016. “Document Ranking using Customizes Vector Method – A Reviewâ€, International Journal of Computer Science and Mobile Computing (IJCSMC). pg. 287-290, Vol.5 Issue.3
Taeho Jo. 2017. "Using K Nearest Neighbors for Text Segmentation with Feature Similarity". Department of Computer and Information Communication Engineering . Hongik University.
Downloads
Published
How to Cite
Issue
Section
License
Joutica : Journal of Informatic Unisla is licensed under an Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license. You are free to:
- Share copy and redistribute the material in any medium or format
- Adapt remix, transform, and build upon the material for any purpose, even commercially. This license is acceptable for Free Cultural Works.
The licensor cannot revoke these freedoms as long as you follow the license terms.
- Attribution You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- Share Alike If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
- No additional restrictions You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Copyright
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under an Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
Joutica : Journal of Informatic Unisla by Universitas Islam Lamongan is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Based on a work at https://jurnalteknik.unisla.ac.id/index.php/elektronika/index