Published: 2021-06-30
Analisis Sentimen Mahasiswa terhadap Kuesioner Penilaian Pelayanan Sekretariat FTKI Universitas Nasional dengan menggunakan Metode Simple Multi Attribute Rating Technique (SMART) dan Simple Additive Weighting (SAW)
DOI: 10.35870/jtik.v5i2.205
Abstract
In the world of higher education, service to students is very much needed, it is very important to maintain the quality of service so that good and disciplined service to students can be realized. This sentiment analysis aims to determine student opinion made using a questionnaire form. In addition, the Decision Support System with the Simple Multi Attribute Rating Technique (SMART) and Simple Additive Weighting (SAW) methods is expected to be a solution in providing an assessment of the FTKI secretariat services. This study uses a questionnaire form to see student assessments and make it an alternative value. The final results are obtained by testing the order analysis technique, which is 82%, proving that by testing these two methods, service assessment can be more expanded.
Keywords
Sentiment Analysis; Questionnaire; SAW; Desicion Support System; SMART
Article Information
This article has been peer-reviewed and published in the Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi). The content is available under the terms of the Creative Commons Attribution 4.0 International License.
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Issue: Vol. 5 No. 2 (2021)
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Section: Computer & Communication Science
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Published: 2021-06-30
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License: CC BY 4.0
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Copyright: © 2021 Authors
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DOI: 10.35870/jtik.v5i2.205
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No author biographies available.
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Hermanto, H., Mustopa, A. and Kuntoro, A.Y., 2020. Algoritma Klasifikasi Naive Bayes Dan Support Vector Machine Dalam Layanan Komplain Mahasiswa. JITK (Jurnal Ilmu Pengetahuan Dan Teknologi Komputer), 5(2), pp.211-220.
-
Muzakki, M.F., Jondri, J. and Umbara, R.F., 2019. Analisis Sentimen Mahasiswa Terhadap Fasilitas Universitas Telkom Menggunakan Metode Jaringan Saraf Tiruan Dan Tf-idf. eProceedings of Engineering, 6(2).
-
Salam, N.S.N., Supianto, A.A. and Perdanakusuma, A.R., 2019. Analisis Sentimen Opini Mahasiswa Terhadap Saran Kuesioner Penilaian Kinerja Dosen dengan Menggunakan TF-IDF dan K-Nearest Neighbor. Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer e-ISSN, 2548, p.964X.
-
Suprianto, S., 2019. Perbandingan Metode Naïve Bayes Classifier Dan Holistic Lexicon Based Dalam Analisis Sentimen Angket Mahasiswa. JSI: Jurnal Sistem Informasi (E-Journal), 11(2).
-
Christina, S., 2019. Sarcasm in Sentiment Analysis of Indonesian Text: A Literature Review. Jurnal Teknologi Informasi, 13(2), pp.54-59.
-
Supiyandi, S., Siahaan, A.P.U. and Alfiandi, A., 2020. Sistem Pendukung Keputusan Pemilihan Pegawai Honorer Kelurahan Babura dengan Metode MFEP. Jurnal Media Informatika Budidarma, 4(3), pp.567-573.
-
Rajamuddin., 2018. Sistem Pendukung Keputusan Penilaian Kinerja Untuk Memilih Dosen Berprestasi Menggunakan Metode AHP, Progress, vol. 7, no. 2, hal. 71–78.
-
M. Megawaty dan M. Ulfa., 2020. Decision Support System Methods, J. Inf. Syst. Informatics, vol. 2, no. 1, hal. 192–201, 2020.
-
S. R. Astari, U. Rusydi, dan Sunardi., 2020. Perbandingan Metode Profile Matching Dengan Metode SMART Untuk Seleksi Asisten Laboratorium, J. Rekayasa Sist. dan Teknol. Inf., vol. 4, no. 10, hal. 311–318.
-
L. P. Wanti et al.., 2020. A support system for accepting student assistance using analytical hierarchy process and simple additive weighting, J. Phys. Conf. Ser., vol. 1430, no. 1.
-
Bendra Wardana, Roni Habibi, dan M. Harry K Saputra., 2020. Comparation of SAW Method and Topsis in Assesing The Best Area Using HSE Standards, Emit. Int. J. Eng. Technol., vol. 8, no. 1, hal. 126–139.
-
Karman, J. and Saputra, J., 2018. Perancangan Sistem Pakar Diagnosa Kerusakan Sepeda Motor Honda Bebek Berkarburator Dengan Menggunakan Metode Teorema Bayes Berbasis Web Mobile. JUTIM (Jurnal Teknik Informatika Musirawas), 3(1), pp.58-64.
-
Amalia, V. and Yanto, R., 2020. Komparasi Metode Saw Dan Smart Penerima Kartu Indonesia Pintar (KIP). Jurnal Teknologi Informasi Mura, 12(01), pp.90-98.
-
Aziz, T.F.A., Sulistiyono, S., Harsiti, H., Setyawan, A., Suhendar, A. and Munandar, T.A., 2020, April. Group decision support system for employee performance evaluation using combined simple additive weighting and Borda. In IOP Conference Series: Materials Science and Engineering (Vol. 830, No. 3, p. 032014). IOP Publishing.
-
Cahya Adi Saputra., “Analisis Sentimen Opini Mahasiswa Terhadap Saran Kuesioner Penilaian Pelayanan Akademik di Universitas Alma Atadengan Menggunakan TF-IDF dan K-Nearest Neighbor.pdf.
-
Sunandar, S., 2020. TA: Analisis Sentimen pada Angket Mahasiswa Universitas Dinamika Menggunakan Algoritma Naive Bayes (Doctoral dissertation, Universitas Dinamika).
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