Penggunaan Metode NAÏVE BAYES Dalam Mengukur Tingkat Kepuasan Pengguna Terhadap Online System Universitas Advent Indonesia
Keywords:
Data Mining, Naïve Bayes, Classification, Measuring User Satisfaction Levels.Abstract
Achieving user satisfaction in using an information system is one of the factors to determine the system as expected. The UNAI Online System has been operating since 2008 and granting students a convenient access to their academic data. In order to enhance users' satisfaction on using the UNAI Online System, it needs to be done according to the right measurements towards an information system. The methods that were used in this study is data mining along with the Naïve Bayes classifications method and data that were obtained from questionnaires. The attributes used are content quality, relevance, privacy, easily operated, speed, visual appeal, online completeness, and customer services. The test results showed that the first test for users' satisfaction using the Naïve Bayes method scored up to 81.3%. The second test with 80% data training and 20% data testing obtained 80% accuracy value. As for cross-validation test, the score reached 78.7%. Lastly, the test with 66% training data and 33% test data get the accuracy value up to 68.6%.
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B. Claudya, “Analisis Pengaruh Persepsi Manfaat dan Persepsi Kemudahan Terhadap Sikap Pengguna Sistem Online UNAI,” Teknik Informatika, Universitas Advent Indonesia, 2018.
Puspitasari, An Nissaa. 2013. Pengaruh Kualitas Website Terhadap Nilai yang dipersepsikan, Kepuasan dan Loyalitas Pelanggan Pada Online Shop. Jurnal Ilmu Administrasi.
A.K.H. Audio, “Klasifikasi Penyakit Hipertensi Menggunakan Algoritma C4.5 Studi Kasus RSU Provinsi NTB ,” Teknik Informatika, Universitas Sanata Dharma, 2017.
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