Widodo, Iswahyudi (2021) Analisis Kesesuaian Indeks Kepuasan Mahasiswa Dengan Nilai Mata Kuliah Menggunakan Pendekatan Korelasi Signifikansi Dan Backpropagation. Magister thesis, Universitas Brawijaya.
Abstract
Implementasi pengukuran kepuasan pelanggan adalah pengukuran kepuasan pelayanan dosen terhadap mahasiswa hingga dosen yang dilakukan UIN Maulana Malik Ibrahim Malang pada masa pandemi dengan menggunakan IKM Aplikasi online. Kompetensi yang diukur adalah kompetensi pedagogik, kompetensi profesional, kompetensi kepribadian, dan kompetensi kompetensi sosial. Pengukuran korelasi signifikansi terhadap hasil IKM Online dibandingkan dengan nilai siswa sebagai output pembelajaran dilakukan untuk mengetahui hubungan antara kedua variabel tersebut. Koefisien determinasi juga ditambahkan pengukuran untuk mengetahui kekuatan pengaruh suatu variabel terhadap variabel lainnya. Hasilnya menunjukkan bahwa korelasi antara 2 variabel kuat dan variabel nilai mata pelajaran berpengaruh sebesar 55,9504% terhadap variabel hasil IKM. Data proses klasifikasi menggunakan algoritma backpropagation digunakan untuk memperkuat hubungan antara kedua variabel. Hasil adalah model 2-5-1 dengan RMSE 0,728 sebagai model terbaik dan kelas data kuat menjadi kelas pertama. Dari studi ini, diperlukan pengukuran untuk mengetahui faktor-faktor lain yang mempengaruhi penilaian kepuasan mahasiswa terhadap dosen dan evaluasi terhadap instrumen survei.
English Abstract
Kata Kunci: survei kepuasan, IKM online, korelasi, signifikansi, koefien determinasi, The implementation of the measurement of customer satisfaction is the measurement of service satisfaction of lecturers to students to lecturers carried out by the State Islamic University (UIN) Maulana Malik Ibrahim Malang during the pandemic using the IKM Online application. The competencies measured are pedagogic competence, professional competence, personality competence, and social competence. The results of the measurement evaluation indicate the need to evaluate the instrument and process of measuring service satisfaction of lecturers to students. One of the variables that can be measured is the IKM result variable compared to the value of the course as learning output. In this study, measurements of the Pearson's method correlation, coefficient of determination and significance were carried out on the IKM result variables and course grades. Calculations using PHP and MySql applications. This application is also used to perform preprocessing by normalizing the data in the classification process. The classification process uses an artificial neural network Backpropagation algorithm. This method is used to determine the existing data classes. Data processing utilizes the RapidMiner application. The results show that the correlation between the two strong variables based on Pearson's formula is 0.748, the coefficient of determination is 0.559504 and the significance is 271.4732. The data classification process using the backpropagation algorithm is used to strengthen the relationship between the two variables. The result is the 2-5-1 model with RMSE 0.728 with a training time of 77s being the best model and the strong data class being the first class. From this study, measurements are needed to determine other factors that affect the assessment of student satisfaction to lecturers and evaluation of survey instruments. Keywords: satisfaction survey, IKM online, correlation, significance, coefficient of determination, backpropagation..
Other obstract
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| Item Type: | Thesis (Magister) |
|---|---|
| Identification Number: | 621.381 |
| Uncontrolled Keywords: | Kata Kunci: survei kepuasan, IKM online, korelasi, signifikansi, koefien determinasi, backpropagation.--satisfaction survey, IKM online, correlation, significance, coefficient of determination, backpropagation.. |
| Divisions: | S2/S3 > Magister Teknik Elektro, Fakultas Teknik |
| Depositing User: | Unnamed user with username saputro |
| Date Deposited: | 20 Oct 2021 11:51 |
| Last Modified: | 17 Oct 2024 06:37 |
| URI: | http://repository.ub.ac.id/id/eprint/184398 |
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