ANALISIS EFEKTIVITAS DOSEN MENGAJAR DI UNIVERSITAS MERCU BUANA MENGGUNAKAN ALGORITMA NAIVE BAYES (STUDI KASUS: FAKULTAS ILMU KOMPUTER JURUSAN SISTEM INFORMASI UNIVERSITAS MERCU BUANA)

SANJANI, MUHAMAD ALFI REZA (2024) ANALISIS EFEKTIVITAS DOSEN MENGAJAR DI UNIVERSITAS MERCU BUANA MENGGUNAKAN ALGORITMA NAIVE BAYES (STUDI KASUS: FAKULTAS ILMU KOMPUTER JURUSAN SISTEM INFORMASI UNIVERSITAS MERCU BUANA). S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

This research aims to analyze the effectiveness of teaching by lecturers at Mercu Buana University using the Naive Bayes Machine Learning algorithm. Data was collected through questionnaires filled out by students attending classes in the Department of Information Systems at Mercu Buana University during the even semester of the academic year 2021/2022. The Naive Bayes analysis method was used to classify the effectiveness of teaching by lecturers as good or bad based on student assessments. The research results indicate that the Naive Bayes algorithm can be used to predict student satisfaction levels with an accuracy of 90%. This study is expected to contribute to the development of knowledge, particularly in the field of analyzing the effectiveness of teaching by lecturers using the Naive Bayes algorithm. Furthermore, the research is expected to provide direct benefits to Mercu Buana University and related stakeholders in improving the quality of teaching by lecturers. Keywords: naïve bayes algorithm, classification, machine learning, student assessment Penelitian ini bertujuan untuk menganalisis efektivitas pengajaran dosen di Universitas Mercu Buana menggunakan algoritma Machine Learning Naive Bayes. Data dikumpulkan melalui kuesioner yang diisi oleh mahasiswa yang mengikuti kuliah di Jurusan Sistem Informasi Universitas Mercu Buana pada semester genap tahun akademik 2021/2022. Metode analisis Naive Bayes digunakan untuk mengklasifikasikan efektivitas pengajaran dosen menjadi baik atau buruk berdasarkan penilaian mahasiswa. Hasil penelitian menunjukkan bahwa algoritma Naive Bayes dapat digunakan untuk memprediksi tingkat kepuasan mahasiswa dengan akurasi 90%. Penelitian ini diharapkan dapat memberikan kontribusi pada pengembangan ilmu pengetahuan, khususnya pada bidang analisis efektivitas pengajaran dosen menggunakan algoritma Naive Bayes. Selain itu, penelitian ini diharapkan dapat memberikan manfaat langsung bagi Universitas Mercu Buana dan stakeholder terkait dalam meningkatkan kualitas pengajaran dosen. Kata kunci: algoritma naïve bayes, klasifikasi, machine learning, penilaian mahasiswa

Item Type:	Thesis (S1)
Call Number CD:	FIK/SI. 24 004
Call Number:	SIK/18/24/002
NIM/NIDN Creators:	41820010124
Uncontrolled Keywords:	algoritma naïve bayes, klasifikasi, machine learning, penilaian mahasiswa
Subjects:	000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika 100 Philosophy and Psychology/Filsafat dan Psikologi > 150 Psychology/Psikologi > 154 Subconscious and Altered States and Process/Psikologi Bawah Sadar > 154.6 Sleep Phenomena/Fenomena Tidur > 154.63 Dreams/Mimpi > 154.634 Analysis/Analisis 500 Natural Science and Mathematics/Ilmu-ilmu Alam dan Matematika > 510 Mathematics/Matematika > 518 Numerical Analysis/Analisis Numerik, Analisa Numerik > 518.1 Algorithms/Algoritma
Divisions:	Fakultas Ilmu Komputer > Sistem Informasi
Depositing User:	khalimah
Date Deposited:	13 Jan 2024 04:49
Last Modified:	13 Jan 2024 06:38
URI:	http://repository.mercubuana.ac.id/id/eprint/85298

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