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All Journal Insearch: Information System Research Journal Knowbase : International Journal of Knowledge in Database
Firrizqi, Alya Sahira
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Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Social Sciences Other

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Pengukuran Kualitas Alumni Mahasiswa UIN Fakultas Ushuluddin Imam Bonjol Padang : Sebuah Pendekatan Business Intelligence Firrizqi, Alya Sahira; Fitri, Mega Orina
Insearch: Information System Research Journal Vol 2, No 02 (2022): Insearch (Information System Research) Journal
Publisher : Fakultas Sains dan Teknologi UIN Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/isrj.v2i02.4510

Abstract

Kualitas alumni  menjadi tolak ukur keberhasilan penerapan pola pendidikan, cara berpikir dan pengajaran keahlian di suatu lembaga atau instansi pendidikan, terutama di perguruan tinggi. Pengukuran kualitas alumni dapat dilakukan dengan melihat Indeks Prestasi Kumulatif (IPK), jumlah cumlaude, tamat tepat waktu, dan lama masa studi, serta hasil tracer study baik kepada alumni maupun pengguna lulusan. Tujuan penelitian ini adalah untuk mengetahui kualitas alumni UIN Imam Bonjol Padang, diukur dari rata-rata IPK dan lama masa studi. Objek penelitian adalah alumni/wisudawan Fakultas Ushuluddin angkatan ke-79. Metode penelitian yang digunakan adalah metode experiment dengan menggunakan pendekatan kuantitatif. Tools yang digunakan adalah Microsoft Power Business Intelligence. Hasil penelitian menunjukkan rata – rata IPK mahasiswa alumni Fakultas Ushuluddin UIN Imam Bonjol Padang ialah 3,46 dengan persentase 25,0025% dari 72 orang mahasiswa yang tamat. Sehingga dapat disimpulkan kualitas dari Fakultas Ushuluddin UIN Imam Bonjol memiliki kualitas sedang yang mengacu pada hasil yang telah diolah pada Microsoft Power BI.
Data Mining Analysis to Predict Student Skills Using Naïve Bayes Method Lizar, Yaslinda; Firrizqi, Alya Sahira; Guci, Asriwan; Sunadi, Joko
Knowbase : International Journal of Knowledge in Database Vol. 3 No. 2 (2023): December 2023
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v3i2.7481

Abstract

The possession of specific skills by students not only has a positive impact on the students themselves but also on the Study Program within a Faculty and the University as a whole. However, Study Programs sometimes face difficulties in determining the skills of numerous students even after they have completed 7 semesters of study. Therefore, a method to extract available data in order to determine student skills quickly and accurately is essential. This research aims to apply a data mining method to predict student skills in the Information Systems Study Program at UIN Imam Bonjol Padang. The study focuses solely on predicting student skills in the fields of data processing and programming. The method employed in this data mining analysis is the Naïve Bayes method. Data will be collected from student course grades related to data processing and programming. The data will be processed using an application and subsequently tested using a Confusion Matrix. The research results indicate that predicting the determination of student skills in the Information Systems Study Program at UIN Imam Bonjol can be achieved using the Naïve Bayes algorithm, which yielded a Naïve Bayes model accuracy of 93%, precision of 81%, and recall of 81%. The obtained model can be implemented in the form of an application to determine decision-making strategies for students.
Data Mining Analysis to Predict Student Skills Using Naïve Bayes Method Lizar, Yaslinda; Firrizqi, Alya Sahira; Guci, Asriwan; Sunadi, Joko
Knowbase : International Journal of Knowledge in Database Vol. 3 No. 2 (2023): December 2023
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v3i2.7481

Abstract

The possession of specific skills by students not only has a positive impact on the students themselves but also on the Study Program within a Faculty and the University as a whole. However, Study Programs sometimes face difficulties in determining the skills of numerous students even after they have completed 7 semesters of study. Therefore, a method to extract available data in order to determine student skills quickly and accurately is essential. This research aims to apply a data mining method to predict student skills in the Information Systems Study Program at UIN Imam Bonjol Padang. The study focuses solely on predicting student skills in the fields of data processing and programming. The method employed in this data mining analysis is the Naïve Bayes method. Data will be collected from student course grades related to data processing and programming. The data will be processed using an application and subsequently tested using a Confusion Matrix. The research results indicate that predicting the determination of student skills in the Information Systems Study Program at UIN Imam Bonjol can be achieved using the Naïve Bayes algorithm, which yielded a Naïve Bayes model accuracy of 93%, precision of 81%, and recall of 81%. The obtained model can be implemented in the form of an application to determine decision-making strategies for students.
Co-Authors Fitri, Mega Orina Guci, Asriwan Lizar, Yaslinda Sunadi, Joko