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

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Analisis Bibliometrik Terhadap Penelitian Business Process Reengineering dan Manajemen Menggunakan Vosviewer Sunadi, Joko; Malnovizam, Defa
Insearch: Information System Research Journal Vol 3, No 02 (2023): 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.v3i02.6832

Abstract

Penelitian ini membahas tentang Analisis Bibliometrik Terhadap Penelitian Business Process Reengineering Dan Manajemen Pada Google Scholar Menggunakan VOSViewer. Penelitian ini bertujuan untuk untuk mengetahui jumlah publikasi jurnal ilmiah pada interval waktu 2013 – 2023. Peneliti yang paling aktif dalam riset tentang Business Process Reengineering dan Manajemen serta pemetaan riset tentang Business Process Reengineering dan Manajemen. Metode penelitian pada penelitian ini adalah Tinjauan Pustaka menggunakan pendekatan bibliometric. Data yang digunakan pada penelitian adalah publikasi ilmiah yang terindeks google scholar berjumlah 257 publikasi dengan kata kunci pencarian "Business Process Reengineering" dan "Manajemen". Hasil penelitian ini menunjukkan dari tahun 2013 hingga 2023 mengalami peningkatan yang fluktuatif. Puncak jumlah terbanyak publikasi terjadi pada tahun 2022 sebanyak 52 artikel sedangkan publikasi terendah pada tahun 2019 sebanyak 7 artikel. Terdapat 5 peneliti yang aktif dalam pempublikasi jurnal ilmiah tentang Business Process Reengineering dan Manajemen adalah Wildan Suharso, Sugeng Santoso, Ilyas Nuryasin, Farrikh Al Zami dan Dian Nuswantoro. Dimana Wildan Suharso dan Ilyas Nuryasin memiliki korelasi yang erat. Densitas penelitian yang masih rendah memberikan peluang bagi peneliti lain untuk menciptakan novelty pada penelitian ini melalui publikasi online
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 Firrizqi, Alya Sahira Guci, Asriwan Lizar, Yaslinda Malnovizam, Defa