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All Journal Sistemasi: Jurnal Sistem Informasi Jurnal Pilar Nusa Mandiri Jurnal Teknik Informatika UNIKA Santo Thomas INTI Nusa Mandiri Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Insan Journal of Innovative and Creativity
Ginabila, Ginabila
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Journal : Jurnal Pilar Nusa Mandiri

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KOMPARASI ALGORITMA DENGAN PENDEKATAN RANDOM UNDERSAMPLING UNTUK MENANGANI KETIDAKSEIMBANGAN KELAS PADA PREDIKSI CACAT SOFTWARE Ginabila, Ginabila; Fauzi, Ahamd
Jurnal Pilar Nusa Mandiri Vol 15 No 1 (2019): Pilar Nusa Mandiri : Journal of Computing and Information System Periode Maret 2
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1063.258 KB) | DOI: 10.33480/pilar.v15i1.28

Abstract

Testing is a process that becomes a standard in producing quality software. In predictions of software defects, prediction errors are very bad. Incorrect and inappropriate data sets result in inaccurate prediction results will be affect the software itself. This study aims to overcome the problem of class imbalance with the software defect prediction data set, through the Random Undersampling (RUS) data level approach by taking several algorithms namely Naive Bayes (NB), J48 and Random Forest (RF) which aims to compare the accuracy level highest so that maximum results are obtained in the process of predicting software defects. From the results of this study it can be found that to overcome class imbalances using the Random Undersampling level data approach to predict software defects, the highest level of accuracy is obtained by the Random Forest algorithm with an accuracy rate of 71.932%.
INFORMATION RETRIEVAL SYSTEM PADA FILE PENCARIAN DOKUMEN TESIS BERBASIS TEXT MENGGUNAKAN METODE VECTOR SPACE MODEL Fauzi, Ahmad; Ginabila, Ginabila
Jurnal Pilar Nusa Mandiri Vol 15 No 1 (2019): Pilar Nusa Mandiri : Journal of Computing and Information System Periode Maret 2
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (938.599 KB) | DOI: 10.33480/pilar.v15i1.61

Abstract

Speed and density in the process of finding documents and information has become mandatory, contained in information systems, to facilitate the search process or find documents and information needed, it is called information retrieval or information retrieval system, implementation of the theory applied in this study using the model method vector space, the purpose of this study is to provide general exposure to the process of finding digital documents. With the token and indexing process so that the results of the masses are found in the database using keywords, so the system will search according to the keywords input into the system, and will be compared with the data contained in the database, so that it can produce the correct information.
Co-Authors Angga Kusuma, Angga Dany, Rahmad Dharmawan, Rayhan Eko Yulianto Fauzi Ahmad Muda Fauzi, Ahamd Fitrohan, Hafidinulloh Indra Chaidir, Indra Isroni, Isroni Muhammad Iqbal Pratiwi, Risca Lusiana Siti Fauziah Sriyadi Sriyadi, Sriyadi Zulia Imami Alfianti