Klasifikasi Dependensi Pada Kasus Uji Aplikasi Telepon Seluler Menggunakan Metode PV-DBOW Dan IFROWANN

Salsabila, Nadia Paramitha (2021) Klasifikasi Dependensi Pada Kasus Uji Aplikasi Telepon Seluler Menggunakan Metode PV-DBOW Dan IFROWANN. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

User Acceptance Testing (UAT) merupakan langkah terakhir dan wajib dilakukan untuk meminimalkan kekurangan atau kesalahan pada aplikasi telepon seluler sebelum dirilis ke user. Adapun faktor yang perlu dipertimbangkan pada langkah UAT yaitu dependensi antar kasus uji aplikasi. Dengan mengetahui
dependensi kasus uji pada suatu aplikasi, waktu dan biaya eksekusi UAT dapat dioptimalkan. Oleh karena itu, pada penelitian ini dilakukan klasifikasi dependensi kasus uji dari suatu aplikasi menggunakan metode Imbalanced Fuzzy Rough Ordered Weighted Average Nearest Neighbor (IFROWANN). Untuk menghasilkan fitur data teks kasus uji yang berguna pada proses klasifikasi, diimplementasikan metode Natural Language Processing yaitu Distributed Bag of Words Version of Paragraph Vector (PV-DBOW). Hasil dari penelitian ini berupa klasifikasi kasus uji dependen atau independen dengan accuracy, precision, recall, dan f1-score lebih dari 99%.
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User Acceptance Testing (UAT) is the last step and must be
done to minimize deficiencies or errors in the mobile phone
application before it is released to the user. The factors that need to be considered in the UAT step are dependencies between application test cases. By knowing the dependencies of test cases on an application, UAT execution time and cost can be optimized. Therefore, in this study, the test case dependency classification of an application was carried out using the Imbalanced Fuzzy Rough Ordered Weighted Average Nearest Neighbor (IFROWANN) method. To produce test case text data features that are useful in the classification process, a natural language processing method is implemented, namely the Distributed Bag of Words Version of
Paragraph Vector (PV-DBOW). The results of this study are in the form of a dependent or independent test case classification with an accuracy, precision, recall, and f1-score of more than 99%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	UAT, Klasifikasi Dependensi Kasus Uji, PV-DBOW, IFROWANN, Test Case Dependency Classification
Subjects:	Q Science > QA Mathematics > QA39.3 Fuzzy mathematics T Technology > T Technology (General) > T57.6 Operations research--Mathematics. Goal programming
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Mathematics > 44201-(S1) Undergraduate Thesis
Depositing User:	Nadia Paramitha Salsabila
Date Deposited:	31 Aug 2021 08:16
Last Modified:	31 Aug 2021 08:16
URI:	http://repository.its.ac.id/id/eprint/90942

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