Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Compiler
Subawa, Made Dai
Unknown Affiliation
Computer Science & IT Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Software Defects Predictions using SQL Complexity and Naïve Bayes Subali, Made Agus Putra; Sugiartha, I Gusti Rai Agung; Adnyana, I Made Budi; Putra, I Putu Aditya; Subawa, Made Dai
Compiler Vol 14, No 1 (2025): May
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/compiler.v14i1.2979

Abstract

Software defects result in unreliable software, therefore predicting software defects is an effort to produce quality software. In this study, we used the naïve bayes method because it has the appropriate characteristics of the data used. The data used include NASA MDP datasets and datasets from the calculation of the sql complexity method on eight software modules. The use of two datasets was carried out because in the NASA MDP datasets there were no attributes that paid attention to the use of sql commands, therefore in the datasets from the eight software modules the sql complexity attribute was included which paid attention to the level of complexity of the use of sql commands in each module. The prediction results of this study were evaluated by considering the values of accuracy, precision, recall, and f-measure. Based on these results, the accuracy results of CM1 were 88%, PC2 was 97%, and KC3 was 78%.
Pemberian Bobot Kriteria dan Penambahan Fitur pada Metode SQL Complexity dalam Mengukur Kompleksitas Perangkat Lunak Subali, Made Agus Putra; Sugiartha, I Gusti Rai Agung; Putra, I Putu Aditya; Subawa, Made Dai
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 13 No 2: April 2026
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.132

Abstract

Mengukur kompleksitas perangkat lunak secara adaptif sangat penting untuk dilakukan, karena dapat membantu project manager mengetahui usaha yang diperlukan dalam membangun perangkat lunak yang berkualitas. Pada penelitian terdahulu kompleksitas perangkat lunak diukur dengan memperhatikan penggunaan kriteria file model, view, dan controller, namun ketiga kriteria tersebut memiliki prioritas yang sama dalam proses, selain itu pada metode SQL Complexity belum dapat mengenali perintah transact SQL. Pada penelitian ini diusulkan metode untuk mengukur kompleksitas perangkat lunak yang lebih adaptif dengan tahapan proses, sebagai berikut: (1) pemberian bobot kriteria pada setiap file model, view, dan controller modul perangkat lunak, (2) perhitungan kompleksitas perintah SQL menggunakan metode SQL Complexity dengan penambahan fitur baru, antara lain function, store procedure, trigger, dan view, (3) pengukuran tingkat kemiripan antar modul perangkat lunak menggunakan metode Cosine Similarity. Pada penelitian ini menggunakan dua jenis data, meliputi: (1) data perhitungan metode SLOC, CC, dan SQL Complexity dari delapan modul perangkat lunak dan (2) data berbagai jenis perintah SQL. Berdasarkan hasil yang telah diperoleh metode yang diusulkan mampu beradaptasi dalam menentukan prioritas penggunaan ketiga kriteria modul perangkat lunak maupun fitur baru pada metode SQL Complexity dengan akurasi yang diperoleh sebesar 87.5% dalam mengukur kesesuaian kompleksitas modul perangkat lunak.   Abstract Adaptively measuring software complexity is very important, because it can help project managers know the effort required in building quality software. In previous studies, software complexity was measured by considering the use of model, view, and controller file criteria, but these three criteria have the same priority in the process. In addition, the SQL Complexity method cannot yet recognize transact SQL commands. In this research, it is proposed a method to measure software complexity with the following process steps: (1) assigning criteria weights to each model, view, and controller file of the software module, (2) calculating the complexity of SQL commands using the SQL Complexity method with the addition of new features, including functions, store procedures, triggers, and views, (3) measuring the level of similarity between software modules using the Cosine Similarity method. This study uses two types of data, including: (1) calculation data using the SLOC, CC, and SQL Complexity methods from eight software modules and (2) data on various types of SQL commands. Based on the results obtained, the proposed method can adapt in prioritizing the use of the three software module criteria and new features in the SQL Complexity method with an accuracy of 87.5% in measuring the suitability of software module complexity.
Co-Authors I Gusti Rai Agung Sugiartha I Made Budi Adnyana, I Made Budi Putra, I Putu Aditya Subali, Made Agus Putra