Regression testing as an essential activity in software development that has changed requirements. In practice, regression testing requires a lot of time so that an optimal strategy is needed. One approach that can be used to speed up execution time is the Regression Test Selection (RTS) approach. Currently, practitioners and academics have started to think about developing tools to optimize the process of implementing regression testing. Among them, STARTS and Ekstazi are the most popular regression testing tools among academics in running test case selection algorithms. This article discusses the comparison of the capabilities of the STARTS and Ekstazi features by using feature parameter evaluation. Both tools were tested with the same input data in the form of System Under Test (SUT) and test cases. The parameters used in the tool comparisons are platform technology, test case selection, functionality, usability and performance efficiency, the advantages, and disadvantages of the tool. he results of the trial show the differences and similarities between the features of STARTS and Ekstazi, so that it can be used by practitioners to take advantage of tools in the implementation of regression testing that suit their needs. In addition, experimental results show that the use of Ekstazi is more precise in sorting out important test cases and is more efficient, when compared to STARTS and regression testing with retest all.
The implementation of distance learning in Informatics Engineering has many problems, one of which is the lack of student engagement during learning. The purpose of this study is to improve student engagement by using a feature called Lesson in Quizizz. Lecture teaches on video teleconference and instructs students on Lesson in Quizizz to interact and give feedback about the lesson. The survey method is the research method used for this study. At the end of the semester, students are given a questionnaire regarding increasing interest in learning with conventional methods and the Lesson Quizizz added. The results showed that the student engagement using the Lesson Quizizz features increased by 4.5% compared to conventional learning. Indicators of student engagement have a high increase along with the improvement of student concentration. Thus, Quizizz can encourage students who usually are not active in class
Electronic Supply Chain Management (E-SCM) can be implemented by collaborating several electronic concepts for business process such as E-Transportation, E-Distribution, E-Fulfilment, Enterprise Resource Planning (ERP) and Warehouse Management System (WMS). These concepts require high technology, expensive implementation, high skill and cost in development. Garment and textile are the most numerous industries in Indonesia, especially in West Java, E-SCM can increased efficiency and effectively for textile or garment companies, but E-SCM development requires high costs and high technology. These are problems when many garment and textile companies in Indonesia have limited capabilities of technology. In this research we design new E-SCM model with Value Chain Analysis approach and used Software Architectural Design to make the model. We divided E-SCM system for garment and textile industry in multiple layers and then we collaborate with two existing E-SCM frameworks, namely E-Supply Chain Management Process and Technology Integration Framework and E-SCM Multi-Agent System Framework. We combine layers components with the relevant layers of the existing E-SCM frameworks. The result is a new E-SCM model for garment and textile industry that can accommodate limitations of technological capabilities.
Penelitian ini mengambil studi kasus penjadwalan pengalokasian task kepada resource pada proyek pendokumentasian alur program di sebuah perusahaan. Alokasi task yang dilakukan pada pembuatan jadwal adalah perhitungan alokasi line of code harus sesuai dengan target line of code yang harus diselesaikan. Permasalahan yang terjadi pada saat pembuatan jadwal adalah perhitungan jumlah line of code dari script program pada penentuan task kadang kala kala tidak sesuai dengan target line of code. Perhitungan yang tidak tepat ini berdampak pada saat pengerjaan dan estimasi total waktu pengerjaan. Oleh karena itu diusulkan pembuatan jadwal dengan menggunakan algoritma genetika. Pendekatan yang dilakukan dengan cara membandingkan apakah pembuatan jadwal dengan algoritma genetika dapat memberikan hasil yang lebih baik dibandingkan dengan proses manual. Algoritma genetika adalah teknik pencarian dan optimasi yang terinspirasi dari prinsip genetika dan seleksi alam yang biasa digunakan untuk memecahkan suatu pencarian nilai pada masalah optimasi. Hasil uji coba penelitian menunjukkan bahwa pembuatan jadwal dengan algoritma genetika ternyata mampu meminimalisir perhitungan jumlah line of code yang tidak sesuai dengan target dibandingkan dengan perhitungan manual. Hal ini ditunjukkan dengan adanya penurunan jumlah line of code yang tidak sesuai dengan target yaitu sebesar 699 baris atau sebesar 15,9 % dari total. Kontribusi dalam penelitian memberikan kesimpulan bahwa pembuatan jadwal dengan algoritma genetika memberikan hasil yang lebih baik dibandingkan jadwal yang dibuat manual meskipun hasilnya tidak cukup signifikan.
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