CROMOSOM: CROWDSOURCED SOFTWARE ENGINEERING APPLICATION USING TASK RECOMMENDATION COMPONENT BASED ON SOCIAL MEDIA

• Main Author: Ramadhan Putra, Kurnia
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/39736
• Institution: Institut Teknologi Bandung

The concept of crowdsourcing can be utilized in the field of software engineering known as Crowdsourced Software Engineering (CSE). CSE is used to complete tasks related to software, such as component design, programming, testing, and bug fixing. Currently, the problem with CSE applications is the process to find the relevant task is time-consuming and difficult to find workers who have trustworthiness to work on task. The recommendation component can be integrated into the CSE applications which is believed to be able to overcome these problems. Some research on the integration of recommendation component in CSE applications is only to overcome task recommendations and does not consider worker trustworthiness who will work on the task. Whereas in this study, the integration of recommendation component in addition to helping recommend task to worker also perform ranking of workers based on the trustworthiness of the worker. The approach used is a combination of content-based to handle task matching and individual-based to handle social profile computation process in generating trustworthiness workers. From the results of the analysis, is obtained several techniques that can be used to perform the task matching process, namely Programming Language Similarity, String Distance, and SWE Taxonomy, but the task matching approach which is implemented is String Distance. Implementation is done by developing the CSE application known as Cromosom, which is integrated with the recommendation component to help recommend tasks to workers and perform ranking of workers based on the trustworthiness of the worker. From the results of testing the functionality performed, the Cromosom application can help workers find tasks that are more relevant based on their expertise, and help requester in choosing workers who have trustworthiness to work on the task.