Optimizing Agricultural Data Management: A Collaborative Approach through Extreme Programming in Software Development - Sihombing, Denny Jean Cross (Jurnal Info Sains : Informatika dan Sains, 2024)
This research explores the profound transformation of the agricultural sector through the application of advanced technologies, pursuing efficiency and sustainability. The first phase, Data Collection, focuses on identifying data needs for farm management through field surveys and the integration of agricultural sensors. Technologies such as mobile apps and the Internet of Things (IoT) help to efficiently collect high-quality data on soil, weather, and other agricultural factors. The second phase, Application Development, introduces technology integration with Extreme Programming (XP) methods, resulting in adaptive and efficient applications. XP's collaborative and responsive process ensures the successful implementation of the app through thorough functional tests before the official launch. The final phase, User Acceptance Analysis, evaluates user acceptance variables with the Technology Acceptance Model (TAM), highlighting perceived usefulness as a critical factor in users' intention to adopt the application. Implications of the findings include suggestions for app updates focusing on optimizing the user interface to improve perceived usefulness. In discussion, this research blends aspects of technology and farm management, providing an in-depth look at the potential for continuous innovation in improving agricultural productivity. Overall, this research reflects valuable contributions regarding current technological solutions to optimize farm management in the modern era, paving the way for continuous improvements in efficiency and responsiveness to changes in the agricultural cycle