Multi-Platform Decision Support System for High Value Crops using a Posteriori Algorithm
RemieBie Donato Andres1, Maria Visitacion N. Gumabay2, Jesus B. Pizarro3
1RemieBie Donato Andres, Isabela State University, Angadanan Campus, Isabela Philippines.
2Maria Visitacion N. Gumabay, St. Paul University, Philippines Cagayan Philippines.
3Jesus B. Pizarro, St. Paul University, Philippines Cagayan Philippines.
Manuscript received on 07 March 2019 | Revised Manuscript received on 20 March 2019 | Manuscript published on 30 March 2019 | PP: 1128-1135 | Volume-8 Issue-5, March 2019 | Retrieval Number: E3366038519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Information systems, particularly of decision support systems are becoming increasingly important in the agriculture sector. Access to vital, timely information can help stakeholders involved in agriculture and agribusiness such as farmers, traders, government personnel make better decisions about crop production and trade. This study aimed to develop a web-based integrated information system within a mobile application on digital marketing as an enabler to enhance better access of information for buyers and farmers. It specifically it aimed to identify the challenges encountered by agency participants within the existing system with regard to accessing relevant information on HVCs, to identify the system to be developed to address the identified challenges, to determine the extent of compliance of the developed system with the ISO 25010:2011 Software Quality Assurance Standard, and to determine whether or not there is a significant difference between the assessment of the users and IT experts with regard to compliance with the aforementioned ISO standard. The Research and Development (R&D) and the V-Model methodologies were selected by this researcher as study and software development methodologies respectively. These participants were chosen on the basis of their involvement in the growing and marketing of high value crops in the province. Questionnaires were the main instrument for gathering data from the participants. Standard statistical methods such as frequency counts and percentage, weighted mean, hypothesis means, and analysis of variance were used as tools in analyzing and interpreting the data gathered. Level of significance was set at.05. For data visualization and knowledge extraction, the educational edition of the RapidMiner application was utilized to summarize the knowledge generated by the system that can be used to support decision-making. The results show that the developed system conformed with industrycompliant software quality standards and thus satisfactorily met all of the requirements of its users. It was concluded that the developed system is a suitable replacement for the existing system and its deployment recommended.
Keyword: High Value Crops, ISO 25010, Isabela, Web-Based, Mobile Application, Decision Support System, Information Systems.
Scope of the Article: System Integration