Main Crops and Goat Production Decision Support System Using Climatic Parameter Predictors
Myelinda A. Baldelovar1, Maria Visitacion Gumabay2, Jesus Pizarro3
1Myelinda A. Baldelovar, Surigao Del Sur State University Tagbina Campus, Surigao Del Sur, Philippines, Southeast Asia.
2Dr. Maria Visitacion Gumabay, Saint Paul University Philippines, Cagayan, Philippines, Southeast Asia.
3Dr. Jesus Pizarro, Saint Paul University Philippinea, Philippiness, Southeast Asia.
Manuscript received on 05 April 2019 | Revised Manuscript received on 14 April 2019 | Manuscript Published on 24 May 2019 | PP: 7-11 | Volume-8 Issue-6S3 April 2019 | Retrieval Number: F10020486S319/19©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: This study aims to develop a decision support system to predict the production of rice, corn, and goat of CARAGA region. Multiple linear regression analysis was used in deriving models that were used to calculate the predicted production. The derived models were used in the system development. Interviews and observations were conducted to the rice, corn and goat farmer participants to determine their best practices in rice, corn and goat production. Interviews were also conducted to the Department of Agriculture technical staff to determine their issues and problems encountered in using the existing system. The responses of the participants are presented thematically. Using a survey evaluation questionnaire, IT professionals evaluated the developed system to determine the extent of compliance based on ISO 25010 software quality assurance standards. Agile methodology particularly SCRUM method was employed in managing the task during system development. The results on the evaluation of the system developed on its extent of compliance based on ISO 25010 software quality assurance standards revealed that IT professionals accepted it unconditionally. IT professionals enumerated suggestions to further enhance the features and performance of the system. Among the suggestions were remarks on output, label of buttons, error message and acronym of the system.
Keywords: Multiple Linear Regression Analysis was used in Deriving Models that were used to Calculate the Predicted Production. The Derived Models were used in the System Development.
Scope of the Article: Communication