DECISION SUPPORT SYSTEM APPLICA TION ON TREES RESOURCE SHARING MODEL IN AGROFORESTRY SYSTEMS

<p>Agroforestry is one of multidiscipline that combines between agriculture, forestry and animal husbandry. Mixed trees scenario is one of problems found in agroforestry system. Where each type of tree has. different competition degree to others. The correct scenario can produce the maximum ag...

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Bibliographic Details
Main Author: , Sri Mulyana. Abd. Bari
Format: Article
Published: [Yogyakarta] : Fak. Teknologi Informasi Universitas Teknologi Yo 2006
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Summary:<p>Agroforestry is one of multidiscipline that combines between agriculture, forestry and animal husbandry. Mixed trees scenario is one of problems found in agroforestry system. Where each type of tree has. different competition degree to others. The correct scenario can produce the maximum agroforestry model in utilizing and , exploiting the resources. So that. the result (trees or annual crops) }Vould be optimum and continuity. Therefore, required the understanding of characteristic of each type of tree that could befound in resource sharing model. DSS is one of CBIS that supports determining of mixed trees scenario. Interaction between trees could produce a competition that shown in competition index (maximum and optimum competition index). Mathematic model of tree's diameter and competition index could be performed by using RegressLonAnalysis. Based on this model, competition index at certain diameter calculated and clustered into five category of quality (worse, bad, good, better and best). The scenario built based on these clusters and criteria decided by user. Withtreesdata collectedin Nglanggeran,Patuk, Gunung Kidul, DIY province, and default criteria (Exponential Regression, 10 cm of tree diameter, and 5. cm of optimum competition index interval) produced five mixed trees scenarios based on default category of quality as follows : acacia-teak (worse, 50%-60%), acaciasonokeling -mahogany-sonokeling (bad, 60%-70%), no data with good (70%80%) category, teak-mahogany (better, 80%-90%), and no data with best (90%-100%) category.</p>