Predicting the Amount of Pineapple Production in Sumatra Using the Fletcher-Reeves Algorithm

Authors

  • Hose Fernando Tampubolon STIKOM Tunas Bangsa
  • Solikhun Solikhun AMIK & STIKOM Tunas Bangsa Pematangsiantar

DOI:

https://doi.org/10.35335/computational.v11i2.2

Keywords:

ANN, Fletcher-Reeves, Gradient, Pineapple Fruit Production, Prediction

Abstract

Pineapple is a kind of organic product from the Bromeliaceae family which has the logical name Ananas comosus Merr. Pineapple plants have weathered skin and pointed leaves on top. The taste of new pineapple is a combination of sweet and slightly sharp. Pineapple is high in L-ascorbic acid, which helps cells fight damage, according to the Linus Pauling Organization at Oregon State College. L-ascorbic acid is also useful in managing medical conditions, such as heart disease and joint pain. However, due to the absence of consideration from the regions and local governments regarding pineapple on the island of Sumatra, it has caused several problems, especially data on pineapples related to the advantages, content, and uniqueness of pineapples to be used as pineapples. chaotic and diminishing pineapple production, especially on the island of Sumatra. Therefore, it is important to make a wish to know the assessed amount of Pineapple Organic Product Crop Creation on the island of Sumatra so that the public authorities on the island of Sumatra have endlessly clear references to decide on an approach or make major progress so
that the development of pineapple on the island of Sumatra does not diminish. The method used in making predictions is the FletcherReeves algorithm and is a method in ANN. In this study, the data used was the number of pineapple fruit plants on the island of Sumatra in 2012-2021 obtained from BPS. Given this information, organizational design models will not be fully defined, including 4-10-1, 4-15-1, 4-20-1, 4-25-1 and 4-30-1. Of these 5 models, then Training and Testing is done and the best architectural model result is 4-15-1 with the least (less) Performance/MSE test. With the lowest Performance/MSE level of 0.005488189 compared to the other 4 models.

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Published

2022-08-28

How to Cite

Tampubolon, H. F., & Solikhun, S. (2022). Predicting the Amount of Pineapple Production in Sumatra Using the Fletcher-Reeves Algorithm. International Journal of Mechanical Computational and Manufacturing Research, 11(2), 60–68. https://doi.org/10.35335/computational.v11i2.2

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