Predicting amount of fertilizer substances for gardening by using Rule Based Technique / Farah Dalila Rodzuan

This project is developed to predict the amount of fertilizer substances for gardening by implementing Rule Based Technique. Rimbun Ventures Nursery is chosen as stakeholder for this project, which is located at Taman Pulai Flora, Johor Bahru, Johor where it’s near to Pulai Spring Resort and Technol...

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Main Author: Rodzuan, Farah Dalila
Format: Thesis
Language:English
Published: 2017
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/18759/
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author Rodzuan, Farah Dalila
author_facet Rodzuan, Farah Dalila
author_sort Rodzuan, Farah Dalila
building UiTM Institutional Repository
collection Online Access
description This project is developed to predict the amount of fertilizer substances for gardening by implementing Rule Based Technique. Rimbun Ventures Nursery is chosen as stakeholder for this project, which is located at Taman Pulai Flora, Johor Bahru, Johor where it’s near to Pulai Spring Resort and Technology Park University Technology Malaysia (UTM). There are few users of this system which are the owner of the nursery itself, the gardener and the other users in related area of knowledge. Currently, there is very few system that predict the amount of fertilizer substances to be used, this lead to several problems such as flower plant stunted growth because of lacking nutrient, misuse type of fertilizer and fertilizer amount used over or understated. In order to minimize this problem, the objectives had been identified for conducting and monitoring this research. This prediction system helps the nursery by providing the suggestion on the fertilizer amount needs for flower plant, according to the uncertainty attributes such as the age of flower plant, temperature (Celcius), water requirement and soil pH value. The Rule Based technique was chosen to analyze and produce the rules from the data that have been gathered from the expert knowledge. Beforehand, the data have to undergo data pre-processing phase in order to clean, transform, reduce and smooth the raw data. Based on the data that have been pre-processed, the uncertainty attributes were divided into several categories to ease the rules produced such age of flower plant that has been categorized into threes according to its height, which are small, medium and large. From the rules, the system can suggest a few suggested percentages of the fertilizer amount needed for flower plants. The rules embedded into the prototype system to demonstrate on how the rules functioning. Therefore, the type of fertilizer to be used also being suggested according to soil pH values. In order to control the entire process involved, a waterfall methodology has been chosen. Even though this project have been completed, there is a lot of enhancement that can be done to improve such as within the scope of this research on covering the other type of plants such as herb, fruit and vegetables. Furthermore, this prototype system platform also can be changed into mobile applications for more easy and quick uses as well as can address the need of the testing phase. In conclusion, this research proved to be beneficial not only for the stakeholder but also for the other users.
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format Thesis
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institution Universiti Teknologi MARA
institution_category Local University
language English
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publishDate 2017
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spelling uitm-187592018-01-25T03:29:06Z https://ir.uitm.edu.my/id/eprint/18759/ Predicting amount of fertilizer substances for gardening by using Rule Based Technique / Farah Dalila Rodzuan Rodzuan, Farah Dalila Soil conservation and protection This project is developed to predict the amount of fertilizer substances for gardening by implementing Rule Based Technique. Rimbun Ventures Nursery is chosen as stakeholder for this project, which is located at Taman Pulai Flora, Johor Bahru, Johor where it’s near to Pulai Spring Resort and Technology Park University Technology Malaysia (UTM). There are few users of this system which are the owner of the nursery itself, the gardener and the other users in related area of knowledge. Currently, there is very few system that predict the amount of fertilizer substances to be used, this lead to several problems such as flower plant stunted growth because of lacking nutrient, misuse type of fertilizer and fertilizer amount used over or understated. In order to minimize this problem, the objectives had been identified for conducting and monitoring this research. This prediction system helps the nursery by providing the suggestion on the fertilizer amount needs for flower plant, according to the uncertainty attributes such as the age of flower plant, temperature (Celcius), water requirement and soil pH value. The Rule Based technique was chosen to analyze and produce the rules from the data that have been gathered from the expert knowledge. Beforehand, the data have to undergo data pre-processing phase in order to clean, transform, reduce and smooth the raw data. Based on the data that have been pre-processed, the uncertainty attributes were divided into several categories to ease the rules produced such age of flower plant that has been categorized into threes according to its height, which are small, medium and large. From the rules, the system can suggest a few suggested percentages of the fertilizer amount needed for flower plants. The rules embedded into the prototype system to demonstrate on how the rules functioning. Therefore, the type of fertilizer to be used also being suggested according to soil pH values. In order to control the entire process involved, a waterfall methodology has been chosen. Even though this project have been completed, there is a lot of enhancement that can be done to improve such as within the scope of this research on covering the other type of plants such as herb, fruit and vegetables. Furthermore, this prototype system platform also can be changed into mobile applications for more easy and quick uses as well as can address the need of the testing phase. In conclusion, this research proved to be beneficial not only for the stakeholder but also for the other users. 2017 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/18759/1/TD_FARAH%20DALILA%20RODZUAN%20CS%2017_5.pdf Rodzuan, Farah Dalila (2017) Predicting amount of fertilizer substances for gardening by using Rule Based Technique / Farah Dalila Rodzuan. (2017) Degree thesis, thesis, Universiti Teknologi MARA. <http://terminalib.uitm.edu.my/18759.pdf>
spellingShingle Soil conservation and protection
Rodzuan, Farah Dalila
Predicting amount of fertilizer substances for gardening by using Rule Based Technique / Farah Dalila Rodzuan
title Predicting amount of fertilizer substances for gardening by using Rule Based Technique / Farah Dalila Rodzuan
title_full Predicting amount of fertilizer substances for gardening by using Rule Based Technique / Farah Dalila Rodzuan
title_fullStr Predicting amount of fertilizer substances for gardening by using Rule Based Technique / Farah Dalila Rodzuan
title_full_unstemmed Predicting amount of fertilizer substances for gardening by using Rule Based Technique / Farah Dalila Rodzuan
title_short Predicting amount of fertilizer substances for gardening by using Rule Based Technique / Farah Dalila Rodzuan
title_sort predicting amount of fertilizer substances for gardening by using rule based technique / farah dalila rodzuan
topic Soil conservation and protection
url https://ir.uitm.edu.my/id/eprint/18759/