DATA CLUSTERING DESIGN AND FISH FARMING POND AUTOMATION CASE STUDY: POND SALMON CENTER ITERA.
Clustering and automation design use the K-means and FCM methods as well as the fuzzy logic method to build an automation system that can be used and implemented in real terms in salmon center ITERA ponds. The Clustering carried out in this study can be used as input from an automation system and...
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| Format: | Theses |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/71882 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Clustering and automation design use the K-means and FCM methods as well as
the fuzzy logic method to build an automation system that can be used and
implemented in real terms in salmon center ITERA ponds. The Clustering carried
out in this study can be used as input from an automation system and as a grouping
of data on a pond whose results will be applied for various purposes for analysis of
pond conditions to optimize pond handling so that pond conditions become optimal.
Happen By using K-means and FCM clustering, maximum results are obtained in
grouping data, the data obtained in K-means and FCM complement each other.
Using SVM in clustering is expected to reduce the error rate in clustering. The
gamma value in the SVM regulation is 0.7, or it can be said to be close to zero, so
it allows for even more classification errors to occur so that the hyperparameter can
be increased so that the results obtained are even better. While the automation
system uses fuzzy logic which is one of the AI methods that can produce a system
that can automatically determine the on and off of the system automatically based
on incoming input, this system can be implemented with the variables used in this
study namely DO, pH, salinity, and temperature. The variables used have fuzzy
sets, namely the DO variable has 5 sets, namely bad, standard, fair, good, and very
good. Whereas for the pH variable, there are 3 fuzzy sets namely acid, neutral and
alkaline, for the salinity variable or what can be called the level of saltiness there
are 3 fuzzy sets namely fresh, brackish, and marine. The last variable is the
temperature variable which has a fuzzy set of heat, growth, and heat. All groups in
all variables have values adjusted to the salmon center ITERA pond standards, but
this system can be used depending on the needs of each type of fish by changing
the parameters and their values depending on the type of fish to be cultivated |
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