ADINDA, RAHMI SARASWATI (2019) SISTEM PAKAR DIAGNOSIS PENYAKIT IKAN GURAMI (OSPHRONEMUS GORAMY) MENGGUNAKAN CASE BASED REASONING. Undergraduate Thesis thesis, Institut Telkom Purwokerto.
Text
Cover.pdf - Accepted Version Download (1MB) |
||
|
Text
Abstract.pdf - Accepted Version Download (208kB) | Preview |
|
|
Text
Abstrak.pdf - Accepted Version Download (207kB) | Preview |
|
|
Text
BAB I.pdf - Accepted Version Download (572kB) | Preview |
|
|
Text
BAB II.pdf - Accepted Version Download (530kB) | Preview |
|
|
Text
BAB III.pdf - Accepted Version Download (973kB) | Preview |
|
Text
BAB IV.pdf - Accepted Version Restricted to Registered users only Download (1MB) |
||
|
Text
BAB V.pdf - Accepted Version Download (208kB) | Preview |
|
|
Text
Daftar Pustaka.pdf - Accepted Version Download (431kB) | Preview |
Abstract
ABSTRACT Gurami (Osphronemus Goramy) is a fish that is widely cultivated and consumed by the community. This fish is a leading sector in several regions of Banyumas district. Gouramy which is cultivated by the Banyumas people, is actually not without obstacles. One obstacle for gouramy breeders is a disease caused by bacteria. Reporting from the online news portal, circulating in February 2018 circulated that news about Gurami farmers was losing money because thousands of broodstock fish that had been raised to death were attacked by bacterial diseases, namely Aeromoniasis. Experts who handle this are limited, namely only 2 people in the Banyumas Regency. In this study the authors made an expert system to diagnose Gurami fish disease caused by bacteria. This study uses the Case Based Reasoning (CBR) and Nearest Neighbor methods used to get the best solution from the identified case. The CBR method compares the old case with the new case and calculates a case similarity value. The system was built with 13 symptoms and 3 Gurami diseases caused by bacteria. Each symptom each has a weight of 5, 3, and 1. The highest similarity value can be used as a conclusion for the case most similar to the expert diagnosis. So that from these two methods an expert system can be produced that can diagnose and analyze according to the similarity of symptoms to the disease, as well as display solutions to the treatment of diagnosed diseases. The test results are between cases and the system uses the similarity calculation to achieve the best value of 100%. The results of the system accuracy test for diagnoses that are in accordance with the expert's mind, obtained results of 93.33% from 30 cases tested with the system. The conclusion of these results is that the system can be said to be feasible to diagnose Gurami disease caused by bacteria according to what experts think. Keywords : Case Based Reasoning, Expert System, Nearest Neighbor, Similarity.
Item Type: | Thesis (Undergraduate Thesis) |
---|---|
Subjects: | T Technology > T Technology (General) |
Divisions: | Faculty of Industrial Engineering and Informatics > Informatics Engineering |
Depositing User: | Users 218 not found. |
Date Deposited: | 05 Jun 2020 18:27 |
Last Modified: | 23 Apr 2021 06:44 |
URI: | http://repository.ittelkom-pwt.ac.id/id/eprint/5674 |
Actions (login required)
View Item |