cbr sapi
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http://digilib.its.ac.id
SUMMARY
PENERAPAN CASE-BASED REASONING PADA SISTEM CERDAS UNTUKPENDETEKSIAN DAN PENANGANAN DINI PENYAKIT SAPI
CASE-BASED REASONING IMPLEMENTATION IN INTELLIGENT SYSTEM FOR COW DISEASE EARLYDETECTION AND TREATMENT
Created by PRAKOSO, IRLANDO MOGGI
Subject : Teknologi informasi
Subject Alt : Expert systems (computer science), Case-based reasoning, Artificial intelligence
Keyword : : Pendeteksian penyakit sapi; Case-Based Reasoning
Description :
Penyakit sapi memberikan dampak yang signifikan terhadap penurunan produksi daging dan susu bagi para peternak sapi. Untuk meminimalisir dampak buruk dari penyakit perlu dilakukan pendeteksian dan penanganan dini untuk mencegah tingginya kerugian yang akan terjadi. Sistem cerdas dapat memudahkan peternak sapi untuk melakukandiagnosa secara mandiri. Penelitian sebelumnya telah menghasilkan sistem cerdas untuk mendiagnosa penyakit sapimenggunakan algoritma Backpropagation Artificial neural Network(ANN). Namun ANN bersifat blackbox karena kitatidak dapat melihat informasi yang mendasari hasil diagnosa.Tugas akhir ini ditujukan untuk menjawab permasalahan tersebut, yakni dengan membuat sistem cerdas berbasisCased-Based Reasoning(CBR) untuk menyempurnakan sistem cerdas yang sebelumnya dibuat menggunakan ANN.CBR memberikan hasil diagnosa berdasarkan permasalahan terdahulu yang dapat direvisi untuk memecahkanpermasalahan terbaru. Dari ketiga uji coba baik dengan case didalam case memory(skenario 1),diluar casememory(skenario 2), maupun gejala parsial dari case memory(skenario 3) mendapatkan hasil yang baik dengan nilaiprecision 100% dan 95.83% untuk skenario 1 dan 3, serta nilai precision yang memang kurang baik untuk skenario 2yaitu sebesar 59.31%. Hasil yang kurang baik pada skenario 2 terjadi karena case yang digunakan merupakan case-caseyang belum pernah ditangani oleh sistem cerdas sehingga belum ada case di case memory yang memiliki ciri-ciri gejalayang sama dengan gejala yang diinputkan. Hal ini merupakan hal yang normal pada CBR, dan mengakibatkan hasildiagnosa dan solusi yang diusulkan dari case memory memiliki kemungkinan salah lebih besar. Dari hasil uji coba dapatdisimpulkan bahwa sistem cerdas ini dapat memberikan hasil diagnosa yang akurat dan memudahkan peternak sapidalam mendiagnosa secara mandiri.
Description Alt:Cow disease causes significant impact on meat and milk production degradation for livestock breeders. Actually Early
detection and treatment is necessary to minimalize the bad impact caused by cow desease and to avoid the high lossesthat will occur. Intelligent system is an alternative to eabse the livestock breeders to diagnose cow diseaseindependently. And the former research has produced intelligent system based on Backpropagation Artificial NeuralNetwork(ANN) to diagnose and give treatment suggestion that can be used by the breeders. But unfortunately ANNworks in a blackbox because the groundwork information which lead to the diagnostic result is unshown.This research is dedicated to solve the problem by making intelligent system based on Case-Based Reasoning(CBR) torefine the former intelligent system that made based on ANN. CBR suggests the diagnosis result based on past problemswhich can be revised to solve new problem accurately. From the three experiments, using cases from case memory(scenario 1), outside case memory (scenario 2), and partial symptoms from case memory (scenario 3) gives good resultwith 100% and 95.83% precision value for scenario 1 and 3. And precision value which is actually true with only
59.31% for scenario 2. The poor result in scenario 2 caused by the cases used in experiment are cases that never beenfaced by intelligent system, so there is no cases in case memory has the same symptoms with the symptom entered inintelligent system. The poor result for scenario 2 is normal in CBR, and increases the possibility to give wrong
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diagnostic result. So it can be concluded from the experiments that this intelligent system can suggests diagnostic resultaccurately and eases the breeders to diagnose cow disease independently.
Contributor : Wiwik Anggraeni, S.Si., M.Kom.
Date Create : 20/07/2012
Type : Text
Format : pdf
Language : Indonesian
Identifier : ITS-Undergraduate-52001130002209
Collection : 52001130002209
Call Number : RSSI 006.333 Pra p
Source : Undergraduate Thesis of Information System, RSSI 006.333 Pra p, 2013
COverage : ITS Community
Right : Copyright @2013 by ITS Library. This publication is protected by copyright and per obtainedfrom the ITS Library prior to any prohibited reproduction, storage in a re transmission in any formor by any means, electronic, mechanical, photocopying, reco For information regardingpermission(s), write to ITS Library
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Thank You,
Nur Hasan ( [email protected] )
Supervisor
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