scholarly journals DIAGNOSA PENYAKIT PADA IKAN AIR TAWAR DENGAN METODE RULE-BASED DAN CASE BASED REASONING

2019 ◽  
Vol 4 (1) ◽  
pp. 67
Author(s):  
Hisma Abduh
Keyword(s):  
Nearest Neighbor ◽  
Case Based Reasoning ◽  
Data Input ◽  
Certainty Factor ◽  
Rule Based ◽  
Case Based

Para pelaku usaha budidaya ikan air tawar, khususnya dalam pemeliharaan ikan di kolam air tawar sudah jelas dituntut agar apa yang diusahakan pada usaha pembesaran ikan dapat berkembang atau tumbuh dengan baik, cepat dan tumbuh besar sehingga produksi akan berhasil secara baik dan bisa memuaskan dengan keuntungan yang maksimal. Untuk mencapai hasil tersebut sudah jelas bahwa pelaku usaha  perlu memahami beberapa teknik yang harus dijalankan sehingga apa yang dilakukan dalam usaha tersebut dapat berhasil dengan baik dan ikan bisa tumbuh berkembang secara cepat dan sempurna. Untuk  menghambat kegagalan dalam pemeliharaan ikan maka perlu dibuat sebuah sistem pakar dengan menggunakan penggabungan RBR dan CBR. Sistem pakar dimulai dengan melakukan pengecekan data masukan berdasarkan aturan yang telah tersimpan dalam basis aturan dengan menerapkan metode certainty factor. Bersamaan dengan itu juga sistem akan melakukan pengecekan data input berdasarkan kasus yang tersimpan dalam basis kasus dengan menerapkan metode nearest neighbor. Hasil penelitian menghasilkan bahwa sistem mengenali 24 data yang sesuai dengan data riil hasil diagnosa pakar dan 6 data yang tidak sesuai dengan data riil hasil diagnosa pakar atau bisa dikatakan nilai akurasi sistem sebesar 80 %.

scholarly journals Rancang Bangin Case Based Reasoning untuk Diagnosis Hama dan Penyakit Tanaman Nilam menggunakan Nearest Neighbor Kombinasi Certainty Factor

2020 ◽  
Vol 7 (3) ◽  
pp. 477
Author(s):  
Rabiah Adawiyah ◽  
Fitrianti Handayani
Keyword(s):  
Nearest Neighbor ◽  
Raw Material ◽  
Case Based Reasoning ◽  
Certainty Factor ◽  
Accuracy Rate ◽  
Pests And Diseases ◽  
System Diagnosis ◽  
Case Study Site ◽  
Case Based

<p class="Judul2" align="left"> </p><p>Tanaman nilam menghasilkan minyak nilam (<em>patchouli oil</em>) yang digunakan sebagai bahan baku kosmetik, parfum, antiseptik, sabun, obat, dan insektisida. Dalam pengembangan dan peningkatannya tanaman nilam mengalami beberapa kendala seperti serangan hama dan penyakit yang mengakibatkan rendahnya hasil panen khususnya pada daerah Desa Gunung Sari Kecamatan Watubangga Kabupaten Kolaka. Pengembangan tanaman nilam yang terserang hama dan penyakit seringkali terhambat karena masih banyak petani yang tidak mengetahui jenis hama dan penyakit yang menyerang tanaman petani. Oleh sebab itu sistem pakar berbasis kasus atau <em>Case Based Reasoning (CBR)</em> dibangun untuk mendiagnosis jenis hama dan penyakit tanaman nilam. Pada penelitian ini digunakan 7 jenis penyakit dan 22 gejala berdasarkan studi kasus tempat penelitian. CBR menggunakan metode<em> similarity</em> Nearest Neighbor untuk menemukan kemiripan antar kasus yang berada dalam tahapan <em>retrieve</em>. Pada penelitian ini digunakan juga metode lain yaitu Certainty Factor yang berfungsi untuk mengetahui derajat kepercayaan terhadap hasil diagnosis sistem dalam menghasikan jenis hama dan penyakit tanaman nilam. Berdasarkan hasil penelitian dengan menggunakan kombinasi dua metode Nearest Neighbor dan Certainty factor maka dihasilkan sistem mampu melakukan diagnosis hama dan penyakit tanaman nilam dengan nilai <em>similarity</em> 0.7 dan tingkat kepercayaaan sebesar 97,2 %  serta menghasilkan tingkat akurasi sistem sebesar 93.82 % dan tingkat kesalahan sistem 3 %</p><div><p> </p><p><em><strong>Abstract</strong></em></p><p><em>Patchouli oil is used as a raw material for cosmetics, perfumes, antiseptics, soaps, medicines, and insecticides. In the development and improvement of patchouli plants experienced several obstacles such as pests and diseases which resulted in low yields, especially in the area of Gunung Sari Village, Watubangga District, Kolaka Regency. The development of patchouli plants attacked by pests and diseases is often hampered because there are still many farmers who do not know the types of pests and diseases that attack farmers' crops. Therefore a case based reasoning (CBR) expert system was built to diagnose patchouli plants and pests. In this study 7 types of diseases were used and 22 symptoms were based on the case study site. CBR uses the similarity Nearest Neighbor method to find similarities between cases that are in the retrieval stage. In this study, another method is used, namely Certainty Factor, which functions to determine the degree of trust in the results of system diagnosis in producing patchouli species and diseases. Based on the results of the study by using a combination of the two Nearest Neighbor and Certainty factor methods, the system was able to diagnose patchouli pests and diseases with a similarity value of 0.7 and a confidence level of 97.2% and produce a system accuracy rate of 93.82% and a system error rate of 3%</em></p><p><em><strong><br /></strong></em></p></div>

Graphical Fault Diagnosis Expert System of CNC Machine Tool Based on B/S

2014 ◽  
Vol 945-949 ◽  
pp. 1707-1712
Author(s):  
Bin Shen ◽  
Shu Yu Zhao ◽  
Jia Hai Wang ◽  
Juergen Fleischer
Keyword(s):  
Fault Diagnosis ◽  
Expert System ◽  
Machine Tool ◽  
Case Based Reasoning ◽  
Cnc Machine Tool ◽  
Cnc Machine ◽  
Rule Based ◽  
Detailed Case ◽  
Case Based ◽  
Remote Fault Diagnosis

Based on the authors previous work of developing an expert system for fault diagnosis of CNC machine tool, this paper studied the theory and method of CNC remote fault diagnosis expert system based on B/S, and presents schema and structure of the expert system in detailed. Case based reasoning is used for the multi-alarm diagnosis, and rule based reasoning is used for single-alarm diagnosis. At last fault diagnosis expert system was designed and developed making use of C# and ASP.NET.

A Case Based Reasoning System For Recommendation Of Restaurant In Jimbaran Using K-Nearest Neighbor

2020 ◽  
Vol 9 (2) ◽  
pp. 267
Author(s):  
I Gede Teguh Mahardika ◽  
I Wayan Supriana
Keyword(s):  
Recommendation System ◽  
Nearest Neighbor ◽  
Case Based Reasoning ◽  
Retrieval Process ◽  
K Nearest Neighbor ◽  
Reasoning System ◽  
Human Ability ◽  
And Function ◽  
Case Based ◽  
Selection Of

Culinary is one of the favorite businesses today. The number of considerations to choose a restaurant or place to visit becomes one of the factors that is difficult to determine the restaurant or place to eat. To get the desired place to eat advice, one needs a recommendation system. Decisions made by the recommendation system can be used as a reference to determine the choice of restaurants. One method that can be used to build a recommendation system is Case Based Reasoning. The Case Based Reasoning (CBR) method mimics human ability to solve a problem or cases. The retrieval process is the most important stage, because at this stage the search for a solution for a new case is carried out. The study used the K-Nearest Neighbor method to find closeness between new cases and case bases. With the selection of features used as domains in the system, the results of recommendations presented can be more suggestive and accurate. The system successfully provides complex recommendations based on the type and type of food entered by the user. Based on blackbox testing, the system has features that can be used and function properly according to the purpose of creating the system.

Retrieving Assembly Part Design Using Case-Based Reasoning and Genetic Algorithms

2005 ◽  
Author(s):  
Guanghsu A. Chang ◽  
Cheng-Chung Su ◽  
John W. Priest
Keyword(s):  
Artificial Intelligence ◽  
Genetic Algorithms ◽  
Nearest Neighbor ◽  
Similarity Measures ◽  
Experimental Results ◽  
Case Based Reasoning ◽  
Feature Weight ◽  
Similar Part ◽  
Case Base ◽  
Case Based

Artificial intelligence (AI) approaches have been successfully applied to many fields. Among the numerous AI approaches, Case-Based Reasoning (CBR) is an approach that mainly focuses on the reuse of knowledge and experience. However, little work is done on applications of CBR to improve assembly part design. Similarity measures and the weight of different features are crucial in determining the accuracy of retrieving cases from the case base. To develop the weight of part features and retrieve a similar part design, the research proposes using Genetic Algorithms (GAs) to learn the optimum feature weight and employing nearest-neighbor technique to measure the similarity of assembly part design. Early experimental results indicate that the similar part design is effectively retrieved by these similarity measures.

scholarly journals Rule-Based and Case-Based Reasoning in Housing Prices

2007 ◽  
Vol 7 (1) ◽  
Author(s):  
Gabrielle Gayer ◽  
Itzhak Gilboa ◽  
Offer Lieberman
Keyword(s):  
Housing Prices ◽  
Case Based Reasoning ◽  
Rule Based ◽  
Case Based

A Tele-command verification of KOMPSAT-II using Rule-based & Case-based reasoning

2002 ◽  
Author(s):  
Won-Chan Jung ◽  
Hee-Sook Mo ◽  
Jae-Hoon Kim ◽  
Seong-Pal Lee
Keyword(s):  
Case Based Reasoning ◽  
Rule Based ◽  
Case Based

The Study of Hybrid Gaussian CBR Technique and Using in Camshaft Design System

2010 ◽  
Vol 108-111 ◽  
pp. 603-607
Author(s):  
Wei Yan ◽  
Xue Qing Li ◽  
Xu Guang Tan ◽  
De Hui Tong ◽  
Qi Gao
Keyword(s):  
Expert System ◽  
Decision Model ◽  
Nearest Neighbor ◽  
Design System ◽  
Case Based Reasoning ◽  
K Nearest Neighbor ◽  
Engine Design ◽  
Cam Profile ◽  
Aided Design ◽  
Case Based

In this paper, we propose a hybrid decision model using case-based reasoning augmented the Gaussian and k nearest neighbor methods for aided design camshaft in engine. The hybrid Gaussian k-NN (HGKNN) CBR scheme is designed to compute memberships between cam profile and engine parameters, which provides a more flexible and practical mechanism for reusing the decision knowledge. These methods were implemented in the database application and expert system following the examples of Cam Profile. To get the designed case, the retrieved results were compared and analyzed by HGKNN and k-NN algorithm in the CBR database. It proves the validity of HGKNN and CBR design system is used successfully in engine design process.

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