scholarly journals Penentuan Ekstrakurikuler Siswa Sesuai Minat Bakat dengan Case-Based Reasoning dan Certainty Factor

2021 ◽  
Vol 7 (3) ◽  
Author(s):  
Arjun Sirojul Anam ◽  
Faris Muslihul Amin ◽  
Mujib Ridwan
Keyword(s):  
Extracurricular Activities ◽  
Confusion Matrix ◽  
High Accuracy ◽  
Case Based Reasoning ◽  
Well Testing ◽  
Certainty Factor ◽  
Web Based ◽  
Precision Level ◽  
Web Based System ◽  
Case Based

Extracurricular activities at MAN 1 Lamongan are still determined without any support from the system. Students are only given extracurricular information and can register according to the conditions if interested. This makes the extracurricular that students have chosen does not fully match their abilities. The result is a decrease in the number of members who are active in extracurricular activities due to loss of interest. A web-based system was developed to assist MAN 1 Lamongan in determining extracurricular according to interests and talents. Case-Based Reasoning (CBR) is the system framework and Certainty Factor (CF) is the algorithm for determining the certainty value. The result is that with test data of 68 students, the system recommends extracurricular well. Testing with Confusion Matrix obtained precision level of 96.03% (high), recall of 99.4% (high), accuracy of 95.76% (high)

Insight into interface design of web-based case-based reasoning retrieval systems

2009 ◽  
Vol 36 (3) ◽  
pp. 7280-7287 ◽  
Author(s):  
Wu He ◽  
Feng-Kwei Wang ◽  
Tawnya Means ◽  
Li Da Xu
Keyword(s):  
Interface Design ◽  
Case Based Reasoning ◽  
Web Based ◽  
Retrieval Systems ◽  
Insight Into ◽  
Case Based

scholarly journals ANALISIS PERBANDINGAN TIGA METODE UNTUK MENDIAGNOSA PENYAKIT MATA PADA MANUSIA

2021 ◽  
Vol 8 (4) ◽  
pp. 1654-1664
Author(s):  
Ahmad Fahmi Adam
Keyword(s):  
Naive Bayes ◽  
Naïve Bayes ◽  
Case Based Reasoning ◽  
Certainty Factor ◽  
Case Based

Untuk mendiagnosa penyakit mata pada manusia diperlukan perhitungan probabilitas yang terbaik. Karena mata merupakan salah satu bagian terpenting pada tubuh manusia yang harus di jaga kesehatannya. Penelitian ini bertujuan untuk menganalisis perbandingan dari 3 metode diantaranya : metode Case-Based Reasoning, Naïve Bayes dan Certainty Factor sehingga bisa diketahui metode mana yang terbaik untuk melakukan pendiagnosaan. Setelah melakukan perbandingan, untuk perhitungan metode Case-Based Reasoning didapatkan hasil probabilitas 61,6 %, metode Naïve Bayes didapatkan hasil 56,36% dan metode Certainty Factor didapatkan hasil 90,4%. Dapat disimpulkan, metode Certainty Factor adalah metode yang terbaik untuk melakukan pendiagnosaan penyakit mata pada manusia. Setelah itu, akan dibuatkan suatu sistem pakar menggunakan metode Certainty Factor untuk mendiagnosa penyakit mata pada manusia. Sistem pakar merupakan peniru suatu pakar dalam melakukan diagnosis suatu penyakit. Tujuan dibuatkan sistem pakar ini, supaya dapat membantu pasien untuk mendiagnosa jenis penyakit mata apa berdasarkan gejala gejala yang dialaminya.

scholarly journals Analisis Penyakit Pada Tanaman Cabai Dengan Metode Case Based Reasoning Berbasis Web

2021 ◽  
Vol 1 (1) ◽  
pp. 43-48
Author(s):  
Desi Ernawati ◽  
Riki Andri Yusda ◽  
Guntur Maha Putra
Keyword(s):  
Expert System ◽  
Plant Diseases ◽  
Case Based Reasoning ◽  
Good Care ◽  
Web Based ◽  
Case Base ◽  
Case Base Reasoning ◽  
Case Based

Abstract:Chili is a production cropthatis much needed by the  community. Good care is needed to increase the production of chili plants. Production of chili plants will decrease if the types of diseases that attack are not considered. To find out about chili plant diseases, farmers only look at the disease without knowing the symptoms that appear beforehand so that it will affect the production of chili plants.So that we need experts who understand the symptoms of disease in chili plants.The existence of experts can be replaced by a system designed to detect symptoms of disease in chili plants.The expert system to be designed is web-based using the case-based reasoning method.This expert system is expected to help increase the productivity of chili plants.            Keywords:expert system; chili; case-based reasoning; chili plants.  Abstrak:Cabai merupakan tanaman produksi yang banyak dibutuhkan oleh masyarakat. Untuk meningkatkan produksi tanaman cabai diperlukan perawatan yang baik. Produksi dari tanaman cabai akan menurun jika tidak diperhatikan jenis penyakit yang menyerang. Untuk mengetahui penyakit tanaman cabai para petani hanya melihat penyakitnya saja tanpa mengetahui terlebih dahulu gejala yang muncul sehingga akan mempengaruhi hasil produksi tanaman cabai. Sehingga diperlukan pakar yang mengerti mengenai gejala penyakit pada tanaman cabai. Keberadaan pakar bisa digantikan oleh sebuah sistem yang dirancang untuk mendeteksi gejala penyakit pada tanaman cabai. Sistem pakar yang akan dirancang berbasis web dengan menggunakan metode case base reasoning. Sistem pakar ini nantinya diharapkan membantu untuk peningkatan produktivitas tanaman cabai. Kata kunci:sistem pakar; cabai; casebasereasoning; tanaman cabai.

Customized Recommendation Mechanism Based on Web Data Mining and Case-Based Reasoning

2008 ◽  
pp. 2659-2672
Author(s):  
Jin Sung Kim
Keyword(s):  
Data Mining ◽  
Shopping Mall ◽  
Case Based Reasoning ◽  
Web Data ◽  
Web Data Mining ◽  
Web Based ◽  
Additional Information ◽  
Hybrid Recommendation ◽  
Case Based

One of the attractive topics in the field of Internet business is blending Artificial Intelligence (AI) techniques with the business process. In this research, we suggest a web-based, customized hybrid recommendation mechanism using Case-Based Reasoning (CBR) and web data mining. CBR mechanisms are normally used in problems for which it is difficult to define rules. In web databases, features called attributes are often selected first for mining the association knowledge between related products. Therefore, data mining is used as an efficient mechanism for predicting the relationship between goods, customers’ preference, and future behavior. If there are some goods, however, which are not retrieved by data mining, we can’t recommend additional information or a product. In this case, we can use CBR as a supplementary AI tool to recommend the similar purchase case. Web log data gathered in a real-world Internet shopping mall was given to illustrate the quality of the proposed mechanism. The results showed that the CBR and web data mining-based hybrid recommendation mechanism could reflect both association knowledge and purchase information about our former customers.

Customized Recommendation Mechanism Based on Web Data Mining and Case-Based Reasoning

2004 ◽  
pp. 47-64 ◽  
Author(s):  
Jin Sung Kim
Keyword(s):  
Data Mining ◽  
Shopping Mall ◽  
Case Based Reasoning ◽  
Web Data ◽  
Web Data Mining ◽  
Web Based ◽  
Additional Information ◽  
Hybrid Recommendation ◽  
Case Based

One of the attractive topics in the field of Internet business is blending Artificial Intelligence (AI) techniques with the business process. In this research, we suggest a web-based, customized hybrid recommendation mechanism using Case-Based Reasoning (CBR) and web data mining. CBR mechanisms are normally used in problems for which it is difficult to define rules. In web databases, features called attributes are often selected first for mining the association knowledge between related products. Therefore, data mining is used as an efficient mechanism for predicting the relationship between goods, customers’ preference, and future behavior. If there are some goods, however, which are not retrieved by data mining, we can’t recommend additional information or a product. In this case, we can use CBR as a supplementary AI tool to recommend the similar purchase case. Web log data gathered in a real-world Internet shopping mall was given to illustrate the quality of the proposed mechanism. The results showed that the CBR and web data mining-based hybrid recommendation mechanism could reflect both association knowledge and purchase information about our former customers.

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