scholarly journals Pembuatan Aplikasi Diagnosa Kerusakan Mesin Sepeda Motor Matic dengan Case-Based Reasoning

2015 ◽  
Vol 2 (3) ◽  
pp. 192
Author(s):  
Sandy Kosasi
Keyword(s):  
Intelligent System ◽  
Automatic Transmission ◽  
Case Based Reasoning ◽  
Test Results ◽  
Design Development ◽  
System Validation ◽  
Wheeled Vehicle ◽  
System Maintenance ◽  
Motorcycle Engine ◽  
Case Based

Sepeda motor matic sebagai terobosan baru kendaraan roda dua dengan transmisi otomatis memberikan implikasi kepada sistem perawatannya. Jumlah mekanik yang terbatas dan minimnya pengetahuan pengguna menyebabkan berbagai kesulitan dalam perawatannya khususnya dalam mengatasi kerusakan mesin. Pembuatan aplikasi sistem cerdas melalui metode case-based reasoning dapat memberikan kemudahan melakukan diagnosis awal secara mandiri. Case-based reasoning memiliki kemampuan dapat memberikan hasil diagnosis yang lebih akurat berdasarkan kejadian terdahulu dan dapat direvisi kembali dalam memecahkan permasalahan terbaru. Metode perancangan aplikasinya menggunakan reuse-based yang meliputi enam tahap yaitu spesifikasi persyaratan, analisis komponen, modifikasi persyaratan, integrasi design sistem dengan reuse, pengembangan dan integrasi, serta validasi sistem. Tujuan penelitian untuk melakukan diagnosa kerusakan mesin sepeda motor matic dan memberikan solusi awal mengenai kondisi kerusakan dan pencegahannya melalui media situs web. Hasil pengujian memperlihatkan aplikasi ini memiliki kemampuan mendiagnosa kerusakan dan memberikan solusi penyelesaian masalah dari pengguna dengan rata-rata nilai similaritas antara 0,62 dan 0,7 dengan nilai keakuratan solusi dari pakar sebesar 80% dan 90%. Automatic motorcycles as a new breakthrough of two-wheeled vehicle with an automatic transmission have implications for the system maintenance. A limited number of mechanics and lack of users’ knowledge cause many difficulties in treatment, especially in dealing with the engine damage. The Design of the intelligent system through case-based reasoning method can provide easiness of initial diagnosis independently. Case-based reasoning has the ability to provide more accurate diagnosis results based on the previous events and may be revised to solve the latest problems. The design of application uses a reuse-based method that includes six stages: requirements specification, component analysis, modification of the terms, integration with reuse system design, development and integration, and system validation. The purpose of the research is for diagnosing automatic motorcycle engine damage and provide an initial solution on its condition and prevention through the medium of the website. The test results demonstrate that this application has the ability to diagnose the damage and provide problem solving solutions to the users with an average of similarity value between 0,62 and 0,7 with an accuracy value of expert solutions for 80% and 90%.

Integrating fuzzy case-based reasoning, parametric and feature-based cost estimation methods for machining process

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Fentahun Moges Kasie ◽  
Glen Bright
Keyword(s):  
Cost Estimation ◽  
Intelligent System ◽  
Machining Process ◽  
Estimation Methods ◽  
Case Based Reasoning ◽  
Cost Estimates ◽  
Content Type ◽  
Estimation Techniques ◽  
Feature Based ◽  
Case Based

Purpose This paper aims to propose an intelligent system that serves as a cost estimator when new part orders are received from customers. Design/methodology/approach The methodologies applied in this study were case-based reasoning (CBR), analytic hierarchy process, rule-based reasoning and fuzzy set theory for case retrieval. The retrieved cases were revised using parametric and feature-based cost estimation techniques. Cases were represented using an object-oriented (OO) approach to characterize them in n-dimensional Euclidean vector space. Findings The proposed cost estimator retrieves historical cases that have the most similar cost estimates to the current new orders. Further, it revises the retrieved cost estimates based on attribute differences between new and retrieved cases using parametric and feature-based cost estimation techniques. Research limitations/implications The proposed system was illustrated using a numerical example by considering different lathe machine operations in a computer-based laboratory environment; however, its applicability was not validated in industrial situations. Originality/value Different intelligent methods were proposed in the past; however, the combination of fuzzy CBR, parametric and feature-oriented methods was not addressed in product cost estimation problems.

scholarly journals Sistem Cerdas Permainan Papan The Battle Of Honor dengan Decision Making dan Machine Learning

2021 ◽  
Vol 12 (2) ◽  
pp. 136
Author(s):  
Arnan Dwika Diasmara ◽  
Aditya Wikan Mahastama ◽  
Antonius Rachmat Chrismanto
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Making ◽  
Intelligent System ◽  
Third Party ◽  
Case Based Reasoning ◽  
Board Game ◽  
Rule Based ◽  
Case Based ◽  
Rule Based Systems

Abstract. Intelligent System of the Battle of Honor Board Game with Decision Making and Machine Learning. The Battle of Honor is a board game where 2 players face each other to bring down their opponent's flag. This game requires a third party to act as the referee because the players cannot see each other's pawns during the game. The solution to this is to implement Rule-Based Systems (RBS) on a system developed with Unity to support the referee's role in making decisions based on the rules of the game. Researchers also develop Artificial Intelligence (AI) as opposed to applying Case-Based reasoning (CBR). The application of CBR is supported by the nearest neighbor algorithm to find cases that have a high degree of similarity. In the basic test, the results of the CBR test were obtained with the highest formulated accuracy of the 3 examiners, namely 97.101%. In testing the AI scenario as a referee, it is analyzed through colliding pieces and gives the right decision in determining victoryKeywords: The Battle of Honor, CBR, RBS, unity, AIAbstrak. The Battle of Honor merupakan permainan papan dimana 2 pemain saling berhadapan untuk menjatuhkan bendera lawannya. Permainan ini membutuhkan pihak ketiga yang berperan sebagai wasit karena pemain yang saling berhadapan tidak dapat saling melihat bidak lawannya. Solusi dari hal tersebut yaitu mengimplementasikan Rule-Based Systems (RBS) pada sistem yang dikembangkan dengan Unity untuk mendukung peran wasit dalam memberikan keputusan berdasarkan aturan permainan. Peneliti juga mengembangkan Artificial Intelligence (AI) sebagai lawan dengan menerapkan Case-Based reasoning (CBR). Penerapan CBR didukung dengan algoritma nearest neighbour untuk mencari kasus yang memiliki tingkat kemiripan yang tinggi. Pada pengujian dasar didapatkan hasil uji CBR dengan accuracy yang dirumuskan tertinggi dari 3 penguji yaitu 97,101%. Pada pengujian skenario AI sebagai wasit dianalisis lewat bidak yang bertabrakan dan memberikan keputusan yang tepat dalam menentukan kemenangan.Kata Kunci: The Battle of Honor, CBR, RBS, unity, AI

scholarly journals Designing Intelligent Tutoring Systems: A Personalization Strategy using Case-Based Reasoning and Multi-Agent Systems

2013 ◽  
Vol 2 (1) ◽  
pp. 41-54
Author(s):  
Carolina González ◽  
Juan Carlos Burguillo ◽  
Martín Llamas ◽  
Rosalía Laza
Keyword(s):  
Intelligent Tutoring Systems ◽  
Intelligent Agents ◽  
Intelligent System ◽  
Intelligent Tutoring ◽  
Educational Systems ◽  
Case Based Reasoning ◽  
Multi Agent Systems ◽  
Tutoring Systems ◽  
Student Profile ◽  
Case Based

Intelligent Tutoring Systems (ITSs) are educational systems that use artificial intelligence techniques for representing the knowledge. ITSs design is often criticized for being a complex and challenging process. In this article, we propose a framework for the ITSs design using Case Based Reasoning (CBR) and Multiagent systems (MAS). The major advantage of using CBR is to allow the intelligent system to propose smart and quick solutions to problems, even in complex domains, avoiding the time necessary to derive those solutions from scratch. The use of intelligent agents and MAS architectures supports the retrieval of similar students models and the adaptation of teaching strategies according to the student profile. We describe deeply how the combination of both technologies helps to simplify the design of new ITSs and personalize the e-learning process for each student

scholarly journals Metode Modified Weighted Minkowski Untuk Pengembangan Sistem Penalaran Berbasis Kasus

2017 ◽  
Vol 7 (1) ◽  
pp. 1
Author(s):  
Edi Faizal
Keyword(s):  
Data Collection ◽  
Knowledge Acquisition ◽  
Error Rate ◽  
Case Based Reasoning ◽  
Test Results ◽  
Research Focus ◽  
Accuracy Rate ◽  
Different Levels ◽  
Case Based ◽  
Representation Of Knowledge

Knowledge acquisition process is not easy, because of the different levels of expertise even though all true. Computer experts had tried other methods to resolve the problem of the acquisition, which is known as case-based reasoning. Representation of knowledge in CBR is a collection of previous case. This research focus is the application of CBR for diagnosing womb diseases. The level of similarity is calculated by using the modified weighted Minkowski. Methods of data collection are interviews, observation and study of literature. The test results show the system can be recognize the womb disease correctly is 94.44% (sensitivity), specitifity rate of 57.14%, PPV of 85.00% and 80.00% NPV. The system have an accuracy rate of 84.00% with an error rate of 16.00%.

Developing a new intelligent system for the diagnosis of oral medicine with case‐based reasoning approach

Oral Diseases ◽  
2019 ◽  
Vol 25 (6) ◽  
pp. 1555-1563 ◽  
Author(s):  
Hamideh Ehtesham ◽  
Reza Safdari ◽  
Arash Mansourian ◽  
Shahram Tahmasebian ◽  
Niloofar Mohammadzadeh ◽  
...  
Keyword(s):  
Intelligent System ◽  
Case Based Reasoning ◽  
Oral Medicine ◽  
Case Based

scholarly journals Penyelesaian Masalah Pengelolaan Lumbung Pangan Desa Menggunakan Case-Based Reasoning dengan Algoritma K-Nearest Neighbor

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Mgs. Afriyan Firdaus ◽  
Dwi Rosa Indah ◽  
Putri Eka Sevtiyuni ◽  
Choirunnisa Qonitah
Keyword(s):  
Problem Solving ◽  
Nearest Neighbor ◽  
Technical Problem ◽  
Case Based Reasoning ◽  
Test Results ◽  
K Nearest Neighbor ◽  
Nearest Neighbor Algorithm ◽  
Existing Problems ◽  
K Nearest Neighbor Algorithm ◽  
Case Based

In this paper, we discuss the problem solving of village food barn management using Case-Based Reasoning (CBR) with the K-Nearest Neighbor algorithm. This research was carried out by adopting the stages of the CBR cycle and the nearest neighbor algorithm. The results of the study show that the application of CBR and K-nearest neighbor algorithms can support the resolution of knowledge problems in village food barn management using technical problem solving based on the symptoms and solutions to existing problems. Based on the test results, the problem-solving accuracy was 92%.Keywords - case-based reasoning, K-nearest neighbor, food barn, problem-solving

scholarly journals SISTEM PENALARAN BERBASIS KASUS UNTUK PENDUKUNG DIAGNOSIS GANGGUAN PENYAKIT PADA UNGGAS (Case Based Reasoning System to Support Diagnosis of Diseases in Poultry)

2017 ◽  
Vol 2 (1) ◽  
Author(s):  
Murien Nugraheni ◽  
Sri Hartati
Keyword(s):  
Cosine Similarity ◽  
Case Based Reasoning ◽  
Test Cases ◽  
Test Results ◽  
Reasoning System ◽  
C4.5 Algorithm ◽  
Amount Of Knowledge ◽  
Similarity Method ◽  
Case Based ◽  
Diagnosis Of Diseases

Case-Based Reasoning (CBR) is a computer system that uses old knowledge to solve new problems. CBR provide solutions for new cases by looking at an old case that comes closest to the new case. It will be very useful because it eliminates the need to extract the model as required by the rules-based system. Moreover, CBR can also be started from a small amount of knowledge, because the knowledge of CBR can be increased gradually when a case is added.This study tries to establish a system for Case-Based Reasoning System to Support Diagnosis of Diseases in Poultry by looking at the characteristics of existing symptoms in poultry. Diagnosis process is done by inserting a new cases that contain the symptoms of the disease to be diagnosed into the system, then the system will do the indexing process or classification with C4.5 algorithm method to obtain an index of new cases. After obtaining an index of the cases, then the system do the calculating of the value of similarity between the new case by case which has the same index with new cases using Cosine Similarity method. The case taken is the case with the highest similarity value. If a case is not successfully diagnosed, then the case will be revised by experts. Revised successful cases will be stored into the system to be used as new knowledge for the system.The results showed case-based reasoning system to diagnose disease of poultry can help experts and farmers in performing diagnostics. The test results of 30 test cases, system has been to produce similarity of 28 cases (93.33%) and obtained 2 cases (6.67%) have similarity values below 0.8 will be revised by experts.Keywords: CBR, poultry, indexing, similarity, cosine similarity

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