scholarly journals SISTEM PAKAR DIAGNOSA KERUSAKAN MOTOR KAWASAKI KLX150 MENGGUNAKAN METODE CASE-BASED REASONING DENGAN ALGORITMA 3W-JACCARD

2021 ◽  
Vol 9 (02) ◽  
pp. 68-74
Author(s):  
Edwin Febriansyah ◽  
Edy Winarno
Keyword(s):  
Zero Point ◽  
Case Based Reasoning ◽  
Mild Symptom ◽  
Revision Process ◽  
A Value ◽  
Calculation Results ◽  
Information Media ◽  
The City ◽  
Alternative Solutions ◽  
Case Based

In this day and age, motorbikes have an important role in transportation facilities, motorbike users are increasingly dense, especially in the city of Semarang, which is not accompanied by information media. The lack of media information regarding damage to the motorbike makes it difficult for someone to know the cause of the damage to the motorbike, not to mention the Kawasaki KLX150 which happens a lot of engine damage. For this reason, the expert system diagnoses motor damage by knowing the type of motor damage, after that diagnostics and alternative solutions to the problem are carried out. With this, the method and algorithm used is Case-Based Reasoning (CBR) using the Similarity 3W-Jaccard calculation, this second method and algorithm can be used to diagnose damage from the symptoms in the database. Each symptom has a weighted value of each, including a value of 5 (five) for severe symptoms, relating to engine and electrical parts, a value of 3 (three) for moderate symptoms, relating to braking and chains, a value of 1 (one) mild symptom, relating to with the indicator on the speedometer. The system will display 5 (five) types of damage calculated using the 3W-Jaccard Algorithm sorted by the highest value. The revision process will appear if the similarity calculation results are less than 0.6 (zero point six) because it is considered that the results are not sufficiently similar to the solution to be repaired, it needs to be reviewed and will be entered into the review table, then the expert will find a solution.

scholarly journals Case based Reasoning Prediksi Waktu Studi Mahasiswa Menggunakan Metode Euclidean Distance dan Normalisasi Min-Max

2020 ◽  
Vol 7 (6) ◽  
pp. 1279
Author(s):  
Henni Endah Wahanani ◽  
Made Hanindia Prami Swari ◽  
Fawwaz Ali Akbar
Keyword(s):  
Euclidean Distance ◽  
Intelligent System ◽  
Accurate Method ◽  
Case Based Reasoning ◽  
Study Program ◽  
A Value ◽  
Student Graduation ◽  
Case Data ◽  
Precision Testing ◽  
Case Based

<p>Salah satu penyebab dari lamanya waktu tempuh mahsiswa di Jurusan Informatika UPN “Veteran” Jawa Timur adalah sullitnya memantau kemajuan studi mahasiswa secara seksama, mengingat jumlah mahasiswa yang cukup banyak serta pihak akademik belum memiliki metode yang akurat untuk memetakan mahasiswa yang diprediksi akan mengalami keterlambatan dalam penyelesaian studinya. Melalui perkembangan teknologi informasi yang berkembang pesat saat ini, maka sangat dimungkinkan untuk membuat sebuah sistem yang mampu memprediksi kemungkinan keterlambatan kelulusan mahasiswa melalui penggunaan berbagai metode komputasi yang ada. Salah satu pendekatan yang dapat digunakan untuk membuat sebuah sistem prediksi kelulusan adalah menggunakan pendekatan populer yang digunakan dalam pembuatan sistem cerdas <em>(intelligent system) </em>yaitu <em>case based reasoning </em>(CBR). Langkah-langkah yang dilakukan pada penelitian ini adalah melakukan pengumpulan dan memasukkan data kasus pada basis kasus, melakukan praprosesing yakni normalisasi atribut yang akan digunakan dalam perhitungan similartitas antar kasus menggunakan normalisasi min-max, implementasi CBR menggunakan metode Euclidean Distance, serta melakukan pengujian pada 141 data kasus. Dari sisi perhitungan akurasi, sistem mampu memberikan nilai akurasi paling tinggi sebesar 100% pada pada pengujian berdasarkan predikat kelulusan, sedangkan berdasarkan ketepatan waktu, sistem mampu memberikan akurasi tertinggi dengan nilai 85,71%, dan sistem mampu memberikan nilai akurasi tertinggi sebesar 71,43% pada pengujian berdasarkan massa studi. Untuk pengujian presisi, sistem mampu mengasilkan nilai terbesar berturut-turut sebesar 90,90%, 43,33%, dan 100%. Sedangkan pada pengujian sensitivitas, sistem berturut-turut mampu menghasilan nilai sebesar 90,90%, 40,48%, dan 100%. Hasil pengujian ini tentunya sangat bergantung dari basis kasus yang dimiliki, oleh sebab itu perbaikan dan peningkatan jumlah kasus yang dimiliki diharapkan mampu meningkatkan performa sistem rekomendasi.</p><p> </p><p><strong><em>Abstract</em></strong></p><p class="Judul2"><em>One of the reasons for the length of study time for students of the Informatics study program of UPN "Veteran" </em><em>Jawa Timur</em><em> is the difficulty of monitoring the progressy, given the large number of students and academics do not have an accurate method to map students who are predicted to experience delays. </em><em>I</em><em>t is possible to create a system that is able to predict the possibility of student graduation delay through the use of various existing computational methods. One approach that can be used to create a graduation prediction system is to use the popular approach namely case based reasoning (CB).</em><em> </em><em>The steps taken in this study are collecting and entering case data, normalizing the attributes using min-max normalization, implementing CBR using the Euclidean Distance, and system testing</em><em> in 141 data case</em><em>.</em><em> </em><em>Sy</em><em>stem is able to provide the highest accuracy value of 100% in testing based on the predicate of graduation, while based on timeliness, the system is able to provide the highest accuracy value with a value of 85.71%, and the system is able to provide the highest accuracy value of 71.43%. on testing based on the study period. For precision testing, the system was able to produce the largest values of 90.90%, 43.33% and 100%, respectively. Whereas in the sensitivity test, the system was able to produce values of 90.90%, 40.48%, and 100% respectively. The results of this test are of course very dependent on the basis of cases that are owned, therefore improvements and an increase in the number of cases owned are expected to be able to improve the performance.</em></p><p><strong><em><br /></em></strong></p>

scholarly journals Where do I Go: Sistema de Recomendações Turísticas

2019 ◽  
Author(s):  
Mauricio Freitas ◽  
Anita Fernandes ◽  
Mônica Da silva
Keyword(s):  
User Profile ◽  
Case Based Reasoning ◽  
Interest Points ◽  
Semantic Constraints ◽  
Similar Solutions ◽  
The City ◽  
Case Based

Abstract. This paper describes the development of Where do I Go, a Mobile Tourist Recommendations System that uses recommendation of interest points according to user profile, temporal and semantic constraints, using Case Based Reasoning (CBR). The application aims to make recommendations to tourists during the experimentation of the city, which are in accordance with their tourism preferences and the context at the time of recommendation. CBR stores knowledge around a particular domain in case format, where each case has a problem part and another solution. CBR is premised on the fact that similar problems have similar solutions, where the basis for solving new problems is previously solved problems.

scholarly journals Implementasi case-based-reasoning pada deteksi estrus sapi perah menggunakan sorensen coefficient

JURNAL ELTEK ◽  
2020 ◽  
Vol 18 (2) ◽  
pp. 30
Author(s):  
Indra Dharma Wijaya ◽  
Milyun Ni’ma Shoumi ◽  
Triska Intania Sulistiyowati
Keyword(s):  
Dairy Cows ◽  
Test Method ◽  
Case Based Reasoning ◽  
Reasoning System ◽  
Accuracy Test ◽  
Calculation Results ◽  
Cattle Farming ◽  
Cattle Breeders ◽  
Further Development ◽  
Case Based

Subsektor peternakan memegang peranan penting dalam meningkatkan perekonomian Indonesia. Salah satu jenis peternakan di Indonesia adalah peternakan sapi. Jenis sapi yang cocok untuk dikembangkan adalah sapi perah. Sapi perah merupakan jenis sapi yang memiliki kemampuan dalam menghasilkan susu dalam jumlah besar. Permasalahan muncul ketika para peternak sapi ingin melakukan perkawinan terhadap sapi untuk menambah populasi dan produksi sapi, para peternak sering mengalami ketidaktepatan dalam mendeteksi estrus sehingga mengalami kegagalan bunting dan kawin berulang. Sistem penalaran berbasis kasus dengan metode Sorensen dapat digunakan untuk mendeteksi ketepatan estrus tetapi perlu ditambahkan proses perhitungan Similarity. Nilai akurasi sistem ditentukan dengan menggunakan metode pengujian perhitungan akurasi, dengan cara membandingkan hasil perhitungan pada Ms.Excel dengan hasil pada sistem. Hasil dari penelitian ini adalah sebuah sistem yang dapat mendeteksi estrus pada sapi perah dengan sistem Case-Based-Reasoning. Maka hasil pengujian akurasi sistem adalah 100%. Dengan penelitian ini dapat disimpulkan bahwa sistem penalaran berbasis kasus yang telah dibuat mampu menerapkan keahlian seorang pakar (dokter hewan) pada kasus peternakan sapi.   The livestock sub-sector is a vital part in improving the national economy. One type of livestock in Indonesia is cattle farming. The type of cow that is suitable for further development is dairy cows. Dairy cows are a type of cow that have the ability to produce large amounts of milk. The problem arises when cattle breeders aim to impregnate cows to increasing population and milk production. At this point, breeders are difficult in identifying estrus that may cause failure in pregnancy. The case-based reasoning system with the Sorensen method can be used to detect the accuracy of estrus, but the Similarity calculation process needs to be added. The system accuracy value is determined using the accuracy calculation test method, by comparing the calculation results on Ms. Excel with the results on the system. The result of this research is a system that can detect estrus in dairy cows with a Case-Based-Reasoning system. Then the system accuracy test results are 100%. With this research, the case-based reasoning system is helpful to apply the expertise of an expert (veterinarian) to the case of cattle farming.

Solving the Message Classification Problem in Voice Interaction Systems

Vestnik MEI ◽  
2020 ◽  
Vol 5 (5) ◽  
pp. 132-139
Author(s):  
Ivan E. Kurilenko ◽  
◽  
Igor E. Nikonov ◽  
Keyword(s):  
Artificial Intelligence ◽  
Classification Problem ◽  
Subject Area ◽  
Text Messages ◽  
Case Based Reasoning ◽  
Short Text ◽  
Proposed Modification ◽  
Voice Interaction ◽  
Text Content ◽  
Case Based

A method for solving the problem of classifying short-text messages in the form of sentences of customers uttered in talking via the telephone line of organizations is considered. To solve this problem, a classifier was developed, which is based on using a combination of two methods: a description of the subject area in the form of a hierarchy of entities and plausible reasoning based on the case-based reasoning approach, which is actively used in artificial intelligence systems. In solving various problems of artificial intelligence-based analysis of data, these methods have shown a high degree of efficiency, scalability, and independence from data structure. As part of using the case-based reasoning approach in the classifier, it is proposed to modify the TF-IDF (Term Frequency - Inverse Document Frequency) measure of assessing the text content taking into account known information about the distribution of documents by topics. The proposed modification makes it possible to improve the classification quality in comparison with classical measures, since it takes into account the information about the distribution of words not only in a separate document or topic, but in the entire database of cases. Experimental results are presented that confirm the effectiveness of the proposed metric and the developed classifier as applied to classification of customer sentences and providing them with the necessary information depending on the classification result. The developed text classification service prototype is used as part of the voice interaction module with the user in the objective of robotizing the telephone call routing system and making a shift from interaction between the user and system by means of buttons to their interaction through voice.

Feature level intentions based product recommendations with case-based reasoning

2018 ◽  
Vol 6 (1) ◽  
pp. 266-274
Author(s):  
D. Teja Santosh ◽  
◽  
K.C. Ravi Kumar ◽  
P. Chiranjeevi ◽  
◽  
...  
Keyword(s):  
Case Based Reasoning ◽  
Product Recommendations ◽  
Case Based

A Selection of Bandung City Travel Route Using The FLOYD-WARSHALL Algorithm

2020 ◽  
Vol 12 (7) ◽  
Author(s):  
Muhammad Ghifari Arfananda ◽  
◽  
Surya Michrandi Nasution ◽  
Casi Setianingsih ◽  
◽  
...  
Keyword(s):  
Traffic Congestion ◽  
Rapid Development ◽  
Route Selection ◽  
Tourist Attractions ◽  
Tourist Destinations ◽  
A Value ◽  
Distance Data ◽  
Simple Additive Weighting ◽  
The City ◽  
Selection Of

The rapid development of information and technology, the city of Bandung tourism has also increased. However, tourists who visit the city of Bandung have problems with a limited time when visiting Bandung tourist attractions. Traffic congestion, distance, and the number of tourist destinations are the problems for tourists travel. The optimal route selection is the solution for those problems. Congestion and distance data are processed using the Simple Additive Weighting (SAW) method. Route selection uses the Floyd-Warshall Algorithm. In this study, the selection of the best route gets the smallest weight with a value of 5.127 from the Algorithm process. Based on testing, from two to five tourist attractions get an average calculation time of 3 to 5 seconds. This application is expected to provide optimal solutions for tourists in the selection of tourist travel routes.

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