The Comparison Combination of Naïve Bayes Classification Algorithm with Fuzzy C-Means and K-Means for Determining Beef Cattle Quality in Semarang Regency

Devi, Feroza Rosalina; Sugiharti, Endang; Arifudin, Riza

doi:10.15294/sji.v5i2.15452

Cited by 2 publications

(2 citation statements)

References 9 publications

(7 reference statements)

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“…The result was evaluated using a confusion matrix. After the test results are known, determine the accuracy using a confusion matrix [24]. Besides that, count precision and recall too.…”

Section: Resultsmentioning

confidence: 99%

Restricted boltzmann machine and softmax regression for acute respiratory infections disease identification

2022

joscex

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Restricted boltzmann machines (RBM) have attracted much attention lately after being proposed as building blocks of deep learning blocks. RBM is an algorithm that belongs to the artificial neural network (ANN) algorithm. Deep learning models can be used in the health field to identify diseases using medical data records. Acute Respiratory Infection (ARI) is a disease that infects the respiratory tract. A patient infected by ARI diseases is high. To identify ARI can use the symptoms that the patient had experienced. Based on this background, this study aims to help identify ARI disease using its symptoms. The method used for identification is the deep learning model, which was built using the RBM and softmax regression. Three steps were used in this research, which are training, testing, and implementation. The trained deep learning model will be implemented to identify ARI disease. This research will use ARI data from Puskemas Warungasem, Indonesia. From the research result, the deep learning model can get an accuracy of 96%. The deep learning configuration used in this research has 4 RBM layers, 1 Softmax layer as the output layer, and a learning rate value of 0.01 and 1000 iterations. This research can be used as a reference so that the next researcher can add other algorithms to Deep learning to improve accuracy.

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“…The result was evaluated using a confusion matrix. After the test results are known, determine the accuracy using a confusion matrix [24]. Besides that, count precision and recall too.…”

Section: Resultsmentioning

confidence: 99%

Restricted boltzmann machine and softmax regression for acute respiratory infections disease identification

2022

joscex

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“…Beberapa penelitian seperti pada [2] memperbandingkan daging sapi dan daging babi. Kelemahan kedua, beberapa penelitian yang berfokus pada kualitas daging sapi seperti pada [3], [5] menggunakan dataset private maupun publik masih memiliki performa yang belum optimal. Akurasinya berkisar antara 70-85%.…”

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Penerapan Metode Convolutional Neural Network Untuk Klasifkasi Kualitas Daging Sapi Pada Aplikasi Berbasis Android

Asmoro,

Solichin

2024

FaktorExacta

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The surging demand for beef in Indonesia poses a significant challenge for the food industry, leading to fraudulent practices among meat traders. To meet the high consumer demand and gain higher profits, fresh beef is mixed with spoiled meat. Unfortunately, many consumers are unable to distinguish between fresh and spoiled beef, relying solely on the meat's aroma to determine its quality. However, recognizing spoiled beef requires considering other indicators of spoilage. To address this issue, researchers focused on developing a beef quality classification system using the Convolutional Neural Network (CNN) method. The study involved implementing TensorflowLite on Android devices and training the CNN model with deep learning algorithms to recognize visual patterns in beef images. The Android application provides clear and user-friendly classification results. The developed beef quality classification system achieved remarkable accuracy, with a precision of 97%, a recall of 96%, and an f1-score of 97%. With 100 beef images as test data, the system demonstrated an accuracy rate of 95.69%. This advancement is expected to improve the efficiency and quality of beef processing in Indonesia, ensuring consumers receive genuine and safe products.

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The Comparison Combination of Naïve Bayes Classification Algorithm with Fuzzy C-Means and K-Means for Determining Beef Cattle Quality in Semarang Regency

Cited by 2 publications

References 9 publications

Restricted boltzmann machine and softmax regression for acute respiratory infections disease identification

Restricted boltzmann machine and softmax regression for acute respiratory infections disease identification

Penerapan Metode Convolutional Neural Network Untuk Klasifkasi Kualitas Daging Sapi Pada Aplikasi Berbasis Android

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