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Mohamad Irfan(2)
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Department of Orthopaedic and Traumatology, Diponegoro University, Semarang, Indonesia(1)
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dept. informatics, Universitas Islam Negeri Sunan Gunung Djati Bandung, Bandung, Indonesia(1)
2015 International Conference on Automation, Cognitive Science, Optics, Micro Electro-Mechanical System, and Information Technology (ICACOMIT)(1)
2023 IEEE 9th International Conference on Computing, Engineering and Design (ICCED)(1)
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Implementation of the Forward Chaining and Dempster Shafer Methods in Diagnosing Tonsillitis

Ichsan Taufik;Mohamad Irfan;Dicky Wahyudi;Yana Aditia Gerhana;Aldy Rialdy Atmadja

2023 IEEE 9th International Conference on Computing, Engineering and Design (ICCED)

Year: 2023 | Conference Paper |

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In seven Indonesian provinces, tonsillitis is the third most common Ear, Nose, and Throat infection condition, affecting about 287,000 children under 15 worldwide. The patient experiences pain during examinations since clinicians still check the patient’s oral cavity directly for extended periods. As a result, we require a system that will aid medical professionals in identifying and explaining to...Show More

Implementation of the Forward Chaining and Dempster Shafer Methods in Diagnosing Tonsillitis

Ichsan Taufik;Mohamad Irfan;Dicky Wahyudi;Yana Aditia Gerhana;Aldy Rialdy Atmadja

2023 IEEE 9th International Conference on Computing, Engineering and Design (ICCED)

Year: 2023 | Conference Paper |

Finger movement pattern recognition method using artificial neural network based on electromyography (EMG) sensor

Mochammad Ariyanto;Wahyu Caesarendra;Khusnul A. Mustaqim;Mohamad Irfan;Jonny A. Pakpahan;Joga D. Setiawan;Andri R. Winoto

2015 International Conference on Automation, Cognitive Science, Optics, Micro Electro-Mechanical System, and Information Technology (ICACOMIT)

Year: 2015 | Conference Paper |

Cited by: Papers (45)

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In this study, the EMG signals are processed using 16 time-domain features extraction to classify the finger movement such as thumb, index, middle, ring, and little. The pattern recognition of 16 extracted features are classified using artificial neural network (ANN) with two layer feed forward network. The network utilizes a log-sigmoid transfer function in hidden layer and a hyperbolic tangent s...Show More

Finger movement pattern recognition method using artificial neural network based on electromyography (EMG) sensor

Mochammad Ariyanto;Wahyu Caesarendra;Khusnul A. Mustaqim;Mohamad Irfan;Jonny A. Pakpahan;Joga D. Setiawan;Andri R. Winoto

2015 International Conference on Automation, Cognitive Science, Optics, Micro Electro-Mechanical System, and Information Technology (ICACOMIT)

Year: 2015 | Conference Paper |

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