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All Journal Jurnal Ilmiah Informatika Komputer Techno Nusa Mandiri : Journal of Computing and Information Technology
Muhammad Ilham Prasetya
Universitas Nusa Mandiri
Computer Science & IT Decision Sciences, Operations Research & Management

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COMPARATIVE CLASSIFICATION OF LUNG X-RAY IMAGES WITH CONVOLUTIONAL NEURAL NETWORK, VGG16, DENSENET121 Muhammad Ilham Prasetya; Yuris Alkhalifi; Rifki Sadikin; Yan Rianto
Techno Nusa Mandiri: Journal of Computing and Information Technology Vol 19 No 1 (2022): TECHNO Period of March 2022
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v19i1.3010

Abstract

Lungs are one of the organs of the human body, and lung tissue will ultimately affect human abilities. The respiratory system exchanges oxygen and carbon dioxide in the blood. Problems that often occur are polluted air quality, many bacteria that attack the lungs, and lung disease can cause shortness of breath, mobility difficulties, and hypoxia, so that if not detected immediately it can cause death. In this regard, the aim of this study is to compare the classification of normal lungs with those of those suffering from Cardiomegaly. The preparation of this dataset is a form of contribution in improving the quality of the disease classification system on X-ray images. CNN, VGG 16 and DenseNet methods were chosen as classification methods to ensure performance and which method is the best for classifying Lung Diseases. It can be concluded that by using the DenseNet121 model, X-Ray images in this research dataset get an accuracy of 67.06%, for the VGG16 model it gets an accuracy of 68.94% and for the CNN model it gets the highest accuracy of 80.54%.
ANALISIS PENGGUNAAN APLIKASI QUIZIZZ PADA EVALUASI PEMBELAJARAN DENGAN METODE MEDIA SYSTEM DEPENDENCY DAN TECHNOLOGY ACCEPTANCE MODEL Rian Ardianto; Muhammad Ilham Prasetya; Widya Lelisa Army; Euis Kusumarini; Emy Yunita Rahma Pratiwi
Jurnal Ilmiah Informatika Komputer Vol 27, No 2 (2022)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/ik.2022.v27i2.6797

Abstract

Quizizz  merupakan  suatu software yang  berisi  materi  pendidikan  yang disajikan dalam bentuk pembelajaran terintegrasi untuk melatih kreativitas dan meningkatkan kecerdasan siswa. Penggunaan metode Media System Dependency (MSD) dan Technology Acceptance Model (TAM) bertujuan untuk mengetahui model kerangka kerja dan domain spesifik pada keterlibatan teknologi siswa dalam konteks quizizz. Faktor yang cenderung tetap menggunakan quizizz dipengaruhi oleh persepsi tentang cenderungnya kemudahan atau kesulitan dalam belajar menggunakan quizizz sesuai dengan pengalaman belajar sebelumnya. Faktor lain yang mempengaruhi kondisi ini adalah sikap penerimaan atau penolakan ketika mendapatkan dampak dari penggunaan quizizz, jika dampaknya positif, maka dukungan orang tua terhadap siswa cenderung tetap menggunakan quizizz. Sikap publik terhadap penggunaan quizizz akan menjadi bentuk penerimaan jika dianggap quizizz mudah dimengerti. Berdasarkan hasil analisis dan penelitian, disimpulkan bahwa faktor-faktor yang mempengaruhi siswa untuk menggunakan quizizz adalah ketika sistem itu mudah dipelajari, fleksibel, mudah digunakan, dan memberikan metode pembelajaran yang unik.
Co-Authors Emy Yunita Rahma Pratiwi Euis Kusumarini Rian Ardianto Rifki Sadikin Widya Lelisa Army Yan Rianto Yuris Alkhalifi