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All Journal ILMU USHULUDDIN Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Speed - Sentra Penelitian Engineering dan Edukasi JUITA : Jurnal Informatika CESS (Journal of Computer Engineering, System and Science) InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Jurnal Informatika Swabumi (Suara Wawasan Sukabumi) : Ilmu Komputer, Manajemen, dan Sosial IJCIT (Indonesian Journal on Computer and Information Technology) Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Jurnal Pilar Nusa Mandiri Jurnal Biologi Tropis ILKOM Jurnal Ilmiah FIKRAH Jurnal Teknologi dan Informasi MULTINETICS INTI Nusa Mandiri Dedikasi: Jurnal Pengabdian Masyarakat JUDICIOUS: Journal of Management Computer Science (CO-SCIENCE) Jurnal Pemikiran Islam (JPI) Simpatik: Jurnal sistem Informasi dan Informatika J-Intech (Journal of Information and Technology) Smart: Journal of Sharia, Tradition, and Modernity Jurnal Studi Sosial Keagamaan Syekh Nurjati Akademika : Jurnal Pemikiran Islam Jurnal Fuaduna: Jurnal Kajian Keagamaan dan Kemasyarakatan Jurnal Pengabdian Masyarakat Bhinneka Ladang Artikel Ilmu Komputer Journal of Accounting Information System Nuansa Informatika El-Mujtama: Jurnal Pengabdian Masyarakat EDUKASI EMPIRISMA: JURNAL PEMIKIRAN DAN KEBUDAYAAN ISLAM Edukasia Islamika: Jurnal Pendidikan Islam Hawa : Jurnal Pemberdayaan Dan Pengabdian Masyarakat (HAWAJPPM) Al-madinah: Journal of Islamic Civilization Fikrah : Jurnal Pendidikan Agama Islam
Taufik Hidayatulloh
Universitas Bina Sarana Informatika
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Journal : Computer Science (CO-SCIENCE)

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Analisis Performa Model ResNet-50 Pada Diagnosis Pneumonia Balita Berdasarkan Citra Radiografi Thorax Rahmawati, Ami; Yulianti, Ita; Nurajizah, Siti; Hidayatulloh, Taufik; Sari, Ani Oktarini
Computer Science (CO-SCIENCE) Vol. 5 No. 1 (2025): Januari 2025
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v5i1.7618

Abstract

One of the most serious complications of ARI is pneumonia, where this disease causes sufferers to experience pain when breathing and limited oxygen intake. According to the World Health Organization (WHO), pneumonia is classified as a life-threatening disease due to the high mortality rate caused. To be able to diagnose this disease, patients usually undergo various medical examination methods, one of which is through chest radiography. However, the challenge in diagnosing pneumonia generally lies in the complexity and uncertainty in interpreting the results of these methods. Therefore, this study was conducted with the aim of building an image classification model based on the Chest radiography dataset from toddler patients using the ResNet-50 architecture, which is a variant of the Convolutional Neural Networks (CNN) algorithm. The combination of the two methods is applied to analyze and process images and obtain pattern recognition with high accuracy. The research methods used include the application of data augmentation, CNN architecture design, model training, and performance evaluation. The evaluation results show that the model has quite good performance with an accuracy of 85%, which indicates the model's ability to classify images with a fairly high level of accuracy, and has the potential to help the pneumonia diagnosis process more efficiently and accurately.
Analisis Performa Model ResNet-50 Pada Diagnosis Pneumonia Balita Berdasarkan Citra Radiografi Thorax Rahmawati, Ami; Yulianti, Ita; Nurajizah, Siti; Hidayatulloh, Taufik; Sari, Ani Oktarini
Computer Science (CO-SCIENCE) Vol. 5 No. 1 (2025): Januari 2025
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v5i1.7618

Abstract

One of the most serious complications of ARI is pneumonia, where this disease causes sufferers to experience pain when breathing and limited oxygen intake. According to the World Health Organization (WHO), pneumonia is classified as a life-threatening disease due to the high mortality rate caused. To be able to diagnose this disease, patients usually undergo various medical examination methods, one of which is through chest radiography. However, the challenge in diagnosing pneumonia generally lies in the complexity and uncertainty in interpreting the results of these methods. Therefore, this study was conducted with the aim of building an image classification model based on the Chest radiography dataset from toddler patients using the ResNet-50 architecture, which is a variant of the Convolutional Neural Networks (CNN) algorithm. The combination of the two methods is applied to analyze and process images and obtain pattern recognition with high accuracy. The research methods used include the application of data augmentation, CNN architecture design, model training, and performance evaluation. The evaluation results show that the model has quite good performance with an accuracy of 85%, which indicates the model's ability to classify images with a fairly high level of accuracy, and has the potential to help the pneumonia diagnosis process more efficiently and accurately.
Co-Authors A.Gunawan Aan Rukmana Abdillah Abdillah Ahmad Fauzi Akrom, Akrom Andhika Putra Munggaran ANI OKTARINI SARI, ANI OKTARINI Anisa Fajria Arif Purnama Arif, Ridwan Asti Herliana, Asti Aziizil Fauzia bin Mohd Noor, Khairunnizam Clare Harvey Daniel Ratag Dasya Arif Firmansyah Dede Wintana Desi Susilawati - AMIK BSI Sukabumi Dinar Ismunandar Dini Nurlaela Dwi Rahma, Indira Dzulfaqor, Arul Fadyah Ernawati Eva Marsusanti Fadhilah, Ulfah Nur Febrian, Rojja Fuad Mahbub Siraj Fuad Nur Hasan Gunawan Gunawan Gunawan Hajam Hajam, Hajam Hartin Kurniawati Hasan, Fuad Nur Ika Rahayu Satyaninrum Iklima Iklima Indra Aditya Prayoga Isep Djuanda Ita Yulianti Ita Yulianti Jabang Nurdin Jasisca Marleftan Kamarzaman, Mohd Haidhar Lestari Yusuf Lila Dini Utami Lis Saumi Ramdhani Lisnawati Dewi, Lisnawati Miftah Farid Adiwisastra Mohamad Syarif Sumantri Munawaroh, Fitri Mustika Madliah Mustika Dewi Muttaqien Neng Sella Zakiatun Nufus Neng Senja Nekida Nofrita Nofrita Nugraha, Setyo Bagus Nuri Aslami Nursyifa, Eva Pirim Setiarso Pribadi, Denny Purwaningtias, Deasy Rabathy, Qisthy Rahmawati, Ami Rida Nutria Lestari Rifa Nurafifah Syabaniah Rifai, Pipip A. Risdiansyah, Deni Rival Afrian Rizal Amegia Saputra Rusda Wajhillah Saeful Bahri Saeful Bahri Saputra, Alfian Ady Satia Suhada, Satia Saumantri, Theguh Siskawati Siskawati Siti Fatimah Siti Nurajizah Sunaryo Sunaryo Syifa, Bahro Theguh Saumantri Toni Arifin Tya Septiani Nurfauzia Koeswara Utami, Dian Tri Veithzal Rivai Zainal Wahyu Nugraha Wahyudi Akmaliah, Wahyudi Wijaya Kusuma, Ceeptadi Winardi, Ardi Winda Nidya Putri Fitriana Yenni Yunita Yulhan Wahyudin Yusti Farlina Zulmi Ramdani