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All Journal Proceeding Fakultas Ekonomi Bulletin of Electrical Engineering and Informatics JDM (Jurnal Dinamika Manajemen) Dimas: Jurnal Pemikiran Agama untuk Pemberdayaan Students´ Journal of Accounting and Banking Students´ Journal of Economic and Management Jurnal Media Wahana Ekonomika Jurnal Ilmiah Administrasi Publik Proceeding SENDI_U El-Mashlahah Jurnal Studi Komunikasi AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat Isti`dal : Jurnal Studi Hukum Islam Fokus Ekonomi IKRA-ITH ABDIMAS Jurnal Penelitian dan Pengabdian Kepada Masyarakat UNSIQ OIKOS: Jurnal Kajian Pendidikan Ekonomi dan Ilmu Ekonomi Jesya (Jurnal Ekonomi dan Ekonomi Syariah) International Journal of Economics, Business and Accounting Research (IJEBAR) Jurnal Ekonomi Manajemen Sistem Informasi Review of Management and Entrepreneurship Khazanah Hukum Community Engagement and Emergence Journal (CEEJ) Management Studies and Entrepreneurship Journal (MSEJ) Community Development Journal: Jurnal Pengabdian Masyarakat JURNAL USM LAW REVIEW Walisongo Law Review (Walrev) Jurnal Tunas Journal of Management and Bussines (JOMB) Indonesian Journal of Law and Economics Review Journal of Management - Small and Medium Enterprises (SME's) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Economics and Digital Business Review Jurnal Ilmiah ASET Jurnal Ekonomi Jurnal Hukum Sehasen Jurnal Hukum Legalita Journal Evidence Of Law Volksgeist: Jurnal Ilmu Hukum dan Konstitusi Journal of Accounting and Finance Management (JAFM) Journal of Law, Poliitic and Humanities Journal of Public Representative and Society Provision International Journal of Multidisciplinary Sciences and Arts Jurnal Penelitian Serambi Hukum QOSIM: Jurnal Pendidikan, Sosial & Humaniora Al-Kharaj: Jurnal Ekonomi, Keuangan & Bisnis Syariah Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Journal of Research on Community Engagement Lex Scientia Law Review Jurnal Akuntansi, Ekonomi dan Manajemen Bisnis
Ali Maskur
Universitas Stikubank
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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Journal : Bulletin of Electrical Engineering and Informatics

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Enhancing skin cancer detection using transfer learning and AdaBoost: a deep learning approach Listiyono, Hersatoto; Retnowati, Retnowati; Purwatiningtyas, Purwatiningtyas; Nur Wahyudi, Eko; Maskur, Ali
Bulletin of Electrical Engineering and Informatics Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i5.10379

Abstract

Skin cancer is one of the most prevalent types of cancer worldwide, with early detection playing a critical role in improving patient outcomes. In this study, we propose a deep learning model based on LeNet-7 combined with adaptive boosting (AdaBoost) to classify skin lesions as either benign or malignant using the International Skin Imaging Collaboration (ISIC) dataset. We evaluate the proposed model alongside other well-established deep learning architectures, such as residual network (ResNet), VGGNet, and the traditional LeNet model, through various performance metrics including precision, recall, F1-score, specificity, Matthew’s correlation coefficient (MCC), area under the receiver operating characteristic curve (AUC-ROC), and testing accuracy. Our results demonstrate that the proposed model (LeNet-7+AdaBoost) significantly outperforms the other models, achieving a testing accuracy of 91.3%, precision of 0.92, recall of 0.91, and AUC-ROC of 0.93. The model successfully addresses issues of overfitting and generalization, providing a robust solution for skin cancer classification. However, some misclassifications of visually similar benign and malignant lesions highlight areas for future improvement. The proposed model shows promise in real-world medical applications and paves the way for further research into optimizing deep learning models for skin cancer detection.
Co-Authors 06.3502.0746 Ribut Hadi Handoko 0625020025 Asa Bangkit Probo Pratista 08.05.51.0061 Jefri Handiarko 08.05.51.0094 ARDI ANUGRAH UTAMA 08.05.52.0115 Candra Arta Kusuma 08.3502.0508 Nico Martiyanto Bayuaji 08.3502.0548 Ali Muhtar 10.05.52.0150 Temmy Muhas Pribadi 11.05.52.0141 Faris Febrianto, 11.05.52.0141 12.05.51.0173 Nila Ardhianie Abu Hapsin Adib Saeroji, Adib Adila, Arina Hukmu Adilla, Arina Hukmu Afif Noor Afif, Aqila-Syarief Muhammad Agung Nusantara Agus Budi Santosa Agus Budi Santosa Aisa Rurkinantia Al-Ulamai, Ulil Amri Alfina Dwi Pratiwi Almira Veda Islamey Amrillah, Mohamad Yusfi Anita Dyah Wulandari, Anita Dyah Anton Purnomo, 12.05.51.0108 Anton Purnomo, 12.05.51.0108 Arifana Nur Kholiq, Arifana Nur Askar Yunianto Asti Rahmawati Aziz, Aulia Luqman Azizah, Aini Nur Azmi, Muhammad Fazli Azzahra Ardewita Rissema, 15.05.51.0305 Bambang Sudiyatno Bambang Sudiyatno Budi, Mulyo Cahya Abim Maulana Chamami, M Rikza Choirul Saleh Dagma Syafira Destia Wardani Daniswara, Alfreda Khansa Daud Rismana Dwi Wulandari Dzaini Wardi, Ali Edi Supriyanto, Edi Eko Nur Wahyudi Endang Tjahjaningsih Euis Soliha Fauzul Munna, 15.05.51.0262 Febri Andrean, 12.05.51.0073 Febri Andrean, 12.05.51.0073 Ferdiansyah, Alif HARIYANTO HARIYANTO Hariz, Hajar Salamah Salsabila Heli Tistiana Hersatoto Listiyono Ivana Khoiru Amalia Joko Purwanto Karin Ryanda Saputri, 15.05.51.0197 Karnadi Karnadi Khofifah, Siti Khoirul Muttaqin, 14.05.51.0153 Latifah, Vika Ulfiana Lely Indah Mindarti, Lely Indah Mafazah, Nia Laelatul Maksun Maksun Mamila Hidayatullah, 14.05.51.0020 Mamila Hidayatullah, 14.05.51.0020 Marlien Marlien Marsha Nela Anggraeni, 13.05.51.0164 Marsha Nela Anggraeni, 13.05.51.0164 Maruf Maruf, Maruf Meliana Nur Azizah, Siti Merlin Nur Pratiwi, 15.05.51.0221 MIFTA MUTIARA S Mualimah, 14.05.51.0024 Muhammad Ajib Syaifuddin Muhammad Rizal Firdaus Muhshonah, Muhshonah Mulyo Budi Setiawan Muslich Shabir Mya Maulida Hurriyah, 15.05.51.0261 Nada, Tia Lutfiatun Nastiti, Putri Meila Faiza Nawatmi, Sri Nawatmi Nira Widi Pamula, 15.05.51.0090 Nisa', Khoirotin Nurreyhan, Kevin Verrell Nurul Lailatul Janah, 14.05.51.0039 Permonoputri, Rifi Maria Laila Fitri Priyo Utomo Purwaningtyas , P Purwanto Waluyo Purwatiningtyas Purwatiningtyas Purwatiningtyas, P Putri Agustin, Fatma Rafika Amalia, 14.05.51.0225 Ramadhani, Megananda Dwi Retnowati Retnowati Retnowati Retnowati Ridfan Trisnanda, 12.05.51.0122 Ridfan Trisnanda, 12.05.51.0122 Riswan Septriayadi Sianturi S Sunardi Saccidananda Octyangelin Santosa Saifudin Saifudin Sandi Putra Pratama, 14.05.51.0202 Sandi Putra Pratama, 14.05.51.0202 Santoso, Ignatius Hari Sigit Hermawan Sofiana Adhi Putri, 14.05.51.0198 Sopiyani, Sopiyani Sri Mulyani Sri Mulyani Sri Nawatmi Sri Yulianto Fajar Pradapa Sumiarsih, 15.05.51.0224 Suzy Widyasari Sya Faza Maulana, 12.05.51.0079 Sya Faza Maulana, 12.05.51.0079 Syafira Nur Hidayaturohmah Syarifa, Aulia Isnaeni Nurul Yosi Arivianto