Article Per Year (5 Year)
p-Index From 2021 - 2026
3.601
P-Index
This Author published in this journals
All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JMM (Jurnal Masyarakat Mandiri) JURNAL PENDIDIKAN TAMBUSAI EDUMATIC: Jurnal Pendidikan Informatika JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Bulletin of Computer Science Research Brilliance: Research of Artificial Intelligence Pelita Teknologi : Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB Bulletin of Data Science Nautical: Jurnal Ilmiah Multidisiplin Indonesia Jurnal Pengabdian Mandiri Proceeding International Pelita Bangsa GLOBAL: Jurnal Lentera BITEP Jurnal Pelita Pengabdian Journal of Renewable Engineering
Amali, Amali
Unknown Affiliation
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

Published : 25 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Bulletin of Computer Science Research

 1 
Analisis Komparatif Decision Tree C4.5 dan Neural Network pada Prediksi Kanker Payudara Amali, Amali; Widodo, Edy
Bulletin of Computer Science Research Vol. 4 No. 5 (2024): August 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v4i5.295

Abstract

Breast cancer is one of the diseases with the highest incidence and mortality rates among women, requiring methods that can support fast and accurate detection. This study aims to compare the performance of the Decision Tree C4.5 and Neural Network algorithms in breast cancer classification using the Breast Cancer Wisconsin dataset obtained from the UCI Machine Learning Repository. The research method adopts the CRISP-DM approach, which includes data collection, preprocessing, model development, testing, and evaluation stages. The preprocessing stage was carried out through data cleaning, data transformation, and data reduction to improve dataset quality before the modeling process. The testing process used split validation and evaluation based on accuracy, precision, recall, and Area Under Curve (AUC) metrics. The results indicate that the Neural Network algorithm achieved better performance than Decision Tree C4.5. Neural Network obtained an accuracy of 96.17%, precision of 95.80%, recall of 96.50%, and an AUC value of 0.989, which is categorized as excellent classification. Meanwhile, Decision Tree C4.5 achieved an accuracy of 93.50% and an AUC value of 0.945, categorized as very good classification. ROC Curve analysis demonstrates that Neural Network is more effective in distinguishing benign and malignant classes. Therefore, Neural Network is recommended as the best model to support early breast cancer detection based on machine learning, while Decision Tree C4.5 remains relevant for conditions requiring simpler and more interpretable models.
Co-Authors Al Ayubi, Muhammad Din Andri Firmansyah Andriani Andriani Andriano, Choky Angela, Devani Nadia Vita Kusuma Anggraini, Ariska Nur Anshory, Ahmad Shofwan Antika Zahrotul Kamalia Anwar, Muhammad Syaibani ARIF SUSILO Aswan Supriyadi Sunge Badruzzaman, Aceng Bintang Satria, Yusuf Putra Budiarto, Eko Budiman, Banyu Sugara Butsianto, Sufajar DHANI ARIATMANTO Edy Widodo Edy Widodo Fahmi, Alif Gunawan, Achmad Rezky Hamidah, Jilan Herfiansyah, Raihan Hidayah, Aldy Imawan, Alifia Putri Ismamudi Ismamudi Ismamudi, Ismamudi Kurniasih, Nabila Kurniawan, Jidan Restu Listyanto, Rudy Effendy Maulana, Donny Muhammad Rifa'i, Anggi Muhtajuddin Danny Nawangsih, Ismasari Noor, Viyan Qomarudin Nugroho, Agung Nurhidayanti, Nisa Permana, Yudi Pikriyansyah, Ridho Pratama, Alvian Saputra Pratama, Fauzhan Qhof Priyo, Basuki Edi Putra, Maha Ramadan, Fadli Ramadhan, Arya Syah Ramadhan, Zidan Lutfi Rifa'i, Anggi Muhammad Saepul, Muhammad Saniyah, Luzzatus Saputra, Muhamad Ariel Satpatmantyo, Kurbandi Septianto, Riski Suryadi Suryadi Tasya, Amalia Taufiq Rachman, Taufiq Tedi, Nanang Turmudi Zy, Ahmad Tyas Ismi Trialfhianty Wangsadanureja, Miftah Wibowo, Mohamad Hegar Sukmana Wiyanto -