Jurnal
Integrating C4.5 and K-Nearest Neighbor Imputation with Relief Feature Selection for Enhancing Breast Cancer Diagnosis
Scientific Journal of Informatics · Vol. 12 No. 1 (2025) · hlm. 107–118
- ISSN
- 2407-7658, 2460-0040
- Terbit
- 2025-05-29
- Penerbit
- Universitas Negeri Semarang
- Bahasa
- eng
Abstrak
Purpose: Breast cancer remains a significant cause of mortality among women, requiring accurate diagnostic methods. Traditional classification models often face accuracy challenges due to missing values and irrelevant features. This investigation advances the classification of breast cancer through the amalgamation of the C4.5 algorithm with K-Nearest Neighbor (KNN) imputation and Relief feature selection methodologies, thereby augmenting data integrity and enhancing classification efficacy. Methods: The Wisconsin Breast Cancer Database (WBCD) was the core reference for evaluating the proposed methodology. KNN imputation addressed missing values, while Relief selected the most relevant features. The C4.5 algorithm executed training by utilizing data segregations in the corresponding proportions of 70:30, 80:20, and 90:10, with its efficiency gauged through a range of metrics, particularly accuracy, precision, recall, and F1-score. Result: This innovative methodology achieved the highest classification accuracy of 98.57%, surpassing several existing models. Particularly noteworthy, the strategy being analyzed exhibited remarkable success relative to PSO-C4.5 (96.49%), EBL-RBFNN (98.40%), Gaussian Naïve Bayes (97.50%), and t-SNE (98.20%), demonstrating associated advancements of 2.08%, 0.17%, 1.07%, and 0.37%. These results confirm its effectiveness in handling missing values and selecting relevant features. Novelty: Unlike prior studies that addressed missing values and feature selection separately, this research integrates both techniques, enhancing classification accuracy and computational efficiency. The findings suggest that this approach provides a reliable breast cancer diagnosis method. Future work could explore deep learning integration and validation on larger datasets to improve generalizability.
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40 penulis · 202 tautan kepenulisan bersama · 5 lintas organisasi · menampilkan 40 yang paling banyak terhubung
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- State University of Semarang
- Universitas Nahdlatul Ulama Blitar
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- Organisasi berbeda
- Organisasi sama
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Tampilkan sebagai tabel
| Rekan penulis | Organisasi | Artikel bersama |
|---|---|---|
| Parmin Parmin | State University of Semarang | 8 |
| Melissa Salma Darmawan | State University of Semarang | 8 |
| Ani Rusilowati | State University of Semarang | 8 |
| Novi Ratna Dewi | State University of Semarang | 7 |
| Muhamad Taufiq | State University of Semarang | 6 |
| Isa Akhlis | State University of Semarang | 6 |
| Ellianawati Ellianawati | State University of Semarang | 5 |
| Indah Urwatin Wusqo | State University of Semarang | 5 |
| Fidia Fibriana | State University of Semarang | 4 |
| Dyah Rini Indriyanti | State University of Semarang | 4 |
| Woro Sumarni | State University of Semarang | 4 |
| Sugianto Sugianto | Universitas Nahdlatul Ulama Blitar | 4 |
| Arka Yanitama | State University of Semarang | 3 |
| Stephani Diah Pamelasari | State University of Semarang | 3 |
| Septiko Aji | Afiliasi tidak diketahui | 3 |
| Tiara Dwi Wulandari | Afiliasi tidak diketahui | 3 |
| Siti Wahyuni | Afiliasi tidak diketahui | 3 |
| Wiyanto Wiyanto | State University of Semarang | 3 |
| Saiful Ridlo | State University of Semarang | 3 |
| Aditya Marianti | Afiliasi tidak diketahui | 3 |
| Hari Wibawanto | State University of Semarang | 3 |
| Agung Laksono | Afiliasi tidak diketahui | 3 |
| Wiwi Isnaeni | State University of Semarang | 3 |
| Miranita Khusniati | State University of Semarang | 2 |
| Siti Alimah | State University of Semarang | 2 |
| Alfiana Nur Rosita Mayanti | Afiliasi tidak diketahui | 2 |
| Bambang Subali | Afiliasi tidak diketahui | 2 |
| Siti Nursulistari | Afiliasi tidak diketahui | 2 |
| Nadia Eka Ardhani | Afiliasi tidak diketahui | 2 |
| Sugiyanto Sugiyanto | Afiliasi tidak diketahui | 2 |
| Aji Saputra | Afiliasi tidak diketahui | 2 |
| Alamsyah Alamsyah | State University of Semarang | 2 |
| Retno Sri Iswari | State University of Semarang | 2 |
| Riza Arifudin | State University of Semarang | 2 |
| Sigit Saptono | State University of Semarang | 2 |
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