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Pujiono Pujiono
Fakultas Ilmu Komputer, Universitas Dian Nuswantoro Semarang
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Journal : JURTEKSI

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PREDICTING OF BREAST CANCER RISK USING MACHINE LEARNING WITH FEATURE SELECTION THROUGH XGBOOST Al Azhar, Cahya Mutiara; Pujiono, Pujiono
JURTEKSI (Jurnal Teknologi dan Sistem Informasi) Vol 11, No 2 (2025): Maret 2025
Publisher : Universitas Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i2.3661

Abstract

Abstract: Breast cancer is the leading cause of death for women globally, exacerbated by late detection. This study proposes a breast cancer risk prediction framework using XGBoost with SelectKBest feature selection. It aims to improve the accuracy and efficiency of early detection through exploratory data analysis, coding, SMOTE to address class imbalance, and feature selection (k=29). As a result, the XGBoost model achieved 98.1% accuracy, 98.1% recall, 98.1% f1-score, and 98.2% precision on test data, highlighting the importance of feature selection. These results are promising in patient prioritization (triage) for further examination, helping medical personnel identify high-risk patients, thus improving resource allocation efficiency. These findings validate SelectKBest and pave the way for the development of a machine learning-based clinical decision support system for breast cancer early detection workflows. This research contributes significantly to the application of machine learning to support early breast cancer detection.            Keywords: breast cancer; feature selection; machine learning; risk prediction; XGBOOST.  Abstrak: Kanker payudara menjadi penyebab utama kematian wanita global, diperparah deteksi yang terlambat. Penelitian ini mengusulkan kerangka prediksi risiko kanker payudara menggunakan XGBoost dengan seleksi fitur SelectKBest. Tujuannya meningkatkan akurasi dan efisiensi deteksi dini melalui analisis data eksploratif, pengkodean, SMOTE untuk mengatasi ketidakseimbangan kelas, dan seleksi fitur (k=29). Hasilnya, model XGBoost mencapai akurasi 98.1%, recall 98.1%, f1-score 98.1%, dan presisi 98.2% pada data uji, menyoroti pentingnya seleksi fitur. Hasil ini menjanjikan dalam penentuan prioritas pasien (triage) untuk pemeriksaan lebih lanjut, membantu tenaga medis mengidentifikasi pasien berisiko tinggi, sehingga meningkatkan efisiensi alokasi sumber daya. Temuan ini memvalidasi SelectKBest dan membuka jalan bagi pengembangan sistem pendukung keputusan klinis berbasis machine learning untuk alur kerja deteksi dini kanker payudara. Penelitian ini berkontribusi signifikan dalam penerapan machine learning untuk mendukung deteksi dini kanker payudara. Kata kunci: kanker payudara; pembelajaran mesin; prediksi risiko ; seleksi fitur; XGBOOST. 
PREDICTING OF BREAST CANCER RISK USING MACHINE LEARNING WITH FEATURE SELECTION THROUGH XGBOOST Al Azhar, Cahya Mutiara; Pujiono, Pujiono
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 11 No. 2 (2025): Maret 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i2.3661

Abstract

Abstract: Breast cancer is the leading cause of death for women globally, exacerbated by late detection. This study proposes a breast cancer risk prediction framework using XGBoost with SelectKBest feature selection. It aims to improve the accuracy and efficiency of early detection through exploratory data analysis, coding, SMOTE to address class imbalance, and feature selection (k=29). As a result, the XGBoost model achieved 98.1% accuracy, 98.1% recall, 98.1% f1-score, and 98.2% precision on test data, highlighting the importance of feature selection. These results are promising in patient prioritization (triage) for further examination, helping medical personnel identify high-risk patients, thus improving resource allocation efficiency. These findings validate SelectKBest and pave the way for the development of a machine learning-based clinical decision support system for breast cancer early detection workflows. This research contributes significantly to the application of machine learning to support early breast cancer detection.            Keywords: breast cancer; feature selection; machine learning; risk prediction; XGBOOST.  Abstrak: Kanker payudara menjadi penyebab utama kematian wanita global, diperparah deteksi yang terlambat. Penelitian ini mengusulkan kerangka prediksi risiko kanker payudara menggunakan XGBoost dengan seleksi fitur SelectKBest. Tujuannya meningkatkan akurasi dan efisiensi deteksi dini melalui analisis data eksploratif, pengkodean, SMOTE untuk mengatasi ketidakseimbangan kelas, dan seleksi fitur (k=29). Hasilnya, model XGBoost mencapai akurasi 98.1%, recall 98.1%, f1-score 98.1%, dan presisi 98.2% pada data uji, menyoroti pentingnya seleksi fitur. Hasil ini menjanjikan dalam penentuan prioritas pasien (triage) untuk pemeriksaan lebih lanjut, membantu tenaga medis mengidentifikasi pasien berisiko tinggi, sehingga meningkatkan efisiensi alokasi sumber daya. Temuan ini memvalidasi SelectKBest dan membuka jalan bagi pengembangan sistem pendukung keputusan klinis berbasis machine learning untuk alur kerja deteksi dini kanker payudara. Penelitian ini berkontribusi signifikan dalam penerapan machine learning untuk mendukung deteksi dini kanker payudara. Kata kunci: kanker payudara; pembelajaran mesin; prediksi risiko ; seleksi fitur; XGBOOST. 
Co-Authors A.A. Ketut Agung Cahyawan W Abulebu, Henny I. Adhe Irham Thoriq Affandy Affandy Ahmad Zainul Fanani Aini, Triska Rahmatul Aisyaturrahmi Al Azhar, Cahya Mutiara Alik Katur Rofiah, Binti Alwani, Alwani Amin, Amirudin M Amiruddin , Amiruddin Andresen, Wily Andry Setiawan, Andry Anggun Pambudi Anton Anton Anugroho, Rohmat Aprila, Bord Nandre Arif Hidayat Arif Widagdo Asih Rohmani B. Pakpahan, Irnovia Bayu, Yoni Setyo Nugroho Budi Haryanto Budiono Budiono Busriyanti Busriyanti, Busriyanti Cantika Sari Siregar Catur Supriyanto Chamdan, Umar Chandra, Jennifer Chusnia, Vina Maulidah David S. V. L Bangguna Dedi Dedi Dewi Sulistianingsih Diah Restu Wardani Diah Restu Wardani Dian Anita Nuswantara Dianwicaksih Arieftiara E. Wuon, Orva Edi Noersasongko Eka Putri, Libryawati Eko Prasetyo Elanda Fikri Eni Wuryani Estu, Ahmad Zulkarnaen Estu, Ahmad Zulkarnain Eti Rimawati Etika Kartikadarma Fadhil, Azhar Fadrul, Fadrul Fadzil, Rozlinda Mohamed Fahmi Amiq Fatihul Barokah Firdaus, Gilbert Fitriya, Vina Syayidatul Fitriyani Fitriyani Fransisca, Luciana Fredy Susanto Freza Surya Asrina Friska, Yuni Guruh Fajar Shidik Hadi, Syukri Hariyati Hariyati Harry Patuan Panjaitan Haryati Haryati Herdhianta, Dhimas Heri Susanto Hernawan Hadi Heru Agus Santoso Hidayat, Rendra Syarief Holmes Rolandy Kapuy Ibad, Sholihul Iin Purnamasari Imam Bukori Indriani, Azizah Defi Irianti, Lingga Resvita Irma Cahyaningtyas, Irma Istiyanti, Istiyanti Ita Mowidu Iwan Hermawan Junaidi Junaidi Jutono Gondohanindijo, Jutono Kahar Kahar, Kahar Kasman Kasman Khoirul Anwar Kusharyanti Kusharyanti Lazuardi, Afried Lintang Venusita Lubis, Lubis Bambang Purnama M. Anwar Sadat M. Tangkeallo, Marthen Made Dudy Satyawan Mahazam Afrad Marita Marita, Marita Martitah Martitah Merlyana Dwinda Yanthi Mimelientesa Irman Moch Arief Soeleman Moch Arief Soeleman, Moch Arief Moch. Eko Rustiyono Mubarok, Ahmad Hasan Muchammad Shidqon Prabowo Muhamad Haris Zuhri Muhtarom Muljono Muljono Muljono, - Mursalim Mustajab Mustajab Nanik Prasetyoningsih Nasution, Khairina Ni Nyoman Alit Triani Nofriza, Eri Noor Ageng Setiyanto, Noor Ageng Nova Rijati Novida, Irma Novitriansyah, Bob Nurhayati Sitorus Nurhayati, Ati Nurtantio, Pulung NURUL HIDAYAH O. Pandoyu, Ebelhart Onny Setyawan Pandoyu, Ebelhart O Pandoyu, Ebelhart O. prabawa, randy aditya Pramana, Hendri Julian Pramitasari, Ratih Pratama, Arfian Nanda Yogi Pulung Nurtantio Andono Purwanto Purwanto Purwanto Purwanto Putra, S.E., MSA, Rediyanto Putra, Tegar Islami Putri, Yeni Nor Diana Putro, Bagus Prindo Sugihartono R Arief Nugroho Rahman, Fathor Rahman, Sarli Rangkuti, Rahmadsyah Ravindo, Besky Pramudya Rediyanto Putra Refky Fielnanda Rendra Arief Hidayat Retno Sunu Astuti Ridha Rahmawati Rini Fidiyani ROHMAWATI KUSUMANINGTIAS Romi Ilham, Romi Roy Aprianto, Roy Rusilawati, Ermina Sahbar, Robi Sahninda, Berian Putra Saputra, Aries Gilang Sari Ayu Wulandari Septian Enggar Sukmana Setiawan, Dicky Sifai, Izzatul Alifah Siti Muslifah, Siti Slamet Sumarto Soeleman, Arief Soeleman, M Arief Solichul Huda Somad, Agus Sri Astuti Sri Slamet Mulyati, Sri Slamet Sudarto Usuli SUGIARTO, LAGA Sugiarto, Triga Agus Sugito - Suharnawi Suharnawi Suharnawi Suharyanto Swanto, Dominicus Josephus Syahputra, Hidayat Syaiful A. Septemuryantoro Tang, Wilson Tangkeallo, Marthen M. Teguh Budi Prijanto, Teguh Budi Ujang Nurjaman, Ujang Ulum, Nafi' Fahrur Wacana, Gitit I.P Wahyu Adi Nugroho Wahyudi, Payzar Wicaksono, Duta Firdaus Widianto, Dhoni WIJAYANTO WIJAYANTO Wuryantoro, Tri Yetri Hasan Yolanda, Oppie Yudistira, Ivan Bhakti Yuli Prasetyo Adhi Yuliana, Dhea Arsinta Yundari, Yundari Yusrizal Yusrizal