Deteksi Kanker Paru Paru Berbasis Mobile: Integrasi Machine Learning dalam Aplikasi Nusaminer
DOI:
https://doi.org/10.24114/cess.v11i1.69023Keywords:
Kangker Paru Paru, Klasifikasi, Prediksi, Data Mining, machine learningAbstract
Deteksi dini kanker paru-paru sangat penting untuk meningkatkan peluang kesembuhan. Penelitian ini membandingkan performa sembilan algoritma klasifikasi (AdaBoost, ANN, Decision Tree, Gradient Boosting, KNN, Logistic Regression, Naïve Bayes, Random Forest, dan SVM) menggunakan RapidMiner dan NusaMiner. Dataset berasal dari Kaggle dengan 309 data pasien dan 16 atribut terkait faktor risiko serta gejala klinis. Evaluasi dilakukan berdasarkan akurasi, precision, recall, F1-score, dan AUC pada rasio 70:30, 80:20, dan 90:10. Hasil menunjukkan NusaMiner memberikan akurasi lebih tinggi dan stabil dibanding RapidMiner. Algoritma Gradient Boosting dan Random Forest mencapai akurasi 100% pada beberapa rasio, sementara Naïve Bayes menunjukkan akurasi terendah di RapidMiner. Temuan ini menegaskan pentingnya pemilihan algoritma dan platform dalam meningkatkan efektivitas sistem deteksi kanker paru-paru berbasis machine learning.Downloads
References
[1] World Health Organization, “Prees Release No.345: Global cancer burden growing, amidst mounting need for services,” Int. Agency Res. Cancer, no. 345, pp. 185–187, 2024, [Online]. Available: https://www.who.int/news/item/01-02-2024-global-cancer-burden-growing--amidst-mounting-need-for-services%0Ahttps://www.iarc.who.int/wp-content/uploads/2024/02/pr345_E.pdf
[2] J. Ferlay et al., “Cancer statistics for the year 2020: An overview,” Int. J. Cancer, vol. 149, no. 4, pp. 778–789, 2021, doi: 10.1002/ijc.33588.
[3] R. Kementerian Kesehatan, “Komite Penanggulangan Kanker Nasional,” Pandu. Penatlaksanaan Kanker Serviks, pp. 10–11, 2016.
[4] S. Rahmaeda and R. Prathivi, “Komparasi Metode SVM dan Logistic Regression untuk Klasifikasi Hipotesa Penyakit Kanker Paru Paru Berdasarkan Gejala Awal,” Kesatria J. Penerapan Sist. Inf. (Komputer dan Manajemen), vol. 6, no. 1, pp. 210–218, 2025, doi: 10.30645/kesatria.v6i1.562.
[5] A. Naseh Khudori and M. Syauqi Haris, “Implementasi Decision tree Untuk Prediksi Kanker Paru-Paru,” J. Ris. Sist. Inf. Dan Tek. Inform. (JURASIK, vol. 9, no. 1, pp. 94–106, 2024, [Online]. Available: https://tunasbangsa.ac.id/ejurnal/index.php/jurasik
[6] D. Widyawati and A. Faradibah, “Comparison Analysis of Classification Model Performance in Lung Cancer Prediction Using Decision Tree, Naive Bayes, and Support Vector Machine,” Indones. J. Data Sci., vol. 4, no. 2, pp. 80–89, 2023, doi: 10.56705/ijodas.v4i2.76.
[7] H. М. Alieksieieva, V. Н. Khomenko, and V. V. Khomenko, “the Role of Artificial Intelligence in Enhancing Online Learning,” Innov. Pedagog., vol. 2, no. 63, pp. 172–175, 2023, doi: 10.32782/2663-6085/2023/63.2.36.
[8] S. Farshchiha, S. Asoudeh, M. S. Kuhshuri, M. Eisaeid, M. Azadie, and S. Hesaraki, “A Comprehensive Analysis on Machine Learning based Methods for Lung Cancer Level Classification,” 2025.
[9] M. Jasmine Pemeena Priyadarsini et al., “Lung Diseases Detection Using Various Deep Learning Algorithms,” J. Healthc. Eng., vol. 2023, 2023, doi: 10.1155/2023/3563696.
[10] B. Andriska, C. Permana, and M. Djamaluddin, “Penerapan Python Dalam Data Mining Untuk Prediksi Kangker Paru Organisasi Kesehatan Dunia ( WHO ) menyatakan bahwa kangker merupakan kelompok penyakit yang berasal dari hampir seluruh organ tubuh dimana sel-sel yang terdapat pada organ tubuh tersebut tumb,” vol. 6, no. 2, 2023.
[11] L. Sari, A. Romadloni, and R. Listyaningrum, “Penerapan Data Mining dalam Analisis Prediksi Kanker Paru Menggunakan Algoritma Random Forest,” Infotekmesin, vol. 14, no. 1, pp. 155–162, 2023, doi: 10.35970/infotekmesin.v14i1.1751.
[12] and B. I. National Heart, Lung, “Lungs,” U.S. Department of Health and Human Services.
[13] Y. E. Sembiring et al., “Lung Cancer: A Literature Review,” J. Respirasi, vol. 9, no. 3, pp. 246–251, 2023, doi: 10.20473/jr.v9-i.3.2023.246-251.
[14] S. Firyal Nabila, D. Setiawan Hendyca Putra, S. Farlinda, E. Tri Ardianto, J. Kesehatan, and P. Negeri Jember, “J-REMI : Jurnal Rekam Medik Dan Informasi Kesehatan Analisis Faktor Risiko Pada Penyakit Karsinoma Paru (C34) Pasien Rawat Inap di Rumah Sakit Baladhika Husada Jember,” vol. 2, no. 2, pp. 244–254, 2021.
[15] aici-umg.com, “Pengertian AI: Definisi dan Konsep Utama,” aici-umg.com. [Online]. Available: https://aici-umg.com/article/pengertian-ai-definisi-dan-konsep-utama/?utm_source=chatgpt.com
[16] T. Wahyudi, “Studi Kasus Pengembangan dan Penggunaan Artificial Intelligence (AI) Sebagai Penunjang Kegiatan Masyarakat Indonesia,” Indones. J. Softw. Eng., vol. 9, no. 1, pp. 28–32, 2023, [Online]. Available: https://ejournal.bsi.ac.id/ejurnal/index.php/ijse
[17] E. S. Eriana, “Artificial Intelligence – AI,” Encycl. Digit. Agric. Technol., pp. 84–84, 2023, doi: 10.1007/978-3-031-24861-0_300007.
[18] V. Goar and N. S. Yadav, “Foundations of machine learning,” Intell. Optim. Tech. Bus. Anal., no. Ml, pp. 25–48, 2024, doi: 10.4018/979-8-3693-1598-9.ch002.
[19] X. Shu and Y. Ye, “Knowledge Discovery: Methods from data mining and machine learning,” Soc. Sci. Res., vol. 110, no. April 2022, p. 102817, 2023, doi: 10.1016/j.ssresearch.2022.102817.
[20] C. A. Palacios, J. A. Reyes-Suárez, L. A. Bearzotti, V. Leiva, and C. Marchant, “Knowledge discovery for higher education student retention based on data mining: Machine learning algorithms and case study in chile,” Entropy, vol. 23, no. 4, pp. 1–23, 2021, doi: 10.3390/e23040485.
[21] J. Han, M. Kamber, and J. Pei, Data Mining : Concepts and Techniques : Concepts and Techniques (3rd Edition). Morgan Kaufmann, 2012.
[22] V. Çetin and O. Yıldız, “A comprehensive review on data preprocessing techniques in data analysis,” Pamukkale Univ. J. Eng. Sci., vol. 28, no. 2, pp. 299–312, 2022, doi: 10.5505/pajes.2021.62687.
[23] Y. Liu, V. Stein Dani, I. Beerepoot, and X. Lu, “Turning Logs into Lumber: Preprocessing Tasks in Process Mining,” Lect. Notes Bus. Inf. Process., vol. 503 LNBIP, pp. 98–109, 2024, doi: 10.1007/978-3-031-56107-8_8.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 CESS (Journal of Computer Engineering, System and Science)
This work is licensed under a Creative Commons Attribution 4.0 International License.
