Enhancing Lung Cancer Prediction Accuracy UsingQuantum-Enhanced K-Medoids with Manhattan Distance
DOI:
https://doi.org/10.30812/matrik.v24i3.4190Keywords:
Clustering, data mining, K-Medoids, Manhattan Distance, Quantum Bit, Quantum ComputingAbstract
Lung cancer is a leading cause of cancer-related deaths worldwide, and early detection plays a crucial
role in improving treatment outcomes. This study proposes an enhancement of the K-Medoids clustering
method by integrating a quantum computing approach using Manhattan distance to improve
prediction accuracy for lung cancer diagnosis. The research was conducted using a publicly available
lung cancer dataset consisting of 309 patient records with 14 diagnostic attributes. Comparative experiments
were carried out between the classical K-Medoids and the quantum-enhanced K-Medoids, with
performance evaluated based on clustering accuracy, precision, recall, and F1-score. The results show
that the quantum-based method has the same accuracy as the classical method, namely 88%. This
suggests that quantum-based clustering can match the accuracy of classical methods after adequate
training, although consistency and parameter stability remain areas for further refinement. Further
research is recommended to test the model on larger datasets and to explore real-world deployment in
clinical decision support systems.
Downloads
References
[1] Y.-M. Li, H.-L. Liu, S.-J. Pan, S.-J. Qin, F. Gao, D.-X. Sun, and Q.-Y. Wen, “Quantum k -medoids algorithm using parallel
amplitude estimation,” Physical Review A, vol. 107, no. 2, p. 022421, Feb. 2023, https://doi.org/10.1103/PhysRevA.107.022421.
[2] N. Gao, D. Li, A. Mishra, J. Yan, K. Simonov, and G. Chiribella, “Measuring Incompatibility and Clustering Quantum Ob-servables with a Quantum Switch,” Physical Review Letters, vol. 130, no. 17, p. 170201, Apr. 2023, https://doi.org/10.1103/
PhysRevLett.130.170201.
[3] K. Hulliyah and S. Solikhun, “Q-Madaline: Madaline Based On Qubit,” Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi),
vol. 7, no. 5, pp. 1003–1008, Aug. 2023, https://doi.org/10.29207/resti.v7i5.5080.
[4] J. L. Pereira, L. Banchi, and S. Pirandola, “Quantum-Enhanced Cluster Detection in Physical Images,” Physical Review Applied,
vol. 19, no. 5, p. 054031, May 2023, https://doi.org/10.1103/PhysRevApplied.19.054031.
[5] N. Piatkowski, T. Gerlach, R. Hugues, R. Sifa, C. Bauckhage, and F. Barbaresco, “Towards Bundle Adjustment for Satellite
Imaging via Quantum Machine Learning,” in 2022 25th International Conference on Information Fusion (FUSION).
Link¨oping, Sweden: IEEE, Jul. 2022, pp. 1–8, https://doi.org/10.23919/FUSION49751.2022.9841388.
[6] L. Zahrotun, U. Linarti, B. H. T. Suandi As, H. Kurnia, and L. Y. Sabila, “Comparison of K-Medoids Method and Analytical
Hierarchy Clustering on Students’ Data Grouping,” JOIV : International Journal on Informatics Visualization, vol. 7, no. 2, p.
446, May 2023, https://doi.org/10.30630/joiv.7.2.1204.
[7] S. Al-Otaibi, V. Cherappa, T. Thangarajan, R. Shanmugam, P. Ananth, and S. Arulswamy, “Hybrid K-Medoids with Energy-
Efficient Sunflower Optimization Algorithm for Wireless Sensor Networks,” Sustainability, vol. 15, no. 7, p. 5759, Mar. 2023,
https://doi.org/10.3390/su15075759.
[8] F. Faisal, L. A. G. Giopani, M. F. Fitriah, Z. C. D. Dwynne, S. S. H. Helma, and M. Mustakim, “Perbandingan Algoritma
K-Means dan K-Medoids Untuk Pengelompokan Suhu di Provinsi Riau: Comparison of K-Means and K-Medoids Algorithms
for Temperature Grouping in Riau Province,” Indonesian Journal of Informatic Research and Software Engineering (IJIRSE),
vol. 2, no. 2, pp. 128–134, Sep. 2022, https://doi.org/10.57152/ijirse.v2i2.434.
[9] S. Samudi, S.Widodo, and H. Brawijaya, “The K-Medoids Clustering Method for Learning Applications during the COVID-19
Pandemic,” SinkrOn, vol. 5, no. 1, p. 116, Oct. 2020, https://doi.org/10.33395/sinkron.v5i1.10649.
[10] Z.Wu, L. Jin, J. Zhao, L. Jing, and L. Chen, “Research on Segmenting E-Commerce Customer through an Improved K-Medoids
Clustering Algorithm,” Computational Intelligence and Neuroscience, vol. 2022, pp. 1–10, Jun. 2022, https://doi.org/10.1155/
2022/9930613.
[11] Mustakim, M. Z. Fauzi, Mustafa, A. Abdullah, and Rohayati, “Clustering of Public Opinion on Natural Disasters in Indonesia
Using DBSCAN and K-Medoids Algorithms,” Journal of Physics: Conference Series, vol. 1783, no. 1, p. 012016, Feb. 2021,
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Solikhun Solikhun, Lise Pujiastuti, Mochamad Wahyudi
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
How to Cite
Similar Articles
- Kiki Rizki, Ahmat Adil, Implementasi Google Maps Api Berbasis Android untuk Lokasi Fasilitas Umum di Kabupaten Sumbawa , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 17 No. 2 (2018)
- Cherfly Kaope, Yoga Pristyanto, The Effect of Class Imbalance Handling on Datasets Toward Classification Algorithm Performance , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 22 No. 2 (2023)
- Dedi Setiadi, Yogi Isro Mukti, Electronic Tourism Using Decision Support Systems to Optimize the Trips , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 23 No. 1 (2023)
- M Safii, Rika Setiana, Population Prediction Using Multiple Regression and Geometry Models Based on Demographic Data , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 24 No. 1 (2024)
- Harri Gunawan, Shinta Esabella, Rancang Bangun Aplikasi Pengenalan Aat Musik Tradisional Sumbawa Berbasis Android , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 18 No. 1 (2018)
- Siti Ummi Masruroh, Andrew Fiade, Muhammad Ikhsan Tanggok, Rizka Amalia Putri, Luigi Ajeng Pratiwi, Convolutional Neural Network for Colorization of Black and White Photos , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 22 No. 2 (2023)
- Pungkas Subarkah, Penerapan Algoritme Klasifikasi Classification And Regression Trees (CART) Untuk Diagnosis Penyakit Diabetes Retinopathy , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 19 No. 2 (2020)
- Asep Syaputra, Aplikasi E-Kelurahan Untuk Peningkatan Pelayanan Administrasi dalam Mendukung Penerapan E-Government , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 20 No. 2 (2021)
- Dewa Ayu Kadek Pramita, Ni Wayan Sumartini Saraswati, I Putu Dedy Sandana, Poria Pirozmand, I Kadek Agus Bisena, Optimizing Hotel Room Occupancy Prediction Using an Enhanced Linear Regression Algorithms , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 24 No. 1 (2024)
- Husain Husain, Pulung Nurtantio Andono, M. Arif Soeleman, Perspektif Baru Enterprise Architecture Pemerintahan Kota Mataram Berbasis TOGAF ADM , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 16 No. 2 (2017)
You may also start an advanced similarity search for this article.
Most read articles by the same author(s)
- Relita Buaton, Solikhun Solikhun, Application of Numerical Measure Variations in K-Means Clustering for Grouping Data , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 23 No. 1 (2023)
- Firmansyah Firmansyah, Mochamad Wahyudi, Analisis Performa Access Control List Menggunakan Metode Firewall Policy Base , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 20 No. 2 (2021)
- Mochamad Wahyudi, Firmansyah Firmansyah, Analisis Performa Open Shortest Path First Load Balancing dengan Metode Cost Manipulation , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 21 No. 3 (2022)
.png)
