Main Article Content

Abstract

Stroke is one of the neurological diseases that often requires complex management and treatment. Making the right decisions in diagnosing and treating stroke patients can have a significant impact on the recovery process and the quality of life for patients. To assist healthcare professionals and patients in making more informed decisions, this research has developed the "StrokeCare Navigator," a web-based Decision Support System (DSS) that utilizes the Decision Tree C4.5 algorithm. This system allows users, including healthcare professionals and patients, to input symptoms and patient medical information, providing an initial diagnosis of the type and severity of the stroke. Additionally, the system offers personalized treatment guidelines, treatment recommendations, and online patient monitoring services. The Decision Tree C4.5 model used in this system was developed through training with relevant patient data. Evaluation results indicate that the system can provide accurate and beneficial recommendations for healthcare professionals and patients. Testing and patient monitoring in clinical practice also demonstrate the potential to enhance stroke patient care. Therefore, StrokeCare Navigator is expected to be a valuable tool in stroke patient management and treatment, ultimately improving the prospects of patient recovery and providing better guidance for healthcare professionals. This research also provides deeper insights into the implementation of the Decision Tree C4.5 algorithm in the context of Decision Support Systems (DSS) in the medical field.

Keywords

Stroke disease, Decision Support System, Daily treatment, e-Health, System design.

Article Details

How to Cite
Azizah, A. H., Asmirajanti, M., & Pratama, A. (2024). Analyzing and Designing Decision Support Systems for Stroke Patient Daily Treatment. TEPIAN, 5(4), 111–118. https://doi.org/10.51967/tepian.v5i4.3186

References

  1. Adhy, Dewanto Rosian. 2021. “Rancang Bangun Sistem Prediksi Varietas Padi Yang Cocok Dengan Lahan Menggunakan Metode Data Mining Algoritma C4.5.” Saintesa 1: 28–38. https://jabarprov.go.id/index.php/pages/id/1046.
  2. Andri, Haris. 2022. “Sistem Penunjang Keputusan (SPK) Pemilihan Supplier Terbaik Dengan Metode MOORA.” Jurnal Sains Informatika Terapan 2(3): 79–84.
  3. Banik, Shouvik et al. 2022. “LSTM Based Decision Support System for Swing Trading in Stock Market.” Knowledge-Based Systems 239: 107994. https://doi.org/10.1016/j.knosys.2021.107994.
  4. Bhuiyan, Mohammad Nuruzzaman, Md Mahbubur Rahman, Md Masum Billah, and Dipanita Saha. 2021. “Internet of Things (IoT): A Review of Its Enabling Technologies in Healthcare Applications, Standards Protocols, Security, and Market Opportunities.” IEEE Internet of Things Journal 8(13): 10474–98.
  5. Citra, Puspa, I Wayan Sriyasa, and Heri Bambang Santoso. 2024. “Sistem Pendukung Keputusan Penentuan Kinerja Sales Terbaik Menggunakan Kombinasi Grey Relational Analysis Dan Pembobotan Rank Sum.” Jurnal Ilmiah Computer Science 2(2): 99–108.
  6. Duwiyanti, Fitri. 2019. “Sistem Pendukung Keputusan Pemilihan Guru Terbaik Di SMK Pustek Serpong Dengan Menggunakan Metode TOPSIS.” International Journal of Education, Science, Technology, and Engineering 2(1): 45–67.
  7. Karim, Nazmul et al. 2020. “Sustainable Personal Protective Clothing for Healthcare Applications: A Review.” ACS Nano 14(10): 12313–40.
  8. Kashani, Mostafa Haghi. 2021. “A Systematic Review of IoT in Healthcare: Applications, Techniques, and Trends.” Journal of Network and Computer Applications 192(103164).
  9. Kementrian Kesehatan. 2023. “Data Set Monitoring.” https://satusehat.kemkes.go.id.
  10. Natsir, F, Sihombing, Abeputra. 2022. “Perancangan Sistem Pendukung Keputusan Untuk Rekomendasi Penentuan Penerima Beasiswa.” Jurnal Sistem Informasi dan Teknologi Peradaban 3(2).
  11. Pagano, A. Giordano R. Vurro M. 2021. “A Decision Support System Based on AHP for Ranking Strategies to Manage Emergencies on Drinking Water Supply Systems.” 2(35): 613–28.
  12. Postolache, O. 2021. “Remote Monitoring of Physical Rehabilitation of Stroke Patients Using IoT and Virtual Reality.” IEEE Journal on Selected Areas in Communications 39(2): 562–73.
  13. Puspitasari, Puti Nadhirah. 2020. “Hubungan Hipertensi Terhadap Kejadian Stroke.” Jurnal Ilmiah Kesehatan Sandi Husada 12(2): 922–26.
  14. Putra, Pandu Pratama. 2018. “Pengembangan Aplikasi Perhitungan Prediksi Stock Motor Menggunakan Algoritma C 4.5 Sebagai Bagian Dari Sistem Pengambilan Keputusan (Studi Kasus Di Saudara Motor).” INOVTEK Polbeng - Seri Informatika 3(1): 24.
  15. Ramadhan, Abiyyu. 2022. “Sistem Pendukung Keputusan Evaluasi Problematika Pendampingan Pembelajaran Daring Dengan Algoritma C4.5.” Jurnal Sistim Informasi dan Teknologi 4: 58–63.
  16. Richter, Daniel et al. 2021. “Analysis of Nationwide Stroke Patient Care in Times of COVID-19 Pandemic in Germany.” Stroke 52(2): 716–21.
  17. Sandfreni, Sandfreni, Muhammad Bahrul Ulum, and Anik Hanifatul Azizah. 2021. “Analisis Perancangan Sistem Informasi Pusat Studi Pada Fakultas Ilmu Komputer Universitas Esa Unggul.” Sebatik 25(2): 345–56.
  18. Singh, Dr Poonam Khetrapal. 2019. “World Stroke Day 2019.”
  19. Siregar, Gunayanti Kemalasari, and Lilik Joko Susanto. 2022. “Sistem Pendukung Keputusan Pemilihan Indekost Pemuda Dengan Menggunakan Metode Simple Additive Weighting (Saw).” Jurnal Ilmiah Sistem Informasi (JISI) 1(2): 31–36.
  20. Sitorus, Jimmi Hendrik P, and Muhammad Sakban. 2021. “Perancangan Sistem Informasi Penjualan Berbasis Web Pada Toko Mandiri 88 Pematangsiantar.” Jurnal Bisantara Informatika (JBI) 5(2): 1–13. http://bisantara.amikparbinanusantara.ac.id/index.php/bisantara/article/download/54/47.
  21. Sutton, Reed T. et al. 2020. “An Overview of Clinical Decision Support Systems: Benefits, Risks, and Strategies for Success.” npj Digital Medicine 3(1): 1–10. http://dx.doi.org/10.1038/s41746-020-0221-y.
  22. Zhang, Yihui, Zekun Xing, Kecheng Zhou, and Songhe Jiang. 2021. “The Predictive Role of Systemic Inflammation Response Index (Siri) in the Prognosis of Stroke Patients.” Clinical Interventions in Aging 16(November): 1997–2007.