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Articles

Vol. 10 No. 7 (2025): Kohesi: Jurnal Sains dan Teknologi, ISSN 3025-1311

TINJAUAN SEMANTIK TENTANG PENERAPAN ANALISIS SEMANTIK DALAM SISTEM PENDUKUNG KEPUTUSA

Submitted
December 4, 2025
Published
2025-12-04

Abstract

Pengembangan sistem pendukung keputusan menghadapi tantangan besarnya volume literatur dan kompleksitas hubungan konsep, sehingga diperlukan pendekatan analisis makna yang lebih dalam. Penelitian ini bertujuan mengevaluasi penerapan tinjauan literatur berbasis semantik dalam pengembangan sistem pendukung keputusan serta membandingkan performanya dengan tinjauan literatur tradisional. Metode yang digunakan mencakup penelusuran dan seleksi literatur dari tahun 2020 hingga 2025, pemrosesan teks berbasis analisis makna, serta penyusunan peta pengetahuan untuk mengidentifikasi pola, hubungan konsep, dan kesenjangan penelitian. Kebaruan penelitian ini terletak pada integrasi pemetaan makna dan struktur pengetahuan yang memungkinkan identifikasi konteks dan relasi konsep secara otomatis. Hasil menunjukkan bahwa pendekatan semantik memberikan peningkatan efektivitas dalam hal ketepatan, kelengkapan, dan kecepatan analisis dibandingkan metode manual. Selain itu, sejumlah tantangan teridentifikasi, seperti keterjelasan model, integrasi data, dan kebutuhan komputasi yang tinggi. Penelitian ini menyimpulkan bahwa penggunaan pendekatan semantik dapat meningkatkan kualitas analisis literatur dan mendukung pengembangan sistem pendukung keputusan yang lebih adaptif. Temuan ini dapat menjadi dasar bagi implementasi arsitektur analisis makna pada berbagai sektor, termasuk pemerintahan dan kesehatan.

References

  1. ​​Ahmed, N., Wahed, M., Thompson, N. C., Nagaraj, A., Mostafa, R., Shen, S., Schmallenbach, L., Schaufele, B., Joshi, M. P., Sarta, A. & Frank, M. (2020). The De-democratization of AI: Deep Learning and the Compute Divide in Artificial Intelligence Research. https://doi.org/10.48550/arXiv.2010.15581
  2. ​Amann, J., Blasimme, A., Vayena, E., Frey, D. & Madai, V. I. (2020). Explainability for artificial intelligence in healthcare: a multidisciplinary perspective. BMC Medical Informatics and Decision Making, 20(1). https://doi.org/10.1186/s12911-020-01332-6
  3. ​Brakefield, W. S., Ammar, N., Olusanya, O. A. & Shaban-Nejad, A. (2021). An Urban Population Health Observatory for Disease Causal Pathway Analysis and Decision Support: Underlying Explainable Artificial Intelligence Model. JMIR Public Health and Surveillance, 7(6). https://doi.org/10.2196/28269
  4. ​Chandra, R., Tiwari, S., Rastogi, S. & Agarwal, S. (2025). A Diagnosis and Treatment of Liver Diseases: Integrating Batch Processing, Rule-Based Event Detection and Explainable Artificial Intelligence. https://pmc.ncbi.nlm.nih.gov/articles/PMC11110446/
  5. ​Jayatilake, S. M. D. A. C. & Ganegoda, G. U. (2021). Involvement of Machine Learning Tools in Healthcare Decision Making. In Journal of Healthcare Engineering (Vol. 2021). Hindawi Limited. https://doi.org/10.1155/2021/6679512
  6. ​Jing, X., Min, H., Gong, Y., Biondich, P., Robinson, D., Law, T., Nohr, C., Faxvaag, A., Rennert, L., Hubig, N. & Gimbel, R. (2023). Ontologies Applied in Clinical Decision Support System Rules: Systematic Review. In JMIR Medical Informatics (Vol. 11). JMIR Publications Inc. https://doi.org/10.2196/43053
  7. ​Kandula, V. V. & Bhattacharyya, P. (2023). Decision Knowledge Graphs: Construction of and Usage in Question Answering for Clinical Practice Guidelines. http://arxiv.org/abs/2308.02984
  8. ​Kim, S. Y., Kim, D. H., Kim, M. J., Ko, H. J. & Jeong, O. R. (2024). XAI-Based Clinical Decision Support Systems: A Systematic Review. In Applied Sciences (Switzerland) (Vol. 14, Issue 15). Multidisciplinary Digital Publishing Institute (MDPI). https://doi.org/10.3390/app14156638
  9. ​Le, N. L., Abel, M.-H. & Gouspillou, P. (2024). Combining Embedding-Based and Semantic-Based Models for Post-hoc Explanations in Recommender Systems. http://arxiv.org/abs/2401.04474
  10. ​Li, A., Han, C., Xing, X., Wei, Q., Chi, Y. & Pu, F. (2024). KGSCS—a smart care system for elderly with geriatric chronic diseases: a knowledge graph approach. BMC Medical Informatics and Decision Making, 24(1). https://doi.org/10.1186/s12911-024-02472-9
  11. ​Maxwell-Smith, Z., Kohler, M. & Suominen, H. (2022). Scoping natural language processing in Indonesian and Malay for education applications. https://doi.org/10.18653/v1/2022.acl-srw.15
  12. ​Muhammad, W. S. F., Baizal, Z. K. A. & Dharayani, R. (2023). Ontology-Based Recommender System for Personalized Physical Exercise in Obesity Management. Sinkron, 8(3), 1699–1708. https://doi.org/10.33395/sinkron.v8i3.12689
  13. ​Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. In BMJ (Vol. 372). BMJ Publishing Group. https://doi.org/10.1136/bmj.n71
  14. ​PPRI No.39. (2019). SATU DATA INDONESIA. https://jdih.kemenkeu.go.id/dok/perpres-39-tahun-2019
  15. ​PPRI No.95. (2018). SISTEM PEMERINTAHAN BERBASIS ELEKTRONIK. https://www.hukumonline.com/pusatdata/detail/lt5bbf25bd643b9/peraturan-presiden-nomor-95-tahun-2018/
  16. ​Ritesh Chandra, Sonali Agarwal, Shashi Shekhar Kumar & Navjot Singh. (2025). OCEP: An Ontology-Based Complex Event Processing Framework for Healthcare Decision Support in Big Data Analytics. https://doi.org/https://doi.org/10.48550/arXiv.2503.21453
  17. ​Sadeghi-Ghyassi, F., Damanabi, S., Kalankesh, L. R., Van de Velde, S., Feizi-Derakhshi, M. R. & Hajebrahimi, S. (2022). How are ontologies implemented to represent clinical practice guidelines in clinical decision support systems: protocol for a systematic review. Systematic Reviews, 11(1). https://doi.org/10.1186/s13643-022-02063-7
  18. ​Shang, Y., Tian, Y., Lyu, K., Zhou, T., Zhang, P., Chen, J. & Li, J. (2024). Electronic Health Record–Oriented Knowledge Graph System for Collaborative Clinical Decision Support Using Multicenter Fragmented Medical Data: Design and Application Study. Journal of Medical Internet Research, 26(1). https://doi.org/10.2196/54263
  19. ​Shea, B. J., Reeves, B. C., Wells, G., Thuku, M., Hamel, C., Moran, J., Moher, D., Tugwell, P., Welch, V., Kristjansson, E. & Henry, D. A. (2017). AMSTAR 2: A critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ (Online), 358. https://doi.org/10.1136/bmj.j4008
  20. ​Shen, Y., Armelle, J.-A. & Joël, C. (2020). Un système multi-agents d’aide à la décision clinique fondé sur des ontologies. https://arxiv.org/pdf/2001.07374
  21. ​Spoladore, D. & Pessot, E. (2021). Collaborative ontology engineering methodologies for the development of decision support systems: Case studies in the healthcare domain. Electronics (Switzerland), 10(9). https://doi.org/10.3390/electronics10091060
  22. ​Subianto, P., Strategi, B. & Bangsa, T. (2025). RPJMN (Rencana Pembangunan Jangka Menengah Nasional) Tahun 2025-2029. https://perpustakaan.bappenas.go.id/e-library/file_upload/koleksi/dokumenbappenas/konten/Dokumen%202025/Konten/%7BDigital%7D%20Ringkasan%20RPJMN%20Tahun%202025-2029.pdf
  23. ​Tupayachi, J., Xu, H., Omitaomu, O. A., Camur, M. C., Sharmin, A. & Li, X. (2024). Towards Next-Generation Urban Decision Support Systems through AI-Powered Construction of Scientific Ontology using Large Language Models -- A Case in Optimizing Intermodal Freight Transportation. https://doi.org/10.3390/smartcities7050094
  24. ​ ​

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