Sistem Pakar dalam Menganalisis Penyakit Organ dan Jaringan Tubuh dengan Metode Perceptron dan Fitur Augmented Reality

Main Article Content

Eryanto Agusriadi
Finot

Abstract

Diseases of organs and tissues of the body or in medicine are commonly referred to as anatomical pathology. Is a medical specialist who deals with the diagnosis of disease based on gross, microscopic and molecular examination of organs, tissues and cells. This procedure is used to identify abnormalities in the body and can help diagnose disease. This study aims that the results of the analysis of the perceptron method can help the doctors of the Putri Hijau Hospital in Medan City quickly and precisely in identifying and analyzing patients with anatomical pathologies. The data processed in this study were 50 patients from the hospital, sourced from one of the anatomical pathology specialists at the hospital. Then the results of the data that have been obtained from patients with the perceptron method using an android-based application. So that the results of the diagnosis of the patient's disease can be obtained. The results of research with this method produce a system that can assist anatomical pathology specialists to present disease diagnosis information at the Putri Hijau Hospital in Medan City. With the existence of an expert system in analyzing diseases of organs and body tissues, it can be recommended to help specialists in anatomical pathology to diagnose patients more quickly and precisely.

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How to Cite
Agusriadi, E., & Finot. (2022). Sistem Pakar dalam Menganalisis Penyakit Organ dan Jaringan Tubuh dengan Metode Perceptron dan Fitur Augmented Reality. Jurnal Informasi Dan Teknologi, 4(1), 39-45. https://doi.org/10.37034/jidt.v4i1.180
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References

[1] Andreas M.; Michael Haenlein (2010) "Users of the world, unite! The challenges and opportunities of Social Media". Business Horizons 53(1): 59–68
[2] Arif, M., 2018. Jaringan Syaraf Tiruan Menggunakan Metode Perceptron Untuk Pengenalan Gejala Penyakit Kaki Gajah (Filariasis). Jurnal Sains dan Informatika, 4(1), pp.11–20. http://dx.doi.org/10.22216/jsi.v4i1.2619
[3] Hutapea, B. D., Ginting, G., & Hondro, R. K. (2021). Penerapan Algoritma Perceptron Untuk Mendeteksi Virus Parvo Pada Anjing. Pelita Informatika: Informasi dan Informatika, 6(4), 425-429
[4] Rouza, E., 2017. Prediksi Jenis Cacing Nematoda Usus Yang Menginfeksi Siswa Dengan Menggunakan Metoda LVQ. Digital Zone: Jurnal Teknologi Informasi dan Komunikasi, 8(2), pp.170–184. http://dx.doi.org/10.31849/digitalzone.v8i2.642
[5] Lorencin, I., Anđelić, N., Španjol, J., & Car, Z. (2020). Using multi-layer perceptron with Laplacian edge detector for bladder cancer diagnosis. Artificial Intelligence in Medicine, 102, 101746. https://doi.org/10.1016/j.artmed.2019.101746
[6] Desai, M. & Shah, M., 2021. An anatomization on breast cancer detection and diagnosis employing multi-layer perceptron neural network (MLP) and Convolutional neural network (CNN). Clinical eHealth, 4, pp.1–11. http://dx.doi.org/10.1016/j.ceh.2020.11.002
[7] Sriyanti, C., 2016, Mutu Layanan Kebidanan & Kebijakan Kesehatan. 1 ed. Kementerian Kesehatan RI Pusat Pendidikan Sumber Daya Manusia Kesehatan
[8] Safrida. 2018. Anatomi dan fisiologi manusia. Banda Aceh: Syiah Kuala University
[9] Smith R D (1989). Some characteristics of the community practice of pathology in the United States. National Manpower Survey of 1987. Arch Pathol Lab Med 113 (12): 1335-42. PMID 2589945
[10] Leviss, Dani (11 Oktober 2020). "How many organs are in the human body?". Live Science. Diakses tanggal 19 Februari 2022
[11] Doll, Julie (29 Oktober 2020). "Tissue types". Ken Hub. Diakses tanggal 19 Februari 2022
[12] Cheng, J.Y. et al., 2021. Challenges in the Development, Deployment, and Regulation of Artificial Intelligence in Anatomic Pathology. The American Journal of Pathology, 191(10), pp.1684–1692. http://dx.doi.org/10.1016/j.ajpath.2020.10.018
[13] Critchley-Thorne, R. et al., 2015. TissueCypher™: A systems biology approach to anatomic pathology. Journal of Pathology Informatics, 6(1), p.48. http://dx.doi.org/10.4103/2153-3539.163987
[14] Kulkov, I. et al., 2021. Navigating uncharted waters: Designing business models for virtual and augmented reality companies in the medical industry. Journal of Engineering and Technology Management, 59, p.101614. http://dx.doi.org/10.1016/j.jengtecman.2021.101614
[15] Sveinsson, B., Koonjoo, N. & Rosen, M.S., 2021. ARmedViewer, an augmented-reality-based fast 3D reslicer for medical image data on mobile devices: A feasibility study. Computer Methods and Programs in Biomedicine, 200, p.105836. http://dx.doi.org/10.1016/j.cmpb.2020.105836
[16] Gsaxner, C. et al., 2019. Facial model collection for medical augmented reality in oncologic cranio-maxillofacial surgery. Scientific Data, 6(1). Available at: http://dx.doi.org/10.1038/s41597-019-0327-8
[17] Weeks, J.K. et al., 2021. Harnessing Augmented Reality and CT to Teach First-Year Medical Students Head and Neck Anatomy. Academic Radiology, 28(6), pp.871–876. Available at: http://dx.doi.org/10.1016/j.acra.2020.07.008