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All Journal Teknika Jupiter Gaung Informatika Jurnal Manajemen dan Keuangan Proceeding International Conference on Information Technology and Business Fortech : Journal of Information Technology Jurnal PGSD Jurnal Pustaka Mitra : Pusat Akses Kajian Mengabdi Terhadap Masyarakat E-Amal: Jurnal Pengabdian Kepada Masyarakat Vokasi UNESA Bulletin of Engineering, Technology and Applied Science
Lia Rosmalia
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Journal : Gaung Informatika

 1 
SISTEM PENDUKUNG KEPUTUSAN KLINIS UNTUK MENENTUKAN JENIS GANGGUAN PSIKOLOGI PADA PASIEN GAGAL GINJAL KRONIS (GGK) YANG MENJALANI TERAPI HEMODIALISA Rosmalia, Lia; Kusumadewi, Sri
JURNAL GAUNG INFORMATIKA Vol 11 No 2 (2018): Jurnal Gaung Informatika Vol 11 No 2 Juli 2018
Publisher : JURNAL GAUNG INFORMATIKA

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Abstract

Psychological factors in patients with chronic renal failure conditions are severely affected by prolonged course of the disease, disability and discomfort should depend onthe hemodialysis machine. Hemodialysis therapy in addition to disturbing the physical, complications can trigger mental disorders. Patients with chronic renal failure often have psychological disorders associated with general medical conditions. Anxiety and depression are often psychological disorders experienced. Symptoms that are almost similar to each other will require experts to correctly identify them based on the patients perceived symptoms. Limitations of health practitioners in exploring thepsychological conditions felt by the patient to be one reason for the necessity of a clinical decision support system capable of integrating patient information  (demographic, clinical, social psychological) with a knowledge base with the aim of identifying psychological conditions in a clinical setting that can assist physicians, nurses, psychologists and health practitioners others in making a clinical decision on their patients. The approach in this study uses case-based reasoning (Case-Based Reasoning) (CBR). CBR process through four stages of the process are: retrieve, reuse, revise and retain. If there is a similar case then the reasoning to weigh the nearest case using the Simple Matching Coefficient (SMC) method so that the system is able to streamline the diagnostic process by taking into account the closeness between the base case and the target case. As a result, the system will be able to provide a recommendation picture of the initial diagnosis of the highest percentage of possible types of psychological disturbance suffered with its severity level and the best solution for new cases based on the nearest case solution of the nearest similarity level.
SISTEM PENDUKUNG KEPUTUSAN KLINIS UNTUK MENENTUKAN JENIS GANGGUAN PSIKOLOGI PADA PASIEN GAGAL GINJAL KRONIS (GGK) YANG MENJALANI TERAPI HEMODIALISA Lia Rosmalia; Sri Kusumadewi
JURNAL GAUNG INFORMATIKA Vol 11 No 2 (2018): Jurnal Gaung Informatika Vol 11 No 2 Juli 2018
Publisher : Universitas Sahid Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Psychological factors in patients with chronic renal failure conditions are severely affected by prolonged course of the disease, disability and discomfort should depend onthe hemodialysis machine. Hemodialysis therapy in addition to disturbing the physical, complications can trigger mental disorders. Patients with chronic renal failure often have psychological disorders associated with general medical conditions. Anxiety and depression are often psychological disorders experienced. Symptoms that are almost similar to each other will require experts to correctly identify them based on the patient's perceived symptoms. Limitations of health practitioners in exploring thepsychological conditions felt by the patient to be one reason for the necessity of a clinical decision support system capable of integrating patient information (demographic, clinical, social psychological) with a knowledge base with the aim of identifying psychological conditions in a clinical setting that can assist physicians, nurses, psychologists and health practitioners others in making a clinical decision on their patients. The approach in this study uses case-based reasoning (Case-Based Reasoning) (CBR). CBR process through four stages of the process are: retrieve, reuse, revise and retain. If there is a similar case then the reasoning to weigh the nearest case using the Simple Matching Coefficient (SMC) method so that the system is able to streamline the diagnostic process by taking into account the closeness between the base case and the target case. As a result, the system will be able to provide a recommendation picture of the initial diagnosis of the highest percentage of possible types of psychological disturbance suffered with its severity level and the best solution for new cases based on the nearest case solution of the nearest similarity level.
Co-Authors - Nurfiana - Nurjoko Agustina Cindy Amelia Alkahfiansyah, Muhammad Andri Irawan Ari Widiantoko Dwi Handayani, Retno H Sudibyo, Novi Herwanto, Riko Melia Gripin Setiawati Nanny Novi Herawadi Sudibyo Retno Dwi Handayani Rosandy, Triowali Santoso, Putra Pratama Setiawati, Melia Gripin Setyawan, Dodi Yudo Sri Karnila Sri Kusumadewi Sukma Puspitorini Wahidin Wahidin Zaenal Abidin Zaidir Jamal