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Pamungkas, Ardian
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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IDENTIFICATION OF CAPABILITY LEVELS OF MEDIS CARE INFORMATION SYSTEM USING COBIT 2019 Pamungkas, Ardian; Fardana, Nouvel Izza; Widodo, Aris Puji; Adi, Kusworo
JURTEKSI (Jurnal Teknologi dan Sistem Informasi) Vol 10, No 4 (2024): September 2024
Publisher : STMIK Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v10i4.3257

Abstract

Abstract: In the health sector, information technology was initially used for exchanging information between patients and doctors, health services, and exchanging health documents. The aim of applying information technology to the health sector is to increase the effectiveness and efficiency of the performance of doctors and clinic staff. This research uses COBIT 2019 as a framework for evaluating information technology governance. Primary data is collected directly from the research subjects through observation and interviews, while secondary data is sourced from other materials, such as documents or websites related to the research subject. This research focuses on Risk Profile and I&T Related Issues, with domains: APO11 – Managed Quality, and APO13 – Managed Security. Through interviews and evaluation, each priority objective was found to be at capability level 2 with ratings of 100% and 86% respectively. There are no significant gaps between the current capability levels; both are at level 2. Keywords: auditing; COBIT 2019; telemedicine  Abstrak: Di sektor kesehatan, teknologi informasi awalnya digunakan untuk pertukaran informasi antara pasien dan dokter, layanan kesehatan, dan pertukaran dokumen kesehatan. Tujuan penerapan teknologi informasi di sektor kesehatan adalah untuk meningkatkan efektivitas dan efisiensi kinerja dokter dan staf klinik. Penelitian ini menggunakan COBIT 2019 sebagai kerangka kerja untuk mengevaluasi tata kelola teknologi informasi. Data primer dikumpulkan langsung dari subjek penelitian dengan melakukan pengamatan dan interaksi langsung, sementara data sekunder diperoleh dari sumber lain. didapatkan dari jurnal atau situs website yang berkaitan dengan subjek penelitian. Penelitian ini berfokus pada Risk Profile dan I&T Related Issues, dengan domain : APO11 – Managed Quality, dan APO13 – Managed Security. Melalui wawancara dan evaluasi, setiap tujuan prioritas ditemukan berada pada level kapabilitas 2 dengan nilai masing-masing 100% dan 86%. Tidak ada kesenjangan signifikan antara tingkat kapabilitas saat ini; keduanya berada pada level 2. Kata kunci: audit; COBIT 2019; telemedis
Implementation of K-Nearest Neighbor in Case-Based Reasoning for Mental Health Diagnosis Systems Pamungkas, Ardian; Isnanto , R Rizal; Nugraheni , Dinar Mutiara Kusumo
Scientific Journal of Informatics Vol. 11 No. 4: November 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i4.19912

Abstract

Purpose: Assessing a model that employs the K-Nearest Neighbor (KNN) technique within Case-Based Reasoning (CBR) for diagnosing mental health disorders, concentrating on conditions such as anxiety, depression, stress, and normalcy, while enhancing its efficacy through the utilization of historical case data for more accurate and tailored diagnostic suggestions. Methods: This study implements the KNN method in CBR to create a mental health diagnosis system that can provide accurate results without the need for complex models or intensive training. This method effectively addresses various patient needs by utilizing previous case data to provide a personalized and case-based diagnosis. This system is designed to tackle mental health issues like anxiety, depression, and academic stress, utilizing a case study of students from ITBK Bukit Pengharapan. Result: This study developed a KNN-based model for mental health diagnosis, achieving 84.62% accuracy on test data. Data processing techniques like text mining, oversampling, and cosine similarity improved performance. With an optimal K value of 2, the model achieved 88% precision, 85% recall, and an F1-score of 84%. The anxiety label performed perfectly, with 100% precision, recall, and F1-score. Novelty: This study adds innovation by integrating the rarely used CBR and KNN algorithms for mental health diagnosis systems. Innovative techniques like text mining, oversampling to get around data integration, and cosine similarity computations, which greatly enhance model performance, assist this strategy. Because this method improves accuracy and expedites the diagnosis process, both of which support clinical decision-making, it may be able to help mental health professionals.
IDENTIFICATION OF CAPABILITY LEVELS OF MEDIS CARE INFORMATION SYSTEM USING COBIT 2019 Pamungkas, Ardian; Fardana, Nouvel Izza; Widodo, Aris Puji; Adi, Kusworo
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 10 No. 4 (2024): September 2024
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v10i4.3257

Abstract

Abstract: In the health sector, information technology was initially used for exchanging information between patients and doctors, health services, and exchanging health documents. The aim of applying information technology to the health sector is to increase the effectiveness and efficiency of the performance of doctors and clinic staff. This research uses COBIT 2019 as a framework for evaluating information technology governance. Primary data is collected directly from the research subjects through observation and interviews, while secondary data is sourced from other materials, such as documents or websites related to the research subject. This research focuses on Risk Profile and I&T Related Issues, with domains: APO11 – Managed Quality, and APO13 – Managed Security. Through interviews and evaluation, each priority objective was found to be at capability level 2 with ratings of 100% and 86% respectively. There are no significant gaps between the current capability levels; both are at level 2. Keywords: auditing; COBIT 2019; telemedicine  Abstrak: Di sektor kesehatan, teknologi informasi awalnya digunakan untuk pertukaran informasi antara pasien dan dokter, layanan kesehatan, dan pertukaran dokumen kesehatan. Tujuan penerapan teknologi informasi di sektor kesehatan adalah untuk meningkatkan efektivitas dan efisiensi kinerja dokter dan staf klinik. Penelitian ini menggunakan COBIT 2019 sebagai kerangka kerja untuk mengevaluasi tata kelola teknologi informasi. Data primer dikumpulkan langsung dari subjek penelitian dengan melakukan pengamatan dan interaksi langsung, sementara data sekunder diperoleh dari sumber lain. didapatkan dari jurnal atau situs website yang berkaitan dengan subjek penelitian. Penelitian ini berfokus pada Risk Profile dan I&T Related Issues, dengan domain : APO11 – Managed Quality, dan APO13 – Managed Security. Melalui wawancara dan evaluasi, setiap tujuan prioritas ditemukan berada pada level kapabilitas 2 dengan nilai masing-masing 100% dan 86%. Tidak ada kesenjangan signifikan antara tingkat kapabilitas saat ini; keduanya berada pada level 2. Kata kunci: audit; COBIT 2019; telemedis
Co-Authors Aris Puji Widodo Fardana, Nouvel Izza Isnanto , R Rizal Kusworo Adi Nugraheni , Dinar Mutiara Kusumo