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All Journal BERKALA SAINSTEK JURNAL ILMIAH OBSGIN : Jurnal Ilmiah Ilmu Kebidanan & Kandungan ARUMAS
Afriany, Renny
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Education Health Professions Mathematics Medicine & Pharmacology Nursing Physics Public Health Veterinary Other

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Information System Security Audit Based on the DSS05 Framework Cobit 5 at Higher Education XX Sinaga, Rudolf; Samsinar, Samsinar; Afriany, Renny
BERKALA SAINSTEK Vol 9 No 1 (2021)
Publisher : Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/bst.v9i1.20361

Abstract

Currently, information has become a commodity or basic need, it can even be said that we are already in an "information-based social" era. It is undeniable that the ability to access and ensure the availability of information quickly and accurately has become a very essential component for an organization, whether in the form of social or commercial organizations, educational institutions such as universities, government agencies, and individuals. Various channels were created to regulate access rights to information, to prevent unauthorized people from accessing it, to minimize losses for the owner of the information. Based on the results of interviews with the research object of XX college, there are still frequent disruptions to information system security such as attacks on servers that result in server downtime, attacks on institutional e-mails that result in being unable to receive or even send e-mails, and other disturbances. This certainly harms information services at the tertiary institution, therefore an information system security audit is required. This study aims to measure the level of information system security capabilities using the Cobit 5 framework in the APO13 and DSS05 domains. Based on the results of the audit, it was found that the GAP value was 3.6 for the APO13 domain or at level 1 while 3.4 for the GAP DSS05 value or at level 2, it can be concluded that the information system security maturity level is still very low so that it needs improvement. It is recommended to make SOPs and documentation of maintenance, control, and periodic security evaluation, install an antivirus that has high and up to date protection accuracy, and make regular maintenance reports both on software and hardware.
Fuzzy Employee Placement Suitability Assessment using Mamdani Fuzzy Method Afriany, Renny; Sinaga, Rudolf; Samsinar, Samsinar
BERKALA SAINSTEK Vol 10 No 2 (2022)
Publisher : Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/bst.v10i2.30280

Abstract

For a company, employees are the spearhead for the company because they have a function as Customer Service, customer satisfaction is obtained after interacting with the company through the performance of its employees. Employees are expected to meet all customer needs with the applicable regulations in the company and become a source of income for the company. To get reliable employees, one way is to assess the suitability of their placement in the appropriate position. With the assessment of the suitability of positioning, companies can consider and determine the provision of rewards, promotions, punishments, training, coaching, counseling, or transfers for their employees. The choice of method used to assess the suitability of employee placement in a company is Fuzzy Mamdani. With the Fuzzy Mamdani method, a system that is completely measurable and human assessments that tend to be immeasurable can be bridged. Assessment of the suitability of employee placement using the resulting fuzzy method, is expected to be an alternative solution for companies to give positions to their employees.
Deteksi Dini Kanker Payudara Menggunakan Metode Gans (Generative Adversarial Network) Dilihat Dari Segi Filosofi: Narrative Review (NR) Samsinar, Samsinar; Afriany, Renny
JURNAL ILMIAH OBSGIN : Jurnal Ilmiah Ilmu Kebidanan & Kandungan P-ISSN : 1979-3340 e-ISSN : 2685-7987 Vol 16 No 4 (2024): DESEMBER
Publisher : NHM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36089/job.v16i4.2545

Abstract

Early detection of cancer using artificial intelligence (AI) from a healthcare perspective is crucial as it significantly increases the chances of successful treatment and reduces the risk of mortality. This aspect is emphasized as a vital factor in enhancing early cancer detection in patients and improving survival rates from a philosophical perspective. This article highlights that early detection can also help reduce the high costs associated with cancer treatment. By identifying the disease at an early stage, patients may require less intensive and less expensive treatment, which can alleviate the burden on both patients and their families. However, there are challenges, as over time, breast cancer becomes more difficult to treat, leading to a decrease in survival rates, necessitating the implementation of effective early detection methods. The development of pattern recognition methods is discussed as a means to improve the accuracy of early cancer detection. The results present a framework for analyzing human-computer interaction that incorporates a philosophical perspective, providing a structured approach to evaluating the implications of technology on human life.
Prediction of Hospital Administration Study Program Students' Graduation Using Decision Tree C4.5: Prediction of Hospital Administration Study Program Students' Graduation Using Decision Tree C4.5 Samsinar, Samsinar; Sinaga, Rudolf; Afriany, Renny
ARUMAS Vol 2 No 2 (2025): Jurnal Administrasi Rumah Sakit
Publisher : STIKES Garuda Putih

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52741/ars.v2i2.109

Abstract

The timely graduation success of students is a crucial indicator in evaluating the quality of higher education institutions. This study aims to predict the graduation rate of undergraduate students in the Hospital Administration Program at STIKES Garuda Putih Jambi using the Decision Tree C4.5 algorithm. The data utilized includes the Cumulative Grade Point Average (CGPA) of 35 students over the first four semesters. The dataset was processed using RapidMiner to generate a prediction model with CGPA as the main variable. The model evaluation indicated an accuracy level of 73.33%. This classification model successfully categorized student graduation outcomes into three groups: satisfactory, very satisfactory, and with distinction. The findings of this study are expected to provide insights for better academic decision-making, as well as enhance the quality of evaluation and learning processes in higher education institutions.
Co-Authors Rudolf Sinaga Samsinar Samsinar