Articles

Predictive Analysis for Personalized Machine: Leveraging Patient Data for Enhanced Healthcare

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This research explores predictive analysis for personalized machine: leveraging patient data for enhanced healthcare. By leveraging the power of information and analytics, the healthcare industry can be driven towards a more patient-centric, proactive model that enhances outcomes and improve the overall quality of care. The objectives of the study are to: determine the significance and challenges of predictive analytics in healthcare, ascertain the data analytics techniques used in healthcare to enhance patient care, find out how predictive analytics can be applied for enhanced healthcare, and determine the ethical considerations associated with healthcare predictive analytics. This study employs the case study approach and experimental design. The study analyzes case studies of real-time deployment of predictive analytics models in healthcare centers, examines how these models enhance the healthcare delivery in those centers. Experiments were also conducted to understand how predictive analytics works. The C4.5 learning algorithm was employed to predict the presence of chronic kidney disease (CKD) in patients and differentiate between those not affected by the condition. The C4.5 classifier shows reasonable strength, evident in the large number of rightly classified occurrences (396) and a low misclassification of only 4 occurrences. This is further demonstrated by a low error rate of 0.37, as shown in table 5. The prevalence of this algorithm is emphasized by the large value of KS (0.97), indicating the classifier’s ground-breaking accuracy and performance. The performance of C4.5, featured by its minimal execution time and accuracy, puts it as a decent classifier. This characteristic makes it specifically well-suited for application in the healthcare sector, particularly for tasks involving prediction and classification. The application of data analytics methods for predictive analysis holds significant benefits in the health sector, as it gives us the power to predict and address potential threats to human health, covering different age groups, from the young ones to the elderly. This proactive method enables early disease detection, helping in timely interventions and contributing to better decision-making.

 

The Effect of Information Quality, System Quality and Organizational Capability on the Implementation of HMIS at Regional public hospital Pambalah Batung, Hulu Sungai Utara Regency

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The Hospital Management Information System (HMIS) is an integral part of overall hospital services and has even become one of the main joints in daily activities. Evaluation of HMIS implementation is carried out because it will assess the benefits derived from HMIS implementation and find potential problems faced by users and organizations. The results of this evaluation can be used as a reference for improving or perfecting the HMIS and minimizing the potential for existing problems, so that HMIS becomes better, perfect and can support the vision, mission and goals of the organization. The find out the quality of information, system quality and organizational capabilities in implementing HMIS at Pambalah Batung Hospital. This research is an associative research with a quantitative paradigm. The sample in this research is 150 respondents. The data analysis technique used a simple and multiple linear regression analysis test. There is an influence between information quality (p=0.000), system quality (p=0.000) and organizational capability (p=0.000) on HMIS implementation. Information quality, system quality and organizational capability simultaneously influence HMIS implementation (p=0.000). Information quality is the most dominant in HMIS implementation with a constant value (b = 0.387) (4.680). There is influence between information quality, system quality and organizational capability partially and simultaneously on HMIS implementation. Information quality has a dominant significant effect on HMIS implementation at Pambalah Batung Hospital. Pambalah Batung Amuntai Hospital, Hulu Sungai Utara Regency, further improves the information system for HMIS employees and must pay more attention to information systems by always improving good information systems and also providing information to Pambalah Batung Hospital.

Systematic Literature Review and Bibliometric: Blockchain Technology in Archives

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Disclosure of information makes it easy for the public to obtain information anytime and anywhere. New solutions for access control and monitoring of archives are urgently needed to keep things safe. Archival institutions as guarantors of the availability of information are expected to provide solutions and new ideas for developments in the implementation of national archives. Archiving in developed countries on blockchain technology is something new. The purpose of this research is to find out the advantages of blockchain technology in archiving and hope that readers or researchers benefit from Blockchain Technology research in archiving, which can be used for other research. Data collection techniques used the literature review method systematically and uses the VOSviewer application in this study and the findings of journal articles sourced from Scopus in 2017-2022.

Proposed Marketing Strategy to Increase Purchase Intention on Tokopedia Package Subscription

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Tokopedia is offering merchants a new feature called packaged subscriptions. However, there is evidence of low sales for these paid features. This study creates a marketing proposition to solve this problem with low-purchase packages. The purpose of this study is to identify the top reasons for unwillingness to pay, identify the key factors that motivate sellers to purchase, and identify appropriate strategies to motivate sellers to pay for packaged subscriptions. This research utilizes Triangulation method consisting of internal, external and qualitative analysis to determine that the main drivers of sellers’ purchase intention were price and information quality factors. The study uses the company’s industry environment, competitors, company capabilities, and the user’s analysis to generate recommendations using the QSPM matrix. The most pertinent recommendation is to offer a free trial program and scheduled in-app notifications to boost the seller’s intent to purchase the subscription package.