Metode Penilaian Kualitas Data Sebagai Rekomendasi Sistem Repositori Ilmiah Nasional

Riyanto, Slamet; Marlina, Ekawati; Subagyo, Hendro; Triasih, Hermin; Yaman, Aris

doi:10.14203/j.baca.v41i1.544

Cited by 3 publications

(2 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The diversity of knowledge and expertise possessed by repository management staff becomes very important, the data that must be managed is very diverse Knowledge of metadata also needs special attention, not everyone have the ability to understand various standard metadata. Research [22] mentions completeness of metadata is needed to provide information related to data saved. Standard metadata that is generally used for data exchange it contains title, creator, description, subject, date, publisher, and contributor.…”

Section: Figure 3 Accuracy Of Data Attributes Percentage Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Data Quality Measurement to Improve Sqa Application in Pt Xyz

Go,

Julianasari,

Imron

et al. 2023

jicon

View full text Add to dashboard Cite

Service Quality Assurance (SQA) is one of a unit in PT XYZ an Indonesian e-commerce company. SQA is responsible for ensuring and maintaining services given to customers by Customer Service agents to meet the company's quality standard. However, the application was built without integration with the Customer Relationship Management (CRM) system, the main customer service application at PT XYZ. The problem is that if companies need SQA data, they must manually input data from SQA to CRM. This can cause vulnerabilities in the data input process. As a result, it impacts the company's business processes, which are inefficient and can be detrimental both materially and immaterially. This research aims to provide recommendations to improve the quality of SQA data so that companies can use the data to be integrated into the CRM system. The Total Data Quality Management (TDQM) method was used for this study with three dimensions: completeness, validity and accuracy. The results of each dimension are 99.64% for completeness, 84.75% for validity, and 100% for accuracy. Business rules on the validity dimension that have the lowest data quality are V1 28.57% and V6 65.11%. The problem factors were identified as an incomplete data dictionary, incomplete and obsolete SOP documents, and no business processes and data control on the application. Recommendations to improve the data quality of the application are PT XYZ can conduct an in-depth study of business roles so that all business processes can be clearly defined and regulations can be set forth in SOP documents. The use of specific reference data for each domain can be used to increase data legitimacy and the level of data suitability.

show abstract

Section: Figure 3 Accuracy Of Data Attributes Percentage Discussionmentioning

confidence: 99%

“…Data curation activities not just checking metadata, complete supporting data, instructions for use data, as well as legal aspects. However, research [22] state it is necessary to understand in substance, so that the data is managed and published can be reused and generate new data (reproduce).…”

Section: Figure 3 Accuracy Of Data Attributes Percentage Discussionmentioning

confidence: 99%

Data Quality Measurement to Improve Sqa Application in Pt Xyz

Go,

Julianasari,

Imron

et al. 2023

jicon

View full text Add to dashboard Cite

show abstract

Tuberculosis Surveillance System Evaluation in Blitar District: Study of System Approach and Attributes

Florentji Adel Benu,

Atoillah Isfandiari,

Pramono

2024

JBE

View full text Add to dashboard Cite

Background: Blitar district was in the last second position in East Java Province, achieving low Tuberculosis recovery and treatment of the national target by 2022. Therefore, it is necessary to support surveillance systems as a prerequisite for providing information as decision-making material. Purpose: to describe the quality of the tuberculosis surveillance system based on its approach and attributes. Methods: This research was an evaluation study design on the tuberculosis surveillance system in 2022. Respondents totaled 19 people. Data was collected by interview using a questionnaire and document study using a checklist. Data was analyzed by comparing the system approach and surveillance attributes to existing guidelines. The data was presented in tables and narratives. Results: Evaluation of tuberculosis surveillance systems based on input, process, and output was available by surveillance guidelines. Evaluation of the surveillance attributes showed that the flexible system has high data quality, high sensitivity, timeliness, and high stability. However, the system is not simple in operation, has low acceptability of the network, and has low positive predictive value because the suspect detection is too loose and not representative. Conclusion: The implementation of the tuberculosis surveillance system has largely been carried out well, supported by several complete surveillance attributes. It is necessary to provide standard operational procedures for recording and reporting, improve coordination with the network to manually and electronically report suspected tuberculosis, and optimize the Mantoux test in children.

show abstract

Improving the Quality of Recording and Reporting as Well as the Quality of Data and Risk Management Information at Kolonodale Hospital, North Morowali Regency with the Website-Based Sip-Menko-Rs Application

Ibrahim,

Fatmasari

et al. 2024

International Journal of Innovative Science and Research Techno

View full text Add to dashboard Cite

Background: IKP reporting in Indonesia in 2019 was 7,310 incidents. The risk factor for incidents is the lack of implementation of a reporting culture, which has not been implemented systematically. Innovations that can be used to change risk management recording and reporting, namely through risk management information system models, are expected to improve the quality of recording and reporting and risk management data and information in hospitals. Method: The method used is Research and Development (R&D) with a qualitative and quantitative approach, the stages are identification of needs, design, expert validation, feasibility test 1, and feasibility test 2. This research uses a pre-experimental design with a one-group pre-design. Post-test. Data collection techniques are interviews, observation, and questionnaires and the data is processed using non-parameteric tests. The sampling technique was purposive sampling consisting of 32 room heads and 1 K3RS person who were given intervention for 1 month. Results: The results of the validity of the risk management information system model show a p-value = 0.000, meaning the model is suitable for use. This model is effective in improving the quality of recording and reporting as well as data and information (p=0.000). In feasibility test 2, the result obtained was p=0.000, meaning the model was suitable for use independently by the head of the room and K3RS.

show abstract

Metode Penilaian Kualitas Data Sebagai Rekomendasi Sistem Repositori Ilmiah Nasional

Cited by 3 publications

References 18 publications

Data Quality Measurement to Improve Sqa Application in Pt Xyz

Data Quality Measurement to Improve Sqa Application in Pt Xyz

Tuberculosis Surveillance System Evaluation in Blitar District: Study of System Approach and Attributes

Improving the Quality of Recording and Reporting as Well as the Quality of Data and Risk Management Information at Kolonodale Hospital, North Morowali Regency with the Website-Based Sip-Menko-Rs Application

Contact Info

Product

Resources

About