Software Architecture Refactoring Based on Data Integration and Interoperability Issues in PeduliLindungi

Setyawan, Rony; Hidayanto, Achmad Nizar; Sensuse, Dana Indra; Suryono, Ryan Randy; Kautsarina, Kautsarina

doi:10.1109/icite54466.2022.9759897

Cited by 5 publications

(2 citation statements)

References 9 publications

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“…DII architecture can be accomplished via application-loose coupling techniques employing services, APIs, or message queues. Some articles on practical data management divide data governance responsibilities into three or four categories (Falahah & Santoso, 2022;Setyawan et al, 2022).…”

Section: Modelling Data Governance Modelmentioning

confidence: 99%

Data Governance Model For Nation-Wide Non-Profit Organization

Paramita,

Prabowo,

Ramadhan

et al. 2023

JAETS

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According to Connolly's (2017) research, the context of nonprofit organizations exhibits variations when compared to commercial organizations or businesses, as supported by Zhang's (2010) study. Hence, it is imperative for both theoretical and empirical studies to contribute towards enhancing our comprehension of the strategy, implementation, and utilization of information systems in the specific context of nonprofit organizations. The investigation of information systems within the context of non-profit organizations offers a promising avenue for advancing the field of information systems research. This study focuses on the development of an information systems framework using the soft systems methodology, which has already been established. One opportunity for the advancement of information systems in non-profit organizations lies in the establishment of a comprehensive framework that facilitates adoption and is accompanied by robust data governance. This framework enables the analysis of data and the generation of valuable insights, thereby contributing to the development of information systems in the non-profit sector. The choice of data governance was informed by Zhang's (2010) research, which demonstrated that non-profit organizations face significant obstacles in the form of privacy and data security concerns. Furthermore, it is apparent that the preservation of data privacy plays a crucial role in the acceptance and utilization of information systems within non-profit entities. This research aims to contribute to the resolution of the issue by establishing a governance framework for information systems that effectively communicates to users the absence of data privacy risks associated with the systems employed by organizations. The objective of this study is to create a data governance model that will fill the research gap mentioned earlier and make a valuable contribution to the field of information systems research. The formation of the data governance model will involve the integration of soft systems methodology and the DAMA framework. The outcome of this study will be a data governance model specifically designed for a nationwide non-profit organization that utilizes microservices as its cutting-edge technology.

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Section: Modelling Data Governance Modelmentioning

confidence: 99%

Data Governance Model For Nation-Wide Non-Profit Organization

Paramita,

Prabowo,

Ramadhan

et al. 2023

JAETS

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“…3. Technical problems is referred to as PLMA [1] Several previous studies related to PLMA, but very lack studies on PLMA user experience and user interface, previous related studies were PeduliLindungi's COVID-19 Treatment Success (Indonesian Case Study) [1], User Satisfaction Analysis of PeduliLindungi App Using EUCS Method [5], PeduliLindungi App Users Multinomial Naive Bayes-SMOTE Fine-Grained Sentiment Analysis [6], Integration and Interoperability Issues with PeduliLindungi Data and Software Architecture Refactoring [7], Aspects of the PeduliLindungi App User's Goals, Procedures, Tools, and Surroundings [8], PeduliLindungi User Satisfaction Research [9], Google Play PeduliLindungi sentiment analysis using the Random Forest Algorithm with SMOTE [10], Case Study of Jakarta University Students' Use of the PeduliLindungi App to Prevent COVID-19 [11], PeduliLindungi, an Indonesian tracking app, sheds light on an integrated model of tracking apps [12], Factors That Influence Indonesians' Plans to Use the PeduliLindungi App During COVID-19 [13], Sentiment Analysis Machine Learning Comparison PeduliLindungi Applications [14], Binary Sentiment Reviews: Support Vector Machine vs. Naive Bayes Classifier for the PeduliLindungi App [15], Support Vector Machine and Naive Bayes Algorithm-Based Particle Swarm Optimization Analysis of Google Play User Reviews for PeduliLindungi [16], and Acceleration of Pedulilindungi's Popularity Among the Public in Relation to the Corona Virus (Covid-19) [17].…”

Section: Introductionmentioning

confidence: 99%

Exploring User Experience and User Interface of Indonesian e-Health PeduliLindungi Mobile-Apps with MeCUE 2.0 Framework

2023

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PeduliLindungi Mobile-Apps (PLMA) is a mobile-based e-Health application that was released by the Ministry of Communication and Information (KOMINFO) of the Republic of Indonesia in April 2020. Its goal is to help the government keep track of the Covid-19 Pandemic in Indonesia and stop it from spreading. PLMA is used to find Covid-19, keep track of it, warn people about it, and stop it from spreading. Reports say that more than 10,000,000 people have downloaded PLMA, and KOMINFO has told all citizens that they must use this app. But PLMA was criticized by people who used its apps because of problems like application errors, data leaks, and mistakes in user data. Also, as of September 29, 2021, 470,521 people had reviewed it on the Google Play Store, giving it an average score of 3.8. The score from the PLMA review shows that the application needs to be improved. PLMA also gets complaints about how hard it is to navigate, how features aren't clear, how there are problems with connection and performance, how personal data isn't safe, and how hard it is to get to. The purpose of the research is to investigate and evaluate PLMA which focuses on the user experience (UX) or user interface (UI) of application users. UI/UX in PLMA has been measured or evaluated in a few studies, but the numbers are still very small and limited. Minge (2020) came up with the meCUE 2.0 framework as a way to evaluate an application user experience service. It is a fairly new and comprehensive framework. The MeCUE 2.0 Framework has a questionnaire with 34 statement items. It is made up of 4 modules: Modules I and II (Perception of quality of instrumental and non-instrumental products), Module III (Emotions), Module IV (Consequences), and Module V (Overall Evaluation). In the first step of this study, the meCUE 2.0 questionnaire was translated and then given to 50 people. The results showed that the UI/UX ratings for PLMA were 3.17 for usefulness, 4 for usability, 3.33 for visual aesthetics, 3 for status, 3.67 for commitment, 3.67 for positive emotions, 2.67 for negative emotions, 3.67 for intention to use, 2.67 for product loyalty, and 3.67 for overall evaluation.(107.00). This research makes a contribution both in terms of ideas and in terms of how it can be used. For example, it tells UX designers and policymakers that they should pay attention to important factors while developing PLMAs.

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