Comparison of PHP Programming Language with Codeigniter Framework in Project CRUD

Muqorobin, Muqorobin; Rais, Nendy Akbar Rozaq

doi:10.29040/ijcis.v3i3.77

Cited by 8 publications

(7 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…CodeIgniter is an open-source application for building dynamic PHP applications (Muqorobin & Rozaq Rais, 2022). CodeIgniter can speed up developers for developing PHP-based web applications (Anggraini et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

Stunting Early Warning Application Using KNN Machine Learning Method

Purwati,

Sulistyo

2023

J. Ris. Inform.

View full text Add to dashboard Cite

Stunting in toddlers is defined as a condition of failure to thrive due to chronic malnutrition in the long term. The problem of stunting in Indonesia is an issue that is still a concern for the Indonesian government. The prevalence of stunting in Indonesia is still relatively high, coupled with the COVID-19 pandemic, which has impacted the economic sector. For this reason, research on stunting is still a critical topic. This study aims to classify toddler stunting using the k-Nearest Neighbor classification algorithm and build a website-based early detection application for toddler stunting cases. The research results using the k-Nearest Neighbor Algorithm trial obtained a relatively high accuracy of 92.45%. Implementing an early detection system for stunting cases has proven to help health workers classify toddlers as stunted or not. This application is also helpful as an archive and facilitates data reporting. The application has eight main menus: the Puskesmas data menu, Posyandu data, toddler data, weighing, weighing results, development menu, and stunting early warning menu, which contains malnourished and stunted toddlers.

show abstract

Section: Discussionmentioning

confidence: 99%

Stunting Early Warning Application Using KNN Machine Learning Method

Purwati,

Sulistyo

2023

J. Ris. Inform.

View full text Add to dashboard Cite

show abstract

“…Data at rest are encrypted using randomized keys generated by AWS key management service that gives centralized control over the cryptographic keys used to protect data. All users’ passwords are hashed and stored using Secure Hashing Algorithms [ 31 ], which shorten passwords into smaller forms that cannot be understood using bitwise operation, modular additions, or compression functions.…”

Section: Methodsmentioning

confidence: 99%

Digital Health Dashboards for Decision-Making to Enable Rapid Responses During Public Health Crises: Replicable and Scalable Methodology

Katapally¹,

Ibrahim²

2023

JMIR Res Protoc

View full text Add to dashboard Cite

Background The COVID-19 pandemic has reiterated the need for cohesive, collective, and deliberate societal efforts to address inherent inefficiencies in our health systems and overcome decision-making gaps using real-time data analytics. To achieve this, decision makers need independent and secure digital health platforms that engage citizens ethically to obtain big data, analyze and convert big data into real-time evidence, and finally, visualize this evidence to inform rapid decision-making. Objective The objective of this study is to develop replicable and scalable jurisdiction-specific digital health dashboards for rapid decision-making to ethically monitor, mitigate, and manage public health crises via systems integration beyond health care. Methods The primary approach in the development of the digital health dashboard was the use of global digital citizen science to tackle pandemics like COVID-19. The first step in the development process was to establish an 8-member Citizen Scientist Advisory Council via Digital Epidemiology and Population Health Laboratory’s community partnerships. Based on the consultation with the council, three critical needs of citizens were prioritized: (1) management of household risk of COVID-19, (2) facilitation of food security, and (3) understanding citizen accessibility of public services. Thereafter, a progressive web application (PWA) was developed to provide daily services that address these needs. The big data generated from citizen access to these PWA services are set up to be anonymized, aggregated, and linked to the digital health dashboard for decision-making, that is, the dashboard displays anonymized and aggregated data obtained from citizen devices via the PWA. The digital health dashboard and the PWA are hosted on the Amazon Elastic Compute Cloud server. The digital health dashboard’s interactive statistical navigation was designed using the Microsoft Power Business Intelligence tool, which creates a secure connection with the Amazon Relational Database server to regularly update the visualization of jurisdiction-specific, anonymized, and aggregated data. Results The development process resulted in a replicable and scalable digital health dashboard for decision-making. The big data relayed to the dashboard in real time reflect usage of the PWA that provides households the ability to manage their risk of COVID-19, request food when in need, and report difficulties and issues in accessing public services. The dashboard also provides (1) delegated community alert system to manage risks in real time, (2) bidirectional engagement system that allows decision makers to respond to citizen queries, and (3) delegated access that provides enhanced dashboard security. Conclusions Digital health dashboards for decision-making can transform public health policy by prioritizing the needs of citizens as well as decision makers to enable rapid decision-making. Digital health dashboards provide decision makers the ability to directly communicate with citizens to mitigate and manage existing and emerging public health crises, a paradigm-changing approach, that is, inverting innovation by prioritizing community needs, and advancing digital health for equity. International Registered Report Identifier (IRRID) RR1-10.2196/46810

show abstract

“…Third, the report officer looks at the report and registers the queue data. Taxpayers can see the status of the queue on the monitor, as shown infigure 13.Queuing officer activity can be seen in figure 6, counter officer activity in figure 7, and reporting officer activity in figure 8 (Muqorobin & Rozaq Rais, 2022). Testing the System: The system testing method used is Gray Box Testing by combining Black Box Testing and White Box Testing methods.…”

Section: Methodsmentioning

confidence: 99%

Development of Client Server-Based Queuing Applications at The Samsat Gowa Office

Jaya¹,

Hendra

Hadis

et al. 2022

ceddi j. inf. syst. technol.

View full text Add to dashboard Cite

The government has established a SAMSAT (One-Stop Manunggal Administration System) office which has duties in the motor vehicle tax service. Queuing activities make people spend their time waiting. Therefore, it is necessary to create a queuing system that can inform the estimated queue time remotely. The queuing system does not require users to wait physically, so the waiting time needed to queue can be used by taxpayers to carry out their own personal and work activities that are more useful. Queuing application development aims to develop queuing service features from previous applications which only provide queued information on taxpayers. Features developed in the form of queuing data processing with different activities, monitoring information on time and queue status periodically. The research method used is SDLC (Software Development Life Cycle) with a prototype model. The test results using the Gray Box Testing method show that queuing applications in government agencies providing motorized vehicle tax services have been successfully developed.

show abstract

Comparison of PHP Programming Language with Codeigniter Framework in Project CRUD

Cited by 8 publications

References 0 publications

Stunting Early Warning Application Using KNN Machine Learning Method

Stunting Early Warning Application Using KNN Machine Learning Method

Digital Health Dashboards for Decision-Making to Enable Rapid Responses During Public Health Crises: Replicable and Scalable Methodology

Development of Client Server-Based Queuing Applications at The Samsat Gowa Office

Contact Info

Product

Resources

About