INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue X October 2025
Page 784
www.rsisinternational.org
A Web-Based Data Driven Analytics System for Income and
Operations Management Using Linear Regression for Modern
Concept Prints
Ace Dela Vega, Windyl Kier S. Aguilar, Rechel Anne D. Sidayon, Jade Mikhal P. Soriano, Gabby C.
Vargas, Mary Grace B. Baya
(SY 2025-2026) Arellano University, Pasig Campus
DOI: https://doi.org/10.51584/IJRIAS.2025.1010000062
Received: 22 October 2025; Accepted: 28 October 2025; Published: 06 November 2025
ABSTRACT
This project, titled “A Web-Based Data Driven Analytics System for Income and Operations Management Using
Linear Regression for Modern Concept Prints,” was developed to address the inefficiencies of manual income
tracking and operations management in small enterprises. Income management, which includes tracking
revenue, managing expenses, and ensuring profitability, is crucial for financial planning and long-term
sustainability. Operations management, which involves the efficient handling of day-to-day processes such as
task delegation, inventory monitoring, and order fulfillment, is equally essential for business optimization. When
these areas are not integrated or managed manually, it becomes difficult to control costs, optimize performance,
and make informed decisions.
This study follows an applied research approach, focusing on the development of a Web-Based System to solve
real-world business challenges faced by Modern Concept Prints, a local printing business. The business had been
relying on spreadsheets and verbal coordination for its operations, leading to frequent delays, inaccurate records,
and limited forecasting capabilities. To address these issues, the researchers designed and implemented a
centralized platform that automates key business processes, including Sales Monitoring, Inventory Management,
and Task Tracking, while utilizing Linear Regression for Income Prediction based on historical data. The system
also integrates Predictive Analytics to forecast future income, thus enhancing decision-making. The project
followed the Spiral Model as its software development methodology, allowing for iterative development,
continuous risk assessment, and frequent refinement of the system based on user feedback.
Developed using PHP, MySQL, HTML, CSS, and JavaScript, the system offers a dynamic, user-friendly
interface that supports real-time data analysis and visualization. Evaluation results, guided by ISO 25010 quality
standards, showed high satisfaction among both technical and user respondents in terms of System Usability,
Data Security, functionality, reliability, and security. The system significantly improved operational workflows,
reduced manual errors, and enhanced financial planning through automated income prediction and sales
monitoring. The project demonstrates how integrating automation, Predictive Analytics, Linear Regression, and
business management can help small businesses optimize decision-making, productivity, and long-term
sustainability. Future recommendations include adding accounting and payroll modules, mobile compatibility,
and advanced forecasting algorithms to further enhance scalability and performance.
Keywords: Web-Based System, Business Management, Income Prediction, Linear Regression, ISO 25010,
Spiral Model, Predictive Analytics, Inventory Management, Sales Monitoring, Task Tracking, Data Security,
System Usability
INTRODUCTION
Income and operations management are critical components for a successful business. Income management
ensures profitability by tracking revenue and expenses, while operations management focuses on the efficiency
of daily activities such as order processing, task delegation, and inventory monitoring. When handled manually,
these processes often result in inefficiencies and poor decision-making. As Gonzales (2020) emphasized, the
adoption of data-driven systems—particularly those utilizing predictive analytics—enables businesses to
forecast outcomes accurately and improve decision-making. Similarly, Jain and Chhabra (2016) noted that
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue X October 2025
Page 785
www.rsisinternational.org
integrating business management systems enhances sustainability and organizational performance through
automation and centralized data.
Small enterprises like Modern Concept Prints face significant challenges due to outdated manual processes.
Despite business growth and a wide customer base, the company still relies on Excel sheets and verbal
communication, causing delays, inaccurate records, and poor coordination. Del Rosario (2019) discussed that
many SMEs in the Philippines experience similar setbacks due to limited access to digital tools, which hinders
operational efficiency. In alignment with this, Osei and Boateng (2022) demonstrated that implementing web-
based management and forecasting systems can significantly improve financial monitoring and reduce human
errors.
To address these limitations, a web-based business management system is proposed to automate order tracking,
inventory control, and task assignment. The system will incorporate a linear regression model to forecast monthly
income based on historical sales data, as supported by studies from Zhang, Huang, and Li (2020), who found
that regression-based income prediction enhances planning accuracy for SMEs. According to Kumar and Lee
(2021), integrating machine learning models into small business ERP systems increases both productivity and
decision accuracy.
This study aims to show how a web-based system with predictive analytics can improve the operational
efficiency and income forecasting of Modern Concept Prints. By centralizing these processes, the system is
expected to reduce errors, enhance productivity, and provide visual insights for better management decisions.
Furthermore, compliance with ISO/IEC 25010:2011 standards ensures that the system upholds quality attributes
such as usability, reliability, and security, as discussed by Sharma and Rathore (2021) and Al-Qutaish (2010).
Scope
This research centers on designing and creating a web-based management system for the printing business,
specifically customized for Modern Concept Prints. Its main purpose is to automate and enhance multiple manual
business processes like task assignments, sales tracking, inventory monitoring, and revenue forecasting by
leveraging machine learning, specifically the linear regression algorithm. The system seeks to optimize internal
processes, improve data precision, and facilitate better decision-making by offering cohesive tools for handling
daily activities and financial strategizing The main functions and coverage of the system are as follows:
Manage order records, production schedules, and customer information.
Track orders, monitor inventory, and oversee business activities in real time.
Upload design files and update progress reports for ongoing projects.
Generate analytical reports such as sales summaries, income forecasts, and visual while integrating
charts using linear regression results.
Observe seasonal order patterns and classify customer types to assist in strategic planning.
The primary focus of this study is to offer a digital solution that enhances workflow efficiency and incorporates
predictive analytics for financial forecasting. This system is meant for internal implementation at Modern
Concept Prints and aims to streamline its processes while establishing a foundation for data-driven business
management.
LIMITATION
The developed Web-Based Business Management System for Modern Concept Prints exhibits strong
functionality in automating processes and supporting data-driven decisions. However, it is specifically designed
for the internal operations of Modern Concept Prints, which limits its adaptability for businesses with different
workflows and operational structures. The system’s income forecasting feature depends solely on historical sales
data, without considering external factors such as inflation, market trends, and supply chain disruptions that may
influence accuracy. In addition, it currently lacks integration with third-party accounting or Point-of-Sale (POS)
systems, restricting seamless data exchange and broader usability.
Moreover, the system’s functionality is further constrained by the absence of mobile accessibility and real-time
payment processing, which limits flexibility for users requiring remote access or quick transaction capabilities.
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue X October 2025
Page 786
www.rsisinternational.org
Its predictive capacity remains confined to linear regression, without the use of more advanced artificial
intelligence algorithms that could enhance analytical depth and forecasting accuracy. These technical and
functional limitations define the current development scope, emphasizing the system’s focus on automation and
operational efficiency. Future improvements are recommended to enhance interoperability, mobile accessibility,
and the incorporation of advanced AI-driven analytics to expand the system’s reach and overall performance.
THEORETICAL FRAMEWORK
This study is anchored on theories that explain how automation, data analysis, and predictive modeling contribute
to efficient business management and decision-making. The Systems Theory, Data-Driven Decision-Making
(DDDM), and Predictive Modeling using Linear Regression serve as the foundational concepts of the developed
system.
The Systems Theory views an organization as a collection of interconnected components that function together
toward a common goal. In the context of Modern Concept Prints, this theory supports the integration of various
operations—such as task management, order tracking, and sales monitoring—into a unified platform to promote
coordination, efficiency, and streamlined workflows.
The Data-Driven Decision-Making (DDDM) theory emphasizes the importance of basing business decisions on
factual data rather than intuition. By collecting, analyzing, and visualizing operational data, the system enables
Modern Concept Prints to plan effectively, allocate resources strategically, and make informed decisions
grounded in accurate insights.
The Predictive Modeling using Linear Regression theory explains how historical data can be analyzed to forecast
future trends. Through this approach, the system predicts income and identifies sales patterns, helping the
business anticipate demand and develop proactive financial strategies.
CONCEPTUAL FRAMEWORK
The conceptual framework of the Web-Based Business Management System for Modern Concept Prints
illustrates how operational, sales, and employee data are processed through automated workflows and predictive
models to support data-driven management. The framework follows the Input–Process–Output (IPO) Model,
demonstrating the systematic flow from data collection to the generation of business insights.
Figure 1: Conceptual Framework
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue X October 2025
Page 787
www.rsisinternational.org
The conceptual framework of the Web-Based Data-Driven Analytics System for Income and Operations
Management is structured according to the Input–Process–Output (IPO) Model, which illustrates the systematic
progression of the system from data collection to the generation of outputs.
Input
The input phase includes the collection of all vital data and resources necessary for the system’s creation and
functionality. This encompasses employee details, designated tasks, client information, order and inventory
records, uploaded design files, and historical monthly sales figures. These inputs form the basis for the system's
automation and predictive analytics capabilities.
Process
The processing stage emphasizes the transformation of the gathered data into valuable and functional
components using automation and data analysis. The system handles information by overseeing tasks,
monitoring inventory, logging sales, and producing reports. It also incorporates a linear regression algorithm to
evaluate historical sales data and predict future revenue, while data visualization tools display outcomes through
graphs and charts, facilitating easier analysis and decision-making.
Output
The output phase signifies the completed system and its expected advantages. The created web-based platform
offers a centralized management system that enhances workflow, boosts productivity, and minimizes human
errors. It generates structured reports, provides real-time updates, and delivers precise income projections that
empower Modern Concept Prints to make informed, data-driven business decisions.
Significance of the Study
The research is significant because it seeks to improve the operational effectiveness and financial oversight of
Modern Concept Prints by creating a web-based business management system that incorporates data analytics
and predictive modeling.
To Business Owners and Administrators: The system provides a centralized platform for managing
employees, orders, inventory, and sales. It enables owners to monitor business performance in real time,
forecast income trends, and make well-informed operational decisions.
To Staff and Employees: Organized task assignments and progress tracking help employees work
efficiently and reduce errors. The system improves coordination, communication, and overall workflow
within the team.
To Clients: The system improves service delivery through better order tracking and timely updates. Clients
experience faster transactions, greater accuracy, and higher satisfaction.
To Future Researchers and Developers: This study serves as a guide for developing future business
management systems with data analytics and machine learning. It may be expanded with advanced features
like accounting integration, mobile access, and enhanced predictive tools.
REVIEW OF RELATED LITERATURE
According to Zhang et al. (2020): Examined the integration of machine learning, particularly linear
regression, into business management systems for SMEs. Their findings showed that using historical sales
and income data allows businesses to generate accurate forecasts, identify operational inefficiencies early,
and enhance inventory control.
As stated by Kumar and Lee (2021): Discovered that ERP systems enhanced with linear regression
algorithms improve income prediction and automate the analysis of customer behavior, seasonal demand,
and expenditure trends, supporting more informed financial decisions.
As emphasized by Patel and Singh (2021): Developed a cloud-based analytics platform for apparel SMEs
in India. This platform improved revenue prediction accuracy by 30% and reduced inventory losses by
20%, demonstrating the value of predictive analytics in small business operations.
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue X October 2025
Page 788
www.rsisinternational.org
As highlighted by Osei and Boateng (2022): Designed a web-based forecasting platform for logistics SMEs
in Ghana. This system incorporated linear regression and visualization tools, leading to a 25%
improvement in prediction accuracy and more efficient budget allocation.
As pointed out by Del Rosario (2019): Highlighted the importance of digital transformation and predictive
modeling tools for MSMEs in the Philippines, enabling businesses to make informed financial decisions,
manage inventory efficiently, and reduce operational risks.
According to Gonzales (2020): Noted that the adoption of data-driven strategies enables microenterprises
to quickly respond to market fluctuations, improve workflow coordination, and maintain competitiveness
in dynamic industries.
As identified by Reyes and Santos (2022): Developed a web-based financial management system for a
local printing business, utilizing linear regression to forecast income with 85% accuracy, which improved
financial planning and operational performance.
In the study by Dela Cruz and Villanueva (2021): Created a similar system for tarpaulin printing that
improved production scheduling and reduced material waste by using predictive analytics to optimize
resources.
Synthesis
The literature and studies reviewed collectively highlight the significance of incorporating digital systems and
predictive analytics to enhance business management and financial decision-making processes. Both
international and local research concur that machine learning, especially linear regression, is crucial for
improving the accuracy of income forecasts and optimizing business operations. Globally, research points out
that predictive tools enable small and medium enterprises to foresee financial trends, improve inventory
management, and proactively react to market changes. These technologies revolutionize conventional business
methods into efficient, data-driven practices that reduce human error and boost productivity.
On a local level, studies concerning Filipino micro, small, and medium enterprises (MSMEs) reveal an increasing
transition towards digital transformation as a vital element for gaining a competitive edge. Research indicates
that web-based systems assist business owners in managing their sales, inventory, and financial performance
more efficiently. By embracing automation and analytics, local SMEs are empowered to make informed
decisions, allocate resources effectively, and maintain operational consistency even in periods of high demand.
Nonetheless, while these systems offer considerable benefits, most local implementations are confined to basic
forecasting tools and lack sophisticated predictive modeling capabilities.
This shortfall emphasizes the necessity for initiatives like the Web-Based Data-Driven Analytics System for
Modern Concept Prints, which merges conventional management practices with contemporary machine learning
techniques. By utilizing a linear regression model, the system improves financial forecasting and operational
effectiveness, allowing small businesses to operate in a more intelligent and competitive manner. In summary,
the synthesis of related literature supports the objective of the project—to encourage a more data-driven,
automated, and sustainable method of managing business income and operations.
METHODOLOGY OF THE STUDY
This research utilizes an Applied Research Design aimed at creating a web-based data analytics platform to
improve income and operational management for Modern Concept Prints. Its goal is to develop a practical digital
tool that automates essential processes and incorporates predictive analytics to enhance decision-making and
financial planning.
The study engages the owner, employees, and production staff, selected through purposive sampling to gather
perspectives from those directly involved in the daily operations. Data was obtained through structured
interviews and direct observations, which highlighted workflow challenges and informed the system’s design
and development. User feedback collected during evaluation and testing was utilized to measure usability and
functionality, with all processes conforming to ethical guidelines and the Data Privacy Act of 2012.
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue X October 2025
Page 789
www.rsisinternational.org
Figure 2: SDLC Spiral Model
Figure 2 is the methodology employs the Spiral Model of the System Development Life Cycle (SDLC), which
highlights iterative development, risk management, and ongoing feedback from stakeholders. This approach is
ideal for projects that incorporate analytics and machine learning elements, as it permits adaptable enhancements
after every cycle. Every iteration comprises planning, risk assessment, engineering, and evaluation, guaranteeing
that the system gradually aligns with the operational requirements of Modern Concept Prints.
The design of the database is arranged to effectively manage and organize crucial business information, including
employee profiles, client orders, inventory records, and sales data. It guarantees data integrity, scalability, and
security while facilitating key functionalities like order tracking, income monitoring, and income prediction
based on linear regression.
The database defines clear relationships among entities—employees, orders, inventory, and administrators—to
ensure smooth data flow and prevent redundancy. The next illustration shows the system’s overall structure and
interactions.
Figure 3: Context Diagram
Figure 3 illustrates the interactions between primary users, including administrators, employees, and clients,
with the system. These interactions enable the system to facilitate real-time data management, coordination of
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue X October 2025
Page 790
www.rsisinternational.org
tasks, and financial forecasting, thereby ensuring effectiveness and dependability throughout all business
processes.
Respondents of the Study
The research consists of two primary categories of participants: user respondents and technical respondents. User
Respondents – This category contains 50 individuals, comprising marketing analysts, students, and business
professionals. They were selected based on their knowledge of business systems and their capacity to provide
insightful feedback as end-users. Their assessment concentrated on the system’s usability, functionality, and
overall user experience. Technical Respondents – This group also encompasses 50 participants, made up of IT
specialists such as developers, programmers, and system analysts. They evaluated the system from a technical
viewpoint, focusing on aspects such as performance, reliability, maintainability, and security. In total, 100
participants took part in the study, equally divided between the two categories. The participants were selected
through simple random sampling, and the sample size was calculated using Slovin’s formula to guarantee
representativeness and precision.
Development and Evaluation Procedure
The development of the Web-Based Business Management System for Modern Concept Prints utilized various
programming languages, frameworks, and software tools to ensure functionality and responsiveness. The system
was developed using PHP for backend operations, MySQL for database management, and Bootstrap 5 for a
responsive interface. Visual Studio Code served as the main code editor, while GitHub was used for version
control. Font Awesome and JavaScript enhanced the system’s design and interactivity. The Spiral Model guided
the development and testing phases, allowing iterative improvement through Unit, Integration, and System
Testing to ensure reliability and performance.
The evaluation focused on criteria from the ISO 25010 Quality Model, which includes:
Functionality – The system’s ability to perform its intended features accurately.
Usability – Ease of use and user satisfaction.
Performance Efficiency – The system’s capability to provide appropriate performance relative to the
amount of resources used.
Security – Protection of user data from unauthorized access.
Overall Satisfaction – The general satisfaction of users with the system’s performance and features.
These evaluation procedures ensured that the final version of the system met quality standards, operated
efficiently, and effectively addressed the operational challenges faced by Modern Concept Prints.
Data Analysis Plan
The primary research instrument was a survey questionnaire. The researchers used weighted mean as a statistical
method to evaluate the system in accordance with the ISO/IEC 25010 Software Quality Model. The criteria for
evaluation included Functional Functionality, Usability, Performance Efficiency, Security, and Overall
Satisfaction. Frequency Percentage Distribution was employed to break down respondents' answers and the
weighted mean was used to assess the overall effectiveness of the system. A four-point Likert scale, ranging
from 1 (Strongly Disagree) to 4 (Strongly Agree), was used to gauge user satisfaction and system quality in
alignment with the ISO 25010 characteristics. This approach enabled a comprehensive evaluation of the system's
performance and user satisfaction.
The System
The system outputs include comprehensive income forecasts that enable Modern Concept Prints to anticipate
future sales and revenue trends. It also provides detailed analytics on customer orders, printing demand, and
seasonal variations in business activity. Administrators and staff have access to predictive reports and interactive
dashboards that promote data-driven decision-making and efficient workflow management. Additionally, the
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue X October 2025
Page 791
www.rsisinternational.org
system delivers actionable insights for resource allocation, inventory control, and performance enhancement.
Overall, these outputs significantly contribute to improving operational efficiency, accuracy, and business
growth for Modern Concept Prints.
The following figures present the key system interfaces and output features developed for the Web-Based
Business Management System of Modern Concept Prints:
Figure 4: Order Management Page
The Order Management Interface allows staff to add, view, and update customer orders in real time. It includes
search and filter options for easy tracking of order progress and completion status. The interface presents a
structured layout that ensures accurate recording of transactions and minimizes delays in processing client
requests.
Figure 5: Analytics Dashboard Page
The Analytics Dashboard Interface provides a visual summary of the company’s operational data, such as total
sales, inventory levels, and income predictions generated through Linear Regression. It features interactive charts
and graphs that help the admin analyze performance trends, supporting better business planning and decision-
making.
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue X October 2025
Page 792
www.rsisinternational.org
Figure 6: Sales Summaries
This presents the Sales Summaries section of the system. It provides an overview of total monthly and annual
sales, including completed and pending transactions. The section displays summarized sales data to help
administrators quickly assess the overall business performance and track income trends over time.
Figure 7: Income Forecasts
This shows the Income Forecasts section of the system. It presents predictive results generated through linear
regression, allowing users to anticipate future income based on historical data. This feature helps the business
make informed financial decisions and plan for future sales growth.
Assessment: Summary of Respondents on the System
The following tables present the distribution of respondents with their corresponding size (n) and percentage.
The consolidated summary of responses from both users and technical participants is also shown. The assessment
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue X October 2025
Page 793
www.rsisinternational.org
follows the ISO/IEC 25010 Software Quality Model, which measures the system’s overall effectiveness and user
satisfaction based on the gathered feedback from staff and technical evaluators of Modern Concept Prints.
Table 1. Distribution of Respondents
Respondents
Size (n)
Percentage
Users
30
60%
Technical
20
40%
Total (n)
50
100%
The table shows the total number and percentage of respondents who participated in the evaluation. Out of 60
participants, 30 are user respondents, representing 60% of the total, while 20 are technical respondents, making
up 40%. This distribution ensures that the evaluation results reflect both the user experience and the technical
assessment of the system’s performance and quality.
Table 2: Summary & Comparison of Evaluations of Respondents
Criteria (ISO 25010)
Respondents (50)
Users (30)
Technical (20)
WM
VI
WM
VI
1. Functionality
3.73
Agree
3.81
Agree
2. Usability
3.72
Agree
3.78
Agree
3. Performance Efficiency
3.68
Agree
3.73
Agree
4. Security
3.68
Agree
3.76
Agree
5. Overall Satisfaction
3.78
Agree
3.76
Agree
Overall Average Mean
3.72
Agree
3.77
Agree
Table 2 presents the summarized comparison of evaluations based on the ISO/IEC 25010 software quality
standards. The results show that user respondents obtained an overall average mean of 3.72, interpreted as Agree,
while technical respondents achieved an overall average mean of 3.63, also interpreted as Agree. Among the
evaluated criteria, Functionality received the highest rating from both users (3.73) and technical respondents
(3.78), indicating that the system performs its intended functions effectively. On the other hand, Security
received the lowest mean for both groups, suggesting that while the system is generally secure, there is still room
for improvement to further strengthen data protection and system safety. Overall, both user and technical
respondents agreed that the Modern Concept Prints Web-Based Business Management System meets the ISO
25010 software quality standards, proving its functionality, usability, and overall reliability in supporting internal
business operations.
Ethical Considerations
The study guarantees that all data gathered from respondents are treated with strict confidentiality and integrity.
Personal information is safeguarded, and no identifying details are shared without the participant’s permission.
The research upholds voluntary participation, allowing respondents to withdraw at any point without facing any
consequences. Proper data protection practices are implemented to avoid unauthorized access or misuse of
information. Lastly, the results are presented truthfully and accurately, ensuring that no manipulation or bias
affects the credibility and reliability of the study.
Summary
The evaluation results show that the developed Web-Based Business Management System for Modern Concept
Prints effectively meets the ISO/IEC 25010 software quality standards.
Based on the assessment, user respondents obtained an overall average mean of 3.72, while technical
respondents achieved 3.63, both interpreted as Agree. Among all the criteria, Functionality received the highest
mean score from technical respondents, indicating that the system performs its intended functions efficiently.
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue X October 2025
Page 794
www.rsisinternational.org
On the other hand, users rated Overall Satisfaction the highest, suggesting that they are pleased with the system’s
performance and usability. Although the Performance Efficiency and Security criteria received slightly lower
means, these still fall under the “Agree” interpretation, showing that the system performs well and maintains
data protection standards.
Overall, both groups of respondents confirmed that the system is functional, user-friendly, and reliable in
supporting Modern Concept Prints’ internal business processes.
CONCLUSION
Based on the results of the system evaluation using the ISO/IEC 25010 software quality model, it can be
concluded that the developed Web-Based Business Management System for Modern Concept Prints effectively
meets the standards of functionality, usability, performance efficiency, and security. The evaluation results from
both user and technical respondents indicate that the system performs efficiently and provides a satisfactory user
experience. Its functionality supports key business operations such as sales recording, order monitoring, and
inventory tracking, which help streamline internal processes. The high usability rating reflects that users find the
system intuitive and easy to navigate, while the overall satisfaction rating confirms that its performance aligns
with user expectations. Although the system achieved positive feedback across all criteria, performance
efficiency and security were identified as areas for further enhancement to ensure optimal reliability and
protection. Overall, the study concludes that the developed system is functional, user-friendly, and reliable,
making it an effective tool for managing the internal operations of Modern Concept Prints and contributing to
improved business management and operational productivity.
RECOMMENDATION
It is recommended that future researchers and developers continue to enhance the Modern Concept Prints Web-
Based Business Management System to improve its overall functionality, scalability, and efficiency.
Organizations should prioritize maintaining accurate data management and continuous system optimization to
ensure reliable and secure performance. Respondents emphasized that ISO standards—particularly functionality,
performance efficiency, and security—must remain central to guarantee the system’s dependability and user
protection. Future development may focus on expanding the system’s capabilities for multi-business
applications, making it adaptable to various industries and workflows. Additionally, refining the income
prediction feature by incorporating external factors such as inflation rates, market fluctuations, and supply chain
conditions will enhance the accuracy and reliability of its forecasts.
Moreover, it is strongly encouraged to integrate third-party accounting software, Point-of-Sale (POS) systems,
and payment processors to achieve seamless financial management and interoperability. Incorporating mobile
and offline accessibility or developing a dedicated mobile application will allow users to monitor operations and
access data conveniently anytime and anywhere. Implementing real-time payment processing and exploring
advanced machine learning algorithms beyond linear regression can further improve analytical precision and
predictive depth. Continuous system enhancement guided by Agile methodology will ensure adaptability to
evolving business needs and technological trends. Finally, collaboration between academic institutions and
business organizations is recommended to refine the system, broaden its application, and ensure long-term
sustainability and user satisfaction.
REFERENCES
1. Al-Qutaish, R. E. (2010). Quality Models in Software Engineering Literature: An Analytical and
Comparative Study. Journal of American Science, 6(3), 166–175.
2. Dela Cruz, J. R., & Villanueva, M. L. (2021). Development of a Forecasting and Inventory Management
System for a Tarpaulin Printing Business [Undergraduate thesis, University of Santo Tomas].
3. Del Rosario, M. (2019). Digital Tools and Sustainability for SMEs in the Philippines. Philippine Journal
of Business and Development, 11(1), 56–68.
4. Gonzales, R. (2020). Data-Driven Systems for Microenterprises: The Rise of Predictive Analytics in
Philippine Business Operations. Journal of Southeast Asian Business Studies, 8(2), 101–115.
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue X October 2025
Page 795
www.rsisinternational.org
5. ISO/IEC 25010:2011. (2011). Systems and Software Engineering — Systems and Software Quality
Requirements and Evaluation (SQuaRE) — System and Software Quality Models. International
Organization for Standardization. Retrieved from https://www.iso.org/standard/35733.html
6. Jain, R., & Chhabra, A. (2016). Business Management System: A Tool for Sustainable Improvement.
International Journal of Management Research, 5(4), 12–20.
7. Kotu, V., & Deshpande, B. (2019). Predictive Analytics and Data Mining: Concepts and Practice with
RapidMiner (2nd ed.). Morgan Kaufmann.
8. Kumar, V., & Lee, H. (2021). Smart ERP: Integrating Machine Learning with Enterprise Resource
Planning for Small Businesses. International Journal of Data Science and Business Intelligence, 6(4),
189–203.
9. Laudon, K. C., & Laudon, J. P. (2020). Management Information Systems: Managing the Digital Firm
(16th ed.). Pearson.
10. Modern Concept Prints. (2025). Company Operational Workflow and Business Process Documentation.
Internal document.
11. Osei, E., & Boateng, K. (2022). Web-Based Financial Monitoring and Forecasting System for Logistics
SMEs in Ghana. African Journal of Information Systems and Management, 14(1), 67–80.
12. Patel, R., & Singh, M. (2021). A Cloud-Based Predictive Inventory and Income Tracking System for
Apparel SMEs. International Journal of Emerging Technologies in Computing, 18(2), 112–125.
13. Pressman, R. S., & Maxim, B. R. (2020). Software Engineering: A Practitioner’s Approach (9th ed.).
McGraw-Hill Education.
14. Reyes, C., & Santos, A. (2022). Design and Implementation of a Web-Based Financial Management
System with Predictive Analytics for Small Print Businesses [Undergraduate thesis, Polytechnic
University of the Philippines].
15. Sharma, M., & Rathore, S. S. (2021). Evaluation of Usability and Performance of Web-Based
Applications Using ISO/IEC 25010. International Journal of Computer Applications, 183(26), 25–31.
16. Zhang, L., Huang, Y., & Li, J. (2020). Forecasting Enterprise Income Using Machine Learning Models:
A Case Study on Web-Based Management Systems. Journal of Business Analytics, 12(3), 245–258.
