Reliability and Accuracy of Fingerprint Biometrics by the End-Users: Basis for Strategic Policy Formulation

International Journal of Recent Innovations in Academic Research This work is licensed under a Creative Commons Attribution 4.0 International License [CC BY 4.0] E-ISSN: 2635-3040; P-ISSN: 2659-1561 Homepage: https://www.ijriar.com/ Volume-9, Issue-4, October-December-2025: 141-156 141 Research Article Reliability and Accuracy of Fingerprint Biometrics by the End-Users: Basis for Strategic Policy Formulation Morris Ranniel P. Samson Master of Science in Criminal Justice (Specialization in Criminology), Graduate School, Philippine College of Criminology, 641 Sales Street, Sta. Cruz, Manila, Philippines Email: [email protected] Received: October 15, 2025 Accepted: November 04, 2025 Published: November 11, 2025 Abstract Fingerprint biometrics plays a vital role in security and identity management within higher education institutions, especially for attendance tracking and access control of personnel. Although it has been widely adopted, doubts still exist about its accuracy and reliability. This research examines the reliability and accuracy of fingerprint biometrics as perceived by end-users, providing a basis for strategic policy formulation. This research used a descriptive-comparative research design and quantitative research method, utilizing both descriptive and inferential statistical methods for analyzing the data. The study included 146 participants selected through stratified random sampling. The research found that fingerprint biometrics are usually reliable and accurate. However, factors such as device quality, software delay, and power interruption-related concerns can affect how well they work. Based on these findings, the researcher proposes the installation of a good backup power system to help prevent downtime during power interruption, maintain regular software updates and consistent implementation of the fingerprint biometric system for all user groups, and provide continuous institutional encouragement for its utilization as the primary tool for identification and attendance tracking. Keywords: Fingerprint Biometrics, Reliability, Accuracy, End-Users, Strategic Policy Formulation. Introduction With the digital age, strong and reliable security solutions are essential, particularly in the domain of individual privacy and data protection. Fingerprint biometrics has grown to become a significant method in this sector, bringing with it a unique combination of security and convenience. With biometric solutions more deeply embedded in everyday use, from cell phone unlocks to safeguarding sensitive financial transactions, their reliability and effectiveness need more scrutiny. Fingerprint biometrics relies on variations in the patterns of valleys and ridges on an individual's fingers. These patterns, in theory, are unique to each individual, and fingerprints have long been an attractive option for verification. Yet the implementation of fingerprint recognition systems presents grave doubts regarding their reliability, precision, and susceptibility. This study aims to evaluate the dependability and integrity of fingerprint biometrics in providing privacy and protection in numerous applications. It surveys the operation of such systems, looking at things from outside, the potential for human errors, and the constantly evolving technical toolkit required to crack the fingerprint dependability puzzle. The study also looks into the real-world applications of fingerprint biometrics across various industries, noting their strengths as well as weaknesses. Literature Review According to Lamin et al., (2021), recording students' attendance has been a significant concern at Kolej Universiti Poly-Tech Mara. However, monitoring attendance manually is a cumbersome issue for lecturers, as students tend to manipulate attendance by signing each other's attendance. It has been found that fingerprint biometrics can monitor attendance systematically and efficiently. This study aims to verify the students' attendance using fingerprint biometrics. The evolutionary prototyping model was used to develop the students' attendance system. Students must use a thumbprint using the fingerprint device installed in the International Journal of Recent Innovations in Academic Research 142 classroom to record their attendance. The fingerprint device captured their fingerprint images, which were then registered to the server for attendance. The implementation of fingerprint biometrics has helped lecturers monitor student attendance more systematically, efficiently, and ethically. Using the system embedded with biometrics, reporting on absenteeism is genuine and straightforward. Lecturers need to print out and take the necessary action. Therefore, fingerprint biometrics is valuable and helpful in keeping track of and managing the attendance of the students. According to Malik (2024), biometric authentication is a fast-growing, novel technology that makes the identity verification process secure and user-friendly with unique physiological and behavioral indicators. Integrating machine learning and artificial intelligence has made these systems more accurate and reliable. Hence, they can be used on mobile devices, banks, and border control since biometric authentication systems are beneficial; however, many risks exist, including privacy, data breaches, spoofing attacks, and regulatory issues. While these risks are unavoidable as more and more organizations are embracing biometric systems, it is only right that data protection is strong, that legal frameworks are abided by, and that the practice is ethical. According to Rahman (2021), the present is a revolutionary time of information and computer technology. Most of the work in daily life depends on computer applications. Traditional student attendance includes all the hassles of roll calling and the time-consuming process of students and teachers conducting classes in an institute. This time-consuming process is very dull for the students and teachers. Thus, a new and innovative approach is required to handle this issue. It motivates us to design a reliable system for student attendance. Biometric authentication systems are widely used for the unique identification of humans, like students, and mainly for the verification and identification of individuals. According to Blancaflor et al., (2024), integrating biometric technology for personal identification is of growing interest and an area of concern. Nevertheless, emerging technological integration emerges as a subject of academic interest and the evolving global market, with the Philippines being no exception. AI's growing misuse and development remain a threat to falsifying biometric data. While such technology is potentially destructive to an entity, embracing how tech will continue to evolve while preparing and mitigating the risks is ideal for thriving as an institution. According to Saul et al., (2023), the traditional method of taking attendance using paper sheets is prone to errors like impersonation, loss, or theft. To solve this issue, automatic attendance systems utilizing identification technology such as barcode badges, electronic tags, magnetic stripe cards, and biometrics have been implemented. Fingerprint identification depends on the uniqueness of fingerprints and consists of comparing two friction ridge impressions on human fingers or toes to ascertain whether they come from the same person. According to Dela Peña et al., (2024), biometric verification is becoming more common in airports to improve security and efficiency. While it offers significant benefits like accurate identification and easier passenger screening, it raises concerns about privacy and data security. The research looked into the use of biometric systems in Philippine airports, focusing on security benefits and privacy protection. A mixedmethods approach was used, which included passenger surveys, interviews with key stakeholders, and case studies of airports that use biometric technology. Theoretical Framework The theoretical framework of this study integrates several interrelated theories-Pattern Recognition Theory, Diffusion of Innovation Theory, Social Exchange Theory, Technological Determinism Theory, and the Unified Theory of Acceptance and Use of Technology (UTAUT)-to assess the reliability and acceptance of fingerprint biometrics. The pattern recognition theory posits that every observed item is stored as a “template” in long-term memory, allowing incoming sensory data to be compared against these templates to ensure accurate identification. This theory supports the idea that fingerprint biometrics function through a similar mechanism, where unique fingerprint patterns are matched against stored templates to confirm identity (de Paiva, 2009). The diffusion of innovation theory explains how new technologies, such as biometric systems, are adopted and spread among individuals and organizations. In the context of fingerprint biometrics, it considers factors International Journal of Recent Innovations in Academic Research 143 like perceived benefits, compatibility with existing systems, complexity, and trialability, which collectively influence the level of acceptance and rate of adoption among users (Rogers, 1962). Meanwhile, the social exchange theory provides insight into the decision-making process behind the implementation and acceptance of fingerprint biometrics. It emphasizes how individuals and organizations weigh perceived risks, such as privacy concerns, against perceived benefits, like enhanced security and efficiency. This balance between cost and reward determines trust and willingness to adopt biometric technologies (Cook and Rice, 2006). The technological determinism theory suggests that technological advancements significantly shape human thought, behavior, and societal structures. Applied to fingerprint biometrics, this theory underscores how emerging technologies can transform security practices, institutional policies, and social interactions by influencing how individuals relate to and depend on technology (McLuhan, 1962). Lastly, the unified theory of acceptance and use of technology (UTAUT) provides a comprehensive framework for understanding technology adoption. It identifies key determinants-performance expectancy, effort expectancy, social influence, and facilitating conditions-that affect users’ behavioral intentions and actual technology usage. This theory helps explain how various factors contribute to the acceptance and continued use of fingerprint biometric systems (Ayaz and Yanartaş, 2020). Together, these theories create a multidimensional foundation for examining both the technical reliability and the human acceptance of fingerprint biometric systems, emphasizing the interaction between technological capability, user perception, and societal adaptation. Conceptual Framework This study is guided by the input-process-output-outcome (IPOO) model, which serves as the conceptual foundation for systematically assessing and improving the fingerprint biometric system. The IPOO model ensures that every stage of the research-from data collection to outcome formulation-follows a structured and logical progression, aligning with the objectives of evaluating system reliability and user satisfaction. In the input phase, three primary components are examined: the end-users’ assessment of the fingerprint biometric system, their satisfaction level, and the challenges they encounter in its use. The analysis focuses on three core aspects-promptness of data, consistency of records and recordings, and durability-which collectively determine the system’s effectiveness and efficiency from the users’ perspective. Furthermore, the study evaluates the end-users’ satisfaction level, categorized into two groups: teaching personnel and non-teaching personnel, to provide a comparative understanding of their experiences with the system. The process phase involves the systematic procedures undertaken to collect, manage, and analyze the data. A structured survey questionnaire is utilized to gather information from the identified respondents. The collected data undergo statistical treatment to ensure objectivity, accuracy, and validity of the findings. This phase also includes data analysis and interpretation, identifying key trends, patterns, and relationships. Moreover, comparative analysis is performed between the two user groups to determine whether significant differences exist in their levels of satisfaction and perception of the system’s performance. The output phase translates the analyzed data into practical and actionable outcomes. These include the development of a strategic action plan, policy recommendations, and training programs designed to address the challenges identified and enhance the fingerprint biometric system’s overall performance. These outputs aim to strengthen both the system’s reliability and the users’ satisfaction by providing evidence-based solutions. Finally, the outcome phase represents the long-term impact of the study’s implementation. Expected outcomes include improved user satisfaction, enhanced system reliability and accuracy, and the formulation of informed strategic policies and implementations. These outcomes highlight the potential of user-centered analysis to guide technological and organizational improvements in biometric systems. Overall, the IPOO framework ensures that each stage of the study builds on the previous one, creating a coherent flow from input to outcome. This structured approach facilitates the generation of well-informed, sustainable solutions aimed at optimizing the performance, reliability, and acceptance of fingerprint biometric systems within institutional settings. International Journal of Recent Innovations in Academic Research 144 Significance of the Study The findings of this study are expected to provide valuable, multi-sectoral contributions centered on enhancing the reliability, security, and ethical adoption of fingerprint biometric systems. For public institutions, the research offers actionable insights for the government to improve the accuracy of national identification systems (like PhilSys) and guides law enforcement in balancing effective security with individual privacy protection. In the private sector, the study supports businesses in minimizing identity fraud and financial losses, while providing technology developers with empirical data crucial for refining algorithmic precision and reducing authentication errors. Critically, the results offer policymakers evidencebased guidance for establishing regulatory frameworks, standards, and privacy protections. Ultimately, this research enriches academic discourse by providing localized, empirical findings and promotes greater confidence and trust in technology-driven identification systems among the general public. Objectives of the Study General Objective This study aims to assess the reliability and accuracy of fingerprint biometrics as perceived by the end-users in higher education institutions. Specific Objectives  Specifically, the study seeks to: Assess the reliability and accuracy of the fingerprint biometric system in terms of:  Promptness of data  Consistency of records and recordings  Durability  Determine whether there is a significant difference in the assessment of end-users on the reliability and accuracy of the fingerprint biometric system when grouped according to:  Higher education institutions teaching personnel  Higher education institutions non-teaching personnel  Evaluate the level of satisfaction of end-users with the reliability and accuracy of the fingerprint biometric system in terms of:  Promptness of data  Consistency of records and recordings  Durability  Identify whether there is a significant difference in the level of satisfaction of end-users with the reliability and accuracy of the fingerprint biometric system in terms of:  Promptness of data  Consistency of records and recordings  Durability  Determine the challenges encountered by end-users in the utilization of the fingerprint biometric system in terms of:  Promptness of data  Consistency of records and recordings  Durability Methodology This study employed a quantitative, descriptive-comparative research design to assess the reliability and accuracy of fingerprint biometrics as perceived by end-users. The research was conducted in two Higher Education Institutions (HEIs) in Tarlac City, Philippines, that utilize biometrics for staff attendance and access control. The target population comprised teaching and non-teaching personnel (aged 25 years and older) who use the system, from which a total sample size of 146 respondents was selected using stratified random sampling. Data were collected using a self-structured questionnaire with a 4-point Likert scale; the instrument was validated by experts and confirmed for high internal consistency via Cronbach's alpha. Data analysis utilized descriptive statistics (median) to determine user assessment and satisfaction levels, while the Mann-Whitney U Test (chosen due to confirmed non-normality) was employed to determine the significant difference in assessment and satisfaction between the independent groups of teaching and nonteaching personnel. International Journal of Recent Innovations in Academic Research 145 Results and Discussions Table 1. End-users’ assessment of the reliability and accuracy of the use of fingerprint biometrics in terms of promptness of data. Promptness of data Teaching personnel Non-teaching personnel Overall Median Int. Median Int. Median Int. 1) The fingerprint biometrics device quickly processes my fingerprint without any delay. 4.00 SA 4.00 SA 4.00 SA 2) The fingerprint biometrics device verification is faster compared to manual methods such as Bundy clocks. 3.00 A 4.00 SA 4.00 SA 3) I don’t experience long queues because the fingerprint biometrics device scans fast. 4.00 SA 4.00 SA 4.00 SA 4) I don’t have to wait a long time for the fingerprint biometrics device to respond after scanning my fingerprint. 4.00 SA 4.00 SA 4.00 SA 5) I receive quick confirmation that my fingerprint has been accepted. 4.00 SA 4.00 SA 4.00 SA 6) The fingerprint biometrics device works well even in different weather or environmental conditions. 4.00 SA 4.00 SA 4.00 SA 7) The fingerprint biometrics device works quickly even during peak hours. 4.00 SA 4.00 SA 4.00 SA 8) The fingerprint biometrics device verifies my fingerprint quickly even when multiple users scan consecutively. 3.00 A 4.00 SA 4.00 SA 9) It only takes a few seconds to scan my fingerprint. 4.00 SA 4.00 SA 4.00 SA Overall 3.78 SA 4.00 SA 4.00 SA Legend: Strongly disagree (1.00-1.99), Disagree (2-2.99), Agree (3-3.49), Strongly agree (3.50-4) Table 1 presents the end-users' assessment of the reliability and accuracy of fingerprint biometrics in terms of promptness of data. The responses were collected from higher education institutions' teaching and nonteaching personnel who use fingerprint biometrics for attendance tracking and access control. The overall median for the end-users’ assessment of the reliability and accuracy of using fingerprint biometrics for both teaching and non-teaching personnel in terms of promptness of data from item 1 to item 9 is 4.00, interpreted as “Strongly Agree”. The median overall score of 4.00 for all items shows that respondents strongly agree that fingerprint biometrics are reliable and accurate regarding the promptness of data. For the overall median of item 1 to 9 responses from teaching personnel, the overall median reflects 3.78, interpreted as “Strongly Agree.” Moreover, for the overall median of items 1 to 9 from non-teaching personnel, the overall median garnered 4.00, interpreted also as “Strongly Agree.” These indicate that the users from both teaching and non-teaching personnel have a high confidence level in the fingerprint biometrics' ability to process data promptly and efficiently. The overall median result is consistent with earlier research results. Gabuya et al., (2022) established that the Biometric Attendance Monitoring System (BAM) used in CTU-Tuburan Campus tremendously increased time efficiency over traditional processes. This substantiates the current study's discovery that users think that the biometric system is quicker and more accurate when processing attendance than the manual method. Likewise, Maggay (2017) found that the use of a biometric attendance monitoring system (BAMS) at Cagayan State University–Lasam Campus minimizes the queuing time and improves the logging experience of the employees, which is the same in the present study, where end-users highly agreed with their assessment that the system provides prompt data. In addition, Jain et al., (2016) pointed out through their biometric study review that technology innovation had significantly improved the performance and speed of fingerprint recognition systems to capture real-time verification even in the presence of high user activity. International Journal of Recent Innovations in Academic Research 146 These findings, in addition to the findings in this study, further establish the application of biometric systems as a very effective and efficient approach to attendance monitoring and access management in institutions. Table 2. End-users’ assessment of the reliability and accuracy of the use of fingerprint biometrics in terms of consistency of records and recordings. Consistency of records and recordings Teaching personnel Non-teaching personnel Overall Median Int. Median Int. Median Int. 1) The fingerprint biometrics device always clocks my attendance without fail. 4.00 SA 4.00 SA 4.00 SA 2) The fingerprint biometrics device correctly identifies my fingerprint every time I use it and efficiently accommodates multiple fingers per user (e.g., the right thumb and left thumb of the teacher/instructor are registered in one device). 4.00 SA 4.00 SA 4.00 SA 3) The system logs match my actual log-in and log-out. 4.00 SA 4.00 SA 4.00 SA 4) The fingerprint biometrics device can scan my fingerprint even if there is a power interruption. 1.00 SD 1.00 SD 1.00 SD 5) I've never encountered a situation where the system mixed up my fingerprint with another person's. 4.00 SA 4.00 SA 4.00 SA 6) My attendance is recorded reliably even when I make use of different biometric scanners at work. 4.00 SA 4.00 SA 4.00 SA 7) The fingerprint biometrics match my profile without error. 4.00 SA 4.00 SA 4.00 SA 8) The fingerprint biometrics device provides the same correct output even if I swipe my fingerprint multiple times. 4.00 SA 4.00 SA 4.00 SA 9) I can rely on the fingerprint system to maintain my attendance records accurately and consistently in the long term. 4.00 SA 4.00 SA 4.00 SA Overall 3.67 SA 3.67 SA 3.67 SA Legend: Strongly disagree (1.00-1.99), Disagree (2-2.99), Agree (3-3.49), Strongly agree (3.50-4) Table 2 presents the end-users' assessment of the reliability and accuracy of fingerprint biometrics in terms of consistency of records and recordings. The responses were collected from higher education institutions teaching and non-teaching personnel who use fingerprint biometrics for attendance tracking and access control. The overall median for the end-users’ assessment of the reliability and accuracy of the use of fingerprint biometrics for both teaching personnel and non-teaching personnel in terms of consistency of records and recordings from item 1 to item 9 (except item 4) is 4.00, interpreted as “Strongly Agree”. The median overall score of 4.00 for all items shows that respondents strongly agree that fingerprint biometrics are reliable and accurate in terms of consistency of records and recordings. However, item 4 has the lowest median rating of 1.00 by both groups, which is interpreted as "Strongly Disagree”. This indicates the lack of capacity of fingerprint biometrics to scan when there is a power interruption in the locale. Apart from the exception of power-related concern, the consistent median value of 4.00 across most items indicates that end-users tend to find the system reliable and accurate in the consistency of records and recordings. For the overall median of item 1 to 9 responses from teaching personnel, the overall median reflects 3.67, interpreted as “Strongly Agree”. Moreover, for the overall median of Items 1 to 9 from non-teaching personnel, the overall median also garnered 3.67, interpreted as “Strongly Agree”. It indicates that both teaching and non-teaching personnel have a very low assessment for item 4, but apart from it, these results reflect that the user has a high level of confidence in the fingerprint biometrics' ability to process data promptly and efficiently, record consistently, reliably, and accurately. This also aligns with the study of Thakur and Vyas (2019), that biometrics are more sophisticated, advanced, and highly sensitive than ever before. They are used to protect businesses and citizens. Above all, biometrics work on the biological qualities of a person that cannot be duplicated. International Journal of Recent Innovations in Academic Research 147 Table 3. End-users’ assessment of the reliability and accuracy of the use of fingerprint biometrics in terms of durability. Durability Teaching personnel Non-teaching personnel Overall Median Int. Median Int. Median Int. 1) The fingerprint biometrics device works well even for long hours of use. 4.00 SA 4.00 SA 4.00 SA 2) The fingerprint biometrics device works well under extreme conditions (e.g., temperature, humidity). 4.00 SA 4.00 SA 4.00 SA 3) Physical wear and tear on the scanner are minimal even with continuous use. 4.00 SA 3.00 A 4.00 SA 4) The general design and structure of the biometric system contribute to its long-term durability. 4.00 SA 4.00 SA 4.00 SA 5) I've witnessed the device last for years without significant damage or repair. 4.00 SA 3.00 A 4.00 SA 6) The fingerprint biometric device withstands frequent pressing and scanning. 4.00 SA 4.00 SA 4.00 SA 7) The system components, such as the screen and sensor pad, remain intact and functional over time. 4.00 SA 4.00 SA 4.00 SA 8) The fingerprint biometrics device is durable enough to be utilized in schools or other busy areas. 4.00 SA 4.00 SA 4.00 SA 9) I have never seen the fingerprint biometrics device overheat while in use. 4.00 SA 4.00 SA 4.00 SA Overall 4.00 SA 3.78 SA 4.00 SA Legend: Strongly disagree (1.00-1.99), Disagree (2-2.99), Agree (3-3.49), Strongly agree (3.50-4) Table 3 presents the end-users' assessment of the reliability and accuracy of fingerprint biometrics in terms of durability. The responses were collected from higher education institutions teaching and non-teaching personnel who use fingerprint biometrics for attendance tracking and access control. The overall median for the end-users’ assessment of the reliability and accuracy of the use of fingerprint biometrics for both teaching personnel and non-teaching personnel in terms of durability from item 1 to item 9 is 4.00, interpreted as “Strongly Agree”. The median overall score of 4.00 for all items shows that respondents strongly agree that fingerprint biometrics are reliable and accurate in terms of durability. For the overall median of item 1 to 9 responses from teaching personnel, the overall median reflects 4.00, interpreted as “Strongly Agree”. Moreover, for the overall median of items 1 to 9 from non-teaching personnel, the median garnered 3.78, interpreted also as “Strongly Agree”. These indicate that respondents from both teaching and non-teaching personnel agree that the components associated with the hardware and software of the fingerprint biometrics are perceived to be exceptionally reliable and well-built, and can withstand different weather and environmental conditions. As users view fingerprint biometrics as long-lasting and ever-reliable through time, their adoption rate and continuous use of the technology become higher (Greenhalgh, 2020). Table 4. Difference in the assessment of the end-users on the reliability and accuracy of the use of fingerprint biometrics according to group. Mann-Whitney U test U statistic p Interpretation Promptness of data Mann-Whitney U 2402 0.447 No significant difference Consistency of records and recordings Mann-Whitney U 2354 0.341 No significant difference Durability Mann-Whitney U 2454 0.58 No significant difference Table 4 presents the significant differences in the assessment of the end-users on the reliability and accuracy of the use of fingerprint biometrics according to the group. The responses were collected from higher education institution teaching personnel and non-teaching personnel who use fingerprint biometrics for attendance tracking and access control. The Mann-Whitney U Test is used to determine whether there are significant differences in the assessments of end-users between teaching personnel and non-teaching International Journal of Recent Innovations in Academic Research 148 personnel. For the promptness of data, the computed U-value is 2402, and the p-value is 0.447. For the consistency of records and recordings, the U-value is 2354, and the p-value is 0.341. And for durability, the computed U-value is 2452, and the p-value is 0.58. For the promptness of data, the computed U-value is 2402 with a p-value of 0.447. Since the p-value is greater than 0.05, the result indicates that the difference is not statistically significant; thus, it fails to reject the null hypothesis H₀1. This means that there is no significant difference between the two groups of respondents in their assessment of the reliability and accuracy of fingerprint biometrics in terms of the promptness of data. Likewise, for the consistency of records and recordings, the computed U-value is 2354 with the p-value of 0.341. Again, since the p-value is greater than 0.05, the result indicates that the difference is not statistically significant; thus, it fails to reject the null hypothesis H₀1. This also means that there is no significant difference between the two groups of respondents in their assessment of the reliability and accuracy of fingerprint biometrics in terms of consistency of records and recordings. And lastly, for durability, the computed U-value is 2452 with a p-value of 0.58. Since the p-value is greater than 0.05, the result indicates that the difference is not statistically significant; thus, it fails to reject the null hypothesis H₀1. This means that there is no significant difference between the two groups of respondents in their assessment of the reliability and accuracy of fingerprint biometrics in terms of durability. These results indicate that both teaching and non-teaching personnel have the same agreement about the promptness, consistency, and durability of fingerprint biometrics. The fact that there are no statistically significant differences in all the variables indicates that the fingerprint biometric system is viewed equally across employee groups. The result of having the same agreement of assessment in the two groups is aligned by the study conducted by Maggay (2017). In her study on fully customized Biometric Attendance Monitoring System (BAMS) design and development at Cagayan State University–Lasam Campus, the system's functionality facilitated users of varied administrative and instructional positions to effectively input, manipulate, and retrieve data. This convenience and simplicity of use between different types of users translated to better work values that facilitated good governance. Likewise, in the current study, teaching and non-teaching personnel both showed a similar level of satisfaction and confidence in the system's dependability, demonstrating that technology is able to address diverse user groups' needs and facilitate efficient, precise attendance tracking irrespective of their roles. Similarly, the outcome is also supported by the study conducted by Gabuya (2022). Gabuya highlighted that biometric systems have continually maintained employee punctuality and offered proper attendance records. The convenience of daily application of the system and the potential for users with a few difficulties indicate high levels of satisfaction expressed in the present study. This adds credence to the reliability of fingerprint biometrics as a speedy and stable tool for following attendance. Table 5 presents the end-users' level of satisfaction with the reliability and accuracy of the use of fingerprint biometrics in terms of promptness of data. The responses were collected from higher education institutions teaching and non-teaching personnel who use fingerprint biometrics for attendance tracking and access control. The overall median for the end-users’ level of satisfaction with the reliability and accuracy of using fingerprint biometrics for both teaching and non-teaching personnel in terms of promptness of data from item 1 to item 9 is 4.00, interpreted as “Very Satisfied”. The median total score of 4.00 shows that respondents are very satisfied with the fingerprint biometrics being reliable and accurate regarding the promptness of data. For the overall median of item 1 to 9 responses from teaching personnel, the overall median reflects 4.00, interpreted as “Very Satisfied”. Moreover, for the overall median of items 1 to 9 from non-teaching personnel, the median garnered 3.89, interpreted also as “Very Satisfied”. These indicate that the users from both teaching and non-teaching personnel have a high level of satisfaction with the fingerprint biometrics' ability to process data promptly and efficiently. The satisfaction of respondents with the fingerprint biometrics being prompt is in agreement with the literature of Rivera (2021). Taking and maintaining the attendance of employees manually on a regular basis is a big activity that requires time. For this reason, an effective system was designed. The system was International Journal of Recent Innovations in Academic Research 149 designed and developed primarily to improve the monitoring of employees’ attendance and leave management through the use of biometric technology. It records the data of the employees, handles leave management, tracks employee attendance, and encourages participation through fingerprint recognition. The outcome shows that through the usage of the biometrics system, employees’ attendance has improved. Table 5. End-users’ level of satisfaction with the reliability and accuracy of the use of fingerprint biometrics in terms of promptness of data. Promptness of data Teaching personnel Non-teaching personnel Overall Median Int. Median Int. Median Int. 1) I am satisfied with how the fingerprint biometrics device quickly processes my fingerprint without any delay. 4.00 VS 4.00 VS 4.00 VS 2) I am satisfied with the use of a fingerprint biometrics device rather than manual methods because it is faster. 4.00 VS 4.00 VS 4.00 VS 3) I am satisfied with the fingerprint biometrics verification because it is faster and I don’t have to wait for a long queue. 4.00 VS 4.00 VS 4.00 VS 4) I am satisfied with how quickly the fingerprint biometrics device responds after scanning my fingerprint. 4.00 VS 4.00 VS 4.00 VS 5) I am satisfied with how quickly I received the information that my fingerprint has been accepted. 4.00 VS 4.00 VS 4.00 VS 6) I am satisfied with the fingerprint biometrics device because it works well even in different weather or environmental conditions. 4.00 VS 4.00 VS 4.00 VS 7) I am satisfied with the use of fingerprint biometrics devices because it works quickly even during peak hours. 4.00 VS 4.00 VS 4.00 VS 8) I am satisfied with how fast the system verifies my fingerprint even when multiple users scan consecutively. 4.00 VS 3.00 S 4.00 VS 9) I am satisfied with the time it takes for my attendance to be recorded. 4.00 VS 4.00 VS 4.00 VS Overall 4.00 VS 3.89 VS 4.00 VS Legend: Very dissatisfied (1.00-1.99), Dissatisfied (2-2.99), Satisfied (3-3.49), Very satisfied (3.50-4) Table 6 presents the end-users' level of satisfaction with the reliability and accuracy of the use of fingerprint biometrics in terms of consistency of records and recordings. The responses were collected from higher education institutions teaching and non-teaching personnel who use fingerprint biometrics for attendance tracking and access control. The overall median for the end-users’ level of satisfaction with the reliability and accuracy of the use of fingerprint biometrics for both teaching personnel and non-teaching personnel in terms of consistency of records and recordings from item 1 to item 9 (except item 4) is 4.00, interpreted as “Very Satisfied”. The median overall score of 4.00 for all items shows that respondents are highly satisfied that fingerprint biometrics are reliable and accurate in terms of consistency of records and recordings. However, item 4 had the lowest median rating of 1.00 by both groups, which is interpreted as "Very Dissatisfied". This indicates the lack of capacity of fingerprint biometrics to scan when there is a power interruption in the locale. Apart from the exception of power-related concern, the consistent median value of 4.00 (VS) across most items indicates that end-users are very satisfied with the consistency of records and recordings provided with fingerprint biometrics. For the overall median of item 1 to 9 responses from teaching personnel, the overall median reflects 3.67, interpreted as “Very Satisfied”. Moreover, for the overall median of items 1 to 9 from non-teaching personnel, the overall median also garnered 3.67, interpreted as “Very Satisfied”. These still indicate that the International Journal of Recent Innovations in Academic Research 156 6. Gabuya, Jr, A.Q., Zosa, L.T. and Miñoza, J.T. 2022. The performance of biometric attendance system (BAS): CTU-Tuburan Campus as case study. International Journal of Scientific and Research Publications, 12(7): 419-426. 7. Greenhalgh, T. 2020. Diffusion of innovation. In: The international encyclopedia of media psychology. 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