A proposal for the automation of attendance system

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A proposal for the automation of attendance system

  1. 1. A R e s e a r c h P a p e r P r e s e n t e d t o t h e F a c u l t y o f S a n P e d r o C o l l e g e o f B u s i n e s s A d m i n i s t r a t i o n Albert Joseph O. Aligonero Joel Jr. P. Pinas Randell E. Octavo Mark Enley Remoquillo
  2. 2. The Military  Foreign military bases initially used this modern technology in controlling access to their high- security facilities.
  3. 3. Business  It has been opened for public use and is now being developed for business such as communications, networking, e- commerce, manufacturing and retail establishments.
  4. 4.  This research paper aims to analyze the possibility of introducing a similar system for the personnel and customer management of Laguna Northwestern College.
  5. 5.  Biometrics and Magnetic Coding are automated attendance systems which are useful in obtaining comprehensive attendance information for colleges and universities
  6. 6. Difference between manual and automated attendance  This process takes about 5-10 minutes of their meetings or approximately 10-20 minutes for a 3-hour subject. With the manual attendance system, roll-call already consumes 35-70 minutes of his one week class schedule.
  7. 7. Attendance Process in S-AMS server for automated attendance in each subject Effective and efficient way to monitor student’s attendance LNC Students INPUT OUTPUTPROCESS BENEFITS
  8. 8. Attendance Process using E-AMS server for automated attendance in working hours Improvement in payroll process for employees LNC Employees INPUT OUTPUTPROCESS BENEFITS
  9. 9. Tony Mansfield  according toTony Mansfield, millions of times easier, and requires only that your facial geometry match the photograph recorded on your ID voucher (whether a passport or an ID card or a biometric visa) or that your fingerprints match the templates recorded on the voucher that you proffer to an immigration control officer, for example, or to a bank manager, to underpin your transactions and interactions with them.
  10. 10.  Identification is the job of proving that each person has one and only one entry on the population register. Professor John Daugman, the father of modern biometrics, inventor of iris recognition
  11. 11.  How to enhance and develop the attendance and payroll process of Laguna Northwestern College?
  12. 12. Financing Implementation Compatible Eco Friendly
  13. 13.  This study hypothesizes that there is no significant difference between the automated attendance system and manual attendance for students and employees of Laguna Northwestern College
  14. 14. Researchers LNC admin School Professors SchoolAccounting department Students
  15. 15.  The scope of the study covers the introducing LNC’s attendance management system from manual to automated system. The researchers only include the study of how this system benefits the attendance management of students of LNC.  The research has several limitations that must be acknowledged.This Study provided little information that does not include the program for the biometric hardware and presenting an actual biometric machine including its cost, capacity and usage of school facilities and other expenses.
  16. 16. Chapter 2
  17. 17. • Originating in criminology, biometric technology has matured over the years with applications in diverse disciplines. However, its use in business and accounting is still in its infancy, and many issues about its role in information systems security are unresolved. Akhilesh Chandra andThomas G. Calderon from the book “Journal of Information Systems” Published on November 1, 2003
  18. 18.  The purpose of the study is to assess the feasibility of fingerprint, iris and face recognition technologies for these applications, to identify unknowns and the risks associated with the use of biometrics in such a national identity scheme, and to make recommendations for how some of these risks might be addressed should such a scheme proceed.  Tony Mansfield and Marek Rejman – Greene on the Feasibility Study on the Use of Biometrics in an Entitlement Scheme
  19. 19. • The system is remotely operated and is powered by a local power source such as an outlet in an office building.GlobeTelecom provides the wireless service and the kiosk is equipped with RFID recognition. It also has a fingerprint scanner to verify the identity of their members, which works in tandem with an electronic card reader.  Mona Green, Blogger at BiometricupdateGSIS
  20. 20.  ” RFID-based interaction into the mix are very relevant in everyday transactions. Most importantly, (from the point of view of enabling biometric authentication) each kiosk supports fingerprint-based biometric authentication.
  21. 21.  Based on the research, the possible benefits of the study would be  increasing the security of the school  Decreasing the scenarios of student having proxy on written attendance,  Reduce human error
  22. 22. T he main focus of this chap ter is the method and p rocedures that were us ed to do this res earch. It cons is t the res earch des ig n us ed and the s ources of data. Next is the res pondents of the s tudy and the s amp ling and s amp ling technique us ed It s tarted by p res enting the p op ulation of the s tudy and followed by the s amp ling p rocedures in the res earch. T he s econd s ection dis cus s ed on ins trumentation for the s tudy how the data was collected in order to analyze the finding from the res earch
  23. 23. This study used quantitative methods involving survey questionnaires to collect the quantitative data. The survey is a very valuable tool for assessing opinions and trends even on a small scale such as government or small businesses.
  24. 24. Gender Male/Female Age 17 - 23 Civil Status Any Year Level 1st – 4th year
  25. 25. C O U R S E S A c c o u n t a n c y C o m p u t e r S t u d i e s E n g i n e e r i n g N u r s i n g B u s i n e s s A d m i n i s t r a t i o n P s y c h o l o g y H R M / H R S E d u c a t i o n P h y s i c a l T h e r a p i s t
  26. 26. Departments Population Sample Percentage Accountancy 196 22 13% Computer Studies 203 22 13% Engineering 120 14 8% Nursing 187 20 12% Business Administration 154 17 10% Psychology 109 12 7% HRM/HRS 165 19 11% Education 184 20 12% Physical Therapist 197 21 13% Total 1515 170 100%
  27. 27. Where: n = sample size N = total population e = margin of error Random Sampling method is used in determining the sample size
  28. 28. Questionnaire is the main tool of the collection data from the respondents

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