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Independent Study / Student Projects Independent Pathway Scheme

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Many students have a passion for realizing great works that are contested at the international level or works of innovative ideas. Independent Study/Project is one of the MBKM activities that are present to accommodate this. Independent Study/Project (PIM) is a form of learning that accommodates the activities of students who want to realize great works of innovative ideas. This activity is carried out outside the lecture class, but is still recognized as part of the lecture. Some of the recognitions given by the Study Programme to students who carry out this activity are:

  1. Equalization of Courses;
  2. Student Portfolio Points; and
  3. Certificate of Companion Diploma (SKPI), Financial Award*, and Charter Award or Certificate.

Video link: https://youtu.be/UggSsnMe9vY 

*Financial provision through participation in independent lecturer research or lecturer research group research.

Proposed Independent Study/Project Student Independent Pathway Scheme Even Semester 2021/2022

The opening of registration for the proposed Student Independent Study/Project (PIM) Independent Pathway Scheme for Computer Science Study Program has been carried out at the beginning of the even semester 2021/2022. This activity is part of the MBKM implementation. Registration is open for students who are already in their 5th semester. Students participate in the selection of PIM proposals by sending PIM proposals and following proposal presentations.

In the even semester of 2021/2022, the Computer Science study program received several PIM proposals. The proposals that were accepted and passed the selection to be implemented during the even semester of 2021/2022 are as follows:

TeamHead TimProject Title
CYBERGede Beny IndrawanSecurity Network Design Using PSAD With Fwsnort and Honeypot at UPTTIK Universitas Pendidikan Ganesha.
BEATERAndi Muh. Richvan JunaidServer Room Monitoring Using Server Room Information System (SIRUSERV).
INSYSKadek Utari Darma PutriFace Detection in Real Time Using the Local Binary Patterns Histograms (LBPH) Method.

The team will be accompanied by a supervisor who has expertise in accordance with the proposed topic. The lecturers involved as mentors were: Kadek Yota Ernanda Aryanto, S.Kom., MT, Ph.D., I Ketut Resika Arthana, ST, M.Kom., and Ni Putu Novita Puspa Dewi, S.Kom., M .Cs.