Evaluation Instrument
Name:
Date:
Address:
Brgy. / Purok:
Instruction: Please evaluate the system by using the given scale and placing checkmark
(/) under the corresponding numerical rating.
Each rating is qualified by the following:
5 – Strongly Agree 4 – Agree 3 – Moderately Agree 2 – Disagree 1 – Highly Disagree
Software
Quality Factors
Descriptions
5 4 3 2 1
Functional
completeness
Functional
Suitability
Functional
correctness
The Cloud-based Outreach and
Extension DSS using Machine
Learning Models covers all the
specified tasks and user
objectives.
The Cloud-based Outreach and
Extension DSS using Machine
Learning Models provides the
correct results with the needed
degree of precision.
The Cloud-based Outreach and
Functional
Extension DSS using Machine
appropriateness Learning Models functions’
facilitate the accomplishment of
specified tasks and objectives.
Time behavior
Performance
Efficiency
Resource
utilization
The Cloud-based Outreach and
Extension DSS using Machine
Learning Models response and
processing times and throughput
rates of a product or system,
when performing its functions,
meet requirements.
The Cloud-based Outreach and
Extension DSS using Machine
Learning Models, when
performing its functions, meet
requirements.
Capacity
Operability
Usability
User error
protection
User interface
aesthetics
Maturity
Reliability
Availability
Fault tolerance
Confidentiality
The Cloud-based Outreach and
Extension DSS using Machine
Learning Models parameters
meet requirements.
The Cloud-based Outreach and
Extension DSS using Machine
Learning Models has attributes
that make it easy to operate and
control.
The Cloud-based Outreach and
Extension DSS using Machine
Learning Models protects users
against making errors.
The Cloud-based Outreach and
Extension DSS using Machine
Learning Models interface
enables pleasing and satisfying
interaction for the user.
The Cloud-based Outreach and
Extension DSS using Machine
Learning Models meets needs
for reliability under normal
operation.
The Cloud-based Outreach and
Extension DSS using Machine
Learning Models is operational
and accessible when required for
use.
The Cloud-based Outreach and
Extension DSS using Machine
Learning Models operates as
intended despite the presence of
hardware or software faults.
The Cloud-based Outreach and
Extension DSS using Machine
Learning Models ensures that
data are accessible only to those
authorized to have access.
Security
Integrity
The Cloud-based Outreach and
Extension DSS using Machine
Learning Models prevents
unauthorized access to, or
modification of data to
unauthorized users.
Degree to which actions or
events can be proven to have
Non-repudiation taken place so that the events or
actions cannot be repudiated
later.
The Cloud-based Outreach and
Extension DSS using Machine
Modularity
Learning Models composed of
discrete components or modules
for easy usage.
Maintainability
Modifiability
Testability
The Cloud-based Outreach and
Extension DSS using Machine
Learning Models can be
changed or updated without
introducing bugs or degrading
the existing standards.
The Cloud-based Outreach and
Extension DSS using Machine
Learning Models provide test
criteria for testing certain actions
or changes in the system.
SUMMARY
Functional Suitability
Performance Efficiency
Usability
Reliability
Security
Maintainability
Total
Validated by:
Dr. Ryan Evangelista
Committee Chair
Dr. Arvin Natividad
Panel Member
Dr. Jesus Paguigan
Panel Member