MACHINE LEARNING SOFTWARE DEVELOPMENT WITH CRISP-DM AND SOME SCRUM CONCEPT
In the field of data mining, machine learning (ML) has been utilized in the search for solutions to various problems. One widely used model process for ML development is the Cross Industry Standard Process for Data Mining (CRISP-DM). On the other hand, Scrum has emerged as the most popular agile...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/74787 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | In the field of data mining, machine learning (ML) has been utilized in the search for solutions
to various problems. One widely used model process for ML development is the Cross Industry
Standard Process for Data Mining (CRISP-DM). On the other hand, Scrum has emerged as the
most popular agile method for software development in recent years. In this research, we
proposed an ML software development guide for ML used in data mining by equipped relevant
Scrum concepts into CRISP-DM. The process involves analyzing CRISP-DM and the
development situation through interviews with experienced ML software developers.
Furthermore, an analysis of the implementation of Scrum concepts in CRISP-DM is conducted.
The proposed guideline is represented in Essence and tested through a case study, qualitative
evaluation, and evidence map. The evidence map is used to analysis the importance of proposed
guideline components is examined. The results indicate that the proposed guideline can be
utilized to assist in the development of ML software. |
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