Ahmad-rizky1617/Buku_Kating_Kelompok2
Oct 2024 – Nov 2024
2 Months active
Languages Used
Python
Technical Skills
Code CleanupCode FormattingCode RefactoringContent ManagementContent UpdateData Entry
devynaass
PROFILE
Devynaass
Devyna contributed to the Ahmad-rizky1617/Buku_Kating_Kelompok2 repository by building and refining user profile management features, implementing data quality improvements, and developing interactive data analysis tools. She used Python, Pandas, and Streamlit to deliver profile and identity updates, initiate external API integrations, and create apps for visualizing department feedback and internship analytics. Her work included code cleanup, refactoring, and UI enhancements to stabilize the codebase and reduce technical debt. By addressing data inconsistencies and improving feedback sentiment capture, Devyna enabled more accurate reporting and better user experiences, demonstrating a strong grasp of both full stack and data-centric development.
Overall Statistics
Feature vs Bugs
58%Features
Repository Contributions
29Total
Bugs
5
Commits
29
Features
7
Lines of code
10,302
Activity Months2
Your Network
39 people
Work History
November 2024
8 Commits • 3 Features
Nov 1, 2024November 2024 (Month: 2024-11) focused on delivering business value through data quality improvements and insights via Streamlit. Key outcomes include feature delivery to enhance department feedback sentiment, data integrity cleanup across departments, and two Streamlit-based apps that illustrate data science concepts and internship analytics. These efforts improved data accuracy, enabled better decision-making, and provided interactive visualizations for stakeholders.
8 Commits • 3 Features
Nov 1, 2024November 2024 (Month: 2024-11) focused on delivering business value through data quality improvements and insights via Streamlit. Key outcomes include feature delivery to enhance department feedback sentiment, data integrity cleanup across departments, and two Streamlit-based apps that illustrate data science concepts and internship analytics. These efforts improved data accuracy, enabled better decision-making, and provided interactive visualizations for stakeholders.
November 2024
October 2024
21 Commits • 4 Features
Oct 1, 2024Month: 2024-10 — Performance-review oriented monthly summary for the repository Ahmad-rizky1617/Buku_Kating_Kelompok2. The month focused on delivering user-facing profile and identity updates, stabilizing the codebase, and enabling external service integration, while addressing data quality and UI/UX issues to reduce operational risk. Key outcomes include a comprehensive set of profile/identity updates for Sonya (photos, positions, and related identity data) across the batch, the initiation of an external service API integration, and broad maintenance across multiple scripts and components (medkraf, ssd, teross, plis, etc.). Critical defect fixes were implemented to harden the release baseline and improve user experience. Impact and business value: higher data accuracy and richer user profiles; faster integration with external services enabling new workflows; improved stability and maintainability across the codebase; reduced risk from UI and metadata inconsistencies; streamlined prep for next sprint with batch cleanup complete.
October 2024
21 Commits • 4 Features
Oct 1, 2024Month: 2024-10 — Performance-review oriented monthly summary for the repository Ahmad-rizky1617/Buku_Kating_Kelompok2. The month focused on delivering user-facing profile and identity updates, stabilizing the codebase, and enabling external service integration, while addressing data quality and UI/UX issues to reduce operational risk. Key outcomes include a comprehensive set of profile/identity updates for Sonya (photos, positions, and related identity data) across the batch, the initiation of an external service API integration, and broad maintenance across multiple scripts and components (medkraf, ssd, teross, plis, etc.). Critical defect fixes were implemented to harden the release baseline and improve user experience. Impact and business value: higher data accuracy and richer user profiles; faster integration with external services enabling new workflows; improved stability and maintainability across the codebase; reduced risk from UI and metadata inconsistencies; streamlined prep for next sprint with batch cleanup complete.
Activity
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Quality Metrics
Correctness89.8%
Maintainability91.0%
Architecture87.0%
Performance91.8%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Code CleanupCode FormattingCode RefactoringContent ManagementContent UpdateData AnalysisData CorrectionData EntryData ManagementData ManipulationData RefinementData ScienceData StructuresData VisualizationFront-end Development
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