Mutia Ayu Sabrina

Lead and manage the Data Intelligence & Analytics team, ensuring high-quality analysis, insights, and delivery across agronomy operations.

Own and drive the development of digital products, including interactive dashboards, analytical engines, and mobile applications, supporting agronomy services and field operations. (Tableau, Python, Flutter)

Design and oversee end-to-end analytics workflows, from data collection, processing, modeling, and validation to visualization and deployment.

Ensure data governance, quality, and standardization across analytics and digital products.

Collaborate with cross-functional stakeholders to deliver actionable insights for performance monitoring, operational efficiency, and decision-making.

Support strategic initiatives by providing advanced analytics, trend analysis, and predictive insights for agronomy services.

Developed a Python-based engine to recommend optimal fertilizer application timing, improving agricultural efficiency and yield consistency.

Established and enforced data standards for critical Tableau dashboards (production, pest attack, and upkeep, climate situation), ensuring reliability and consistency in operational decision-making.

Analyzed plantation datasets to generate actionable insights supporting strategic and day-to-day operational decisions across estates.

Conducted data quality assurance for R&D activities, maintaining high data integrity across experimental and operational datasets.

Designed and developed a mobile application for operational quality assurance (QA) covering Production, Fertilizer, Upkeep, Chemist, and Fruit Grading activities, enabling real-time data collection and performance monitoring in the field.

Built a Python-based QA verification engine used by assistants and managers to validate and analyze QA results submitted by the operational team, strengthening consistency and accountability in field performance assessment.

Designed and implemented interactive Tableau dashboards for monitoring Fruit Set Scores across 9 estates, significantly improving agricultural yield assessment and management.

Developed a comprehensive dashboard for harvester attendance across 9 estates, enhancing labor efficiency and productivity through precise workforce tracking and allocation.

Integrated Tableau with ArcGIS to create dynamic GIS maps, providing detailed views of estates and block performance, which facilitated better strategic agricultural decisions.

Engineered a specialized Agric Block Performance Dashboard to track and analyze agricultural block performance, enabling stakeholders to identify key areas for continuous improvement.

Managed a database of up to 6,000,000 daily records by developing custom SQL queries for efficient ETL processes, ensuring data accuracy and timeliness for all departmental dashboards.

Standardized "Kamus Data ESDM" for Pusdatin ESDM RI, establishing data consistency across all resources involved in ESDM sectors.

Managed data collection from diverse government agencies and companies, ensuring comprehensive and up-to-date information for national resource planning.

Implemented robust data cleaning techniques, enhancing data quality and consistency for improved analytical reliability.

Designed and managed databases to provide necessary data for stakeholder analysis, directly supporting informed decision-making processes.

Developed and delivered training on data management, processing, and analysis, improving data literacy and capabilities for related teams.

Optimized database systems and security, utilizing Python for crawling diverse data sources, enhancing data integrity and acquisition efficiency.

Designed and implemented robust database systems to efficiently store and manage EITI-related data, improving data accessibility and reliability.

Identified and rectified inconsistencies and errors within the EITI database, significantly enhancing overall data quality and accuracy.

Cleaned, validated, and standardized raw data using Python, creating structured datasets for advanced analysis and reporting.

Developed and optimized PostgreSQL queries to extract specific data, supporting the backend of the EITI dashboard and improving data retrieval performance.

Created a custom text detection model using XGBoost to automatically flag report discrepancies, improving data quality through machine learning.

Designed and developed interactive PowerBI and Tableau dashboards for clients like PT Interport Mandiri Utama and MIND ID, enhancing business intelligence and decision-making.

Conducted user feedback research for Mu-Trans app updates, gathering insights to inform feature enhancements and improve user satisfaction.

Redesigned the Tebing Tinggi Smart City Website interface, enhancing user experience and visual appeal.

Collected and processed time series datasets for LME Aluminium and Alumina prices, preparing data for predictive modeling.

Clustered datasets into 3-day segments using Microsoft Excel to prepare for machine learning analysis.

Developed and implemented a Machine Learning model (Backpropagation algorithm with Python) to predict LME Aluminium and Alumina prices.

Collaborated with the engineering team to integrate the forecasting system, providing critical insights for price prediction.

Spearheaded professional development programs for informatics students, enhancing skill sets and career readiness.

Managed scientific initiatives to foster research and innovation among student members.

Assisted in organizing and executing professional development workshops and scientific events.

Contributed to initiatives aimed at enhancing student engagement in academic and career-related activities.

Contributed to initiatives promoting innovation and recognizing student achievements in technology and research.

Assisted in planning and executing events designed to inspire and showcase student talent.