During my internship as a Web Developer, I had the opportunity to work on a significant project aimed at streamlining the expense tracking process for employees. Here's a breakdown of my responsibilities:

• Design and Development of an Expense Tracking Application: I was responsible for designing and developing an application system using Laravel and MySQL. This system aimed to automate and simplify the process of tracking employee expenses. Through efficient coding and user-friendly design, I contributed to the creation of a functional and user-centric application
• Collaboration Across Multiple Divisions and Units: Throughout the project, I collaborated with various units and divisions within the company. This collaboration involved coordinating with cross-functional teams to ensure the application met the needs and requirements of different stakeholders.
• Data Analysis and Functional System Requirements: To ensure the application's effectiveness, I conducted interviews with clients from different departments to analyze data requirements and gather functional system requirements.

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During my role as a System Analyst Intern, I was tasked with analyzing and developing an inventory website for efficient product control. Here's a summary of my responsibilities:

• Analysis of System Requirements: I conducted in-depth interviews with users and relevant stakeholders to comprehensively analyze system requirements. This involved gathering insights into the specific needs and expectations of end-users and business-related parties.
• Data Modeling and Database Schema Development: To visualize and document system functionality, I created detailed use cases and activity diagrams. I also played a pivotal role in creating the database schema for the inventory system. This schema served as the foundation for efficient data management, ensuring that product control processes were streamlined and data was organized effectively.
• User Interface Design with Figma: I was responsible for designing the user interface (UI) of the inventory website using Figma. The UI design focused on user-friendliness and functionality.

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My apprenticeship as a Data Analyst not only expanded my technical expertise but also honed my ability to work collaboratively on meaningful projects. It was a transformative experience that reinforced my passion for leveraging data to drive informed decision-making. The experience included:

• Technical Classes in Data Analysis: Over the course of the first three months, I engaged in rigorous technical classes that delved into various aspects of Data Analysis. This comprehensive training covered data cleaning, data transformation, and data reformation techniques.
• Collaboration on a Capstone Project: As part of the apprenticeship program, I had the opportunity to collaborate with my peers on a capstone project. Our project focused on conducting a case study to analyze reading literacy inequality in Indonesia. This collaborative effort allowed us to apply our newly acquired data analysis skills in a real-world context, addressing a significant social issue.
• Dashboard Visualization for Final Project: For the final project, I leveraged my skills in data visualization by creating an interactive dashboard. This dashboard was designed using tools like Looker Studio or Google Data Studio. It played a crucial role in presenting our findings and insights from the case study, providing a visually engaging and informative representation of the data.

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This program offers an excellent opportunity for participants to develop and master Python programming skills in the context of Data Science. By participating in this program, I had the chance to become proficient in a tool that is highly valued in data analysis and software development. The program covers Python programming from the ground up, including the following topics:

• Data Types, Variables, and Basic I/O: This encompasses the fundamentals of data types in Python, defining variables, and interacting with input and output.
• Control Flow and Lists: These topics relate to the control flow of program execution and how to work with lists of data.
• Collections, Functions, and Error Handling: This involves the use of various data structures like sets and dictionaries, creating functions, and handling errors in programs.
• Modules, Packages, and PIP: Participants will learn about using modules and packages in Python and how to manage dependencies using PIP (Python Package Installer).
• Object-Oriented Programming and others: This covers the principles of object-oriented programming in Python, which enables the creation of more structured and organized code.

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Binar Academy is proud to conduct this bootcamp in partnership with the prestigious Digital Talent Scholarship program by the Ministry of Informatics, as part of the highly-regarded Fresh Graduate Academy initiative.

• Data Analysis and Data Cleaning: I understand the importance of examining, cleaning, and preparing data before analysis. This process involves removing invalid data, filling in missing values, and ensuring data quality.
• Python Programming for Data Manipulation: I've learned how to use the Python programming language to manipulate data. This includes combining, transforming, and manipulating data to fit the needs of my analysis.
• Basic Statistics and Machine Learning Concepts: I have grasped the fundamentals of statistics required for data analysis, such as data distribution concepts and measures of central tendency. Additionally, I've been introduced to machine learning, enabling me to create predictive models based on data.
• Data Visualization and Using SQL: 've learned how to depict data through graphs and visualizations to make it more understandable. Additionally, I understand the use of SQL to access and manage data in databases.
• Real-World Data Project Execution: I've had the opportunity to work on a real-world project that involved applying all the concepts I've learned. This experience has helped me apply my knowledge in real-world situations.

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At IYKRA/Data Fellowship, I underwent an intensive learning program that provided me with a deep understanding of Data Engineering. I gained hands-on experience working with tools like SQL, Python, and Apache Spark, and had the opportunity to apply my skills to real-world projects. I am confident in my abilities as a Data Engineer and eager to make significant contributions to this field. For detail:

• DDevelopment of Data Flow and Data Pipeline: I invested time and effort to master cutting-edge technologies like Kafka, Airflow, and DBT to create efficient Data Flows and Data Pipelines. This facilitated the seamless flow of data from various sources into the Data Warehouse, enhancing the effectiveness of the company's data management.
• Collaboration on Final Project: I actively collaborated with the team throughout this learning journey. At the end of the program, we successfully completed a Final Project relevant to the practical use of Data Engineering technologies in a real-world context.

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