About
Data Analyst & Data Scientist.
Accomplished data analyst with 2 years of experience. I have a proven track record of providing meaningful insights and recommendations to drive business decisions and increase efficiency.
- Name: Aldo Putra
- City: Sidoarjo, East Java, Indonesia
- Email: aldoputradelfiero0506@gmail.com
- Degree: Bachelor's degree
Proficient in programming languages such as Python and SQL, with a strong foundation in data analysis, reporting, and machine learning algorithms to build predictive models and generate insights. Another key area of technical expertise covers Artificial Intelligence (AI), Machine Learning, Large Language Models (LLM), and Computer Vision.
Resume
A glimpse of the my experience.
Sumary
Aldo Putra
Accomplished data analyst with 2 years of experience. I have a proven track record of providing meaningful insights and recommendations to drive business decisions and increase efficiency.
Proficient in programming languages such as Python and SQL, with a strong foundation in data analysis, reporting, and machine learning algorithms to build predictive models and generate insights. Another key area of technical expertise covers Artificial Intelligence (AI), Machine Learning, Large Language Models (LLM), and Computer Vision.
Education
Bachelor of Engineering Physics
2018 - 2022
Gadjah Mada University, Special Region of Yogyakarta, Indonesia
Professional Experience
Data Analyst
2022 - Present
Waresix, Surabaya, Indonesia
- Maintained and built analyzing data in the dashboard or reports with a 95% on-time delivery.
- Participated in the design and development of a data visualization tool, resulting in a 15% increase in stakeholder engagement and understanding of data insights.
- Collaborated with management to identify and prioritize business needs, resulting in the creation of a new dashboard that increased team productivity by 20%.
- Analyzed complex data sets to identify trends and patterns, resulting in the discovery of a new market segment that increased revenue by 15% and increased business efficiency by 20%.
- Led the design and implementation of a data mart, resulting in a 30% reduction in data pipeline costs and a 25% increase in data accessibility.
Portfolio
A glimpse of the projects I've been working on
- Main Project
- Machine Learning
- Deep Learning
- Cloud
- All
Prediction Delivery Time with XGBoost
This project predicts food delivery time. The project uses XGboost regression as a basic model to predict delivery time. This project also includes monitoring machine learning models using evidentlyAI.
KTP Classification using CNN
This project is an AI tool based on CNN that classifies documents, including KTP or non-KTP. This project is based on CNN with the transfer learning method (using efficient-net).
Automated Forecasting using ARIMA
This project aims to carry out forecasting automatically by just entering data. The forecasting results will come out in a few seconds. The project uses one of the best forecasting algorithms, namely ARIMA.
Dashboard Chatbot
This is an AI project based on LLM in the form of a chatbot. This chatbot can answer questions related to the company's dashboard. This chatbot can answer related questions about dashboards, such as "What metrics does this dashboard contain?", "What is the link to the dashboard?".
Customer Segmentation using K-Means
This project performs exploratory data analysis and customer segmentation using Customer Personality Analysis data. Segment customers using a machine learning algorithm, namely K-Means.
Food Classification using CNN
This project is an AI tool based on CNN that classifies types of food (sushi, pizza, steak). This project is based on CNN with the transfer learning method (using efficient-net).
Information Extraction Image Documents
This project performs the complex task of Information Extraction on structured image documents (Specifically, this project uses KTP as a document). This project utilizes the CNN model using pytorch to carry out 4 stages: document classification, document detection, document orientation, and information extraction.
Clothes Classification using CNN
The project builds an application named “Online Payments Fraud Detection System using Artificial Intelligence”. In this application, we use machine learning (Random Forest) techniques for the detection of customer fraud.
Online Payments Fraud Detection
The project builds an application named “Online Payments Fraud Detection System using Artificial Intelligence”. In this application, we use machine learning (Random Forest) techniques for the detection of customer fraud.
Predicting Credit Card Approvals
This project build an automatic credit card approval predictor using machine learning techniques (Using logistic regression), just like the real banks do.
E-Commerce Recommencation System using Matrix Factorization
Online E-commerce companies use various recommendation engines to recommend a variety of suggestions to customers. This project builds a recommendation system based on Matrix Factorization.
E-Commerce Recommendation System using User-Based Collaborative Filtering
Online E-commerce companies use various recommendation engines to recommend a variety of suggestions to customers. This project builds a recommendation system using user-based collaborative filtering.
Edge Detection using Opencv
This project is one part of the information extraction process on image documents. This project performs edge detection for an ID card (such as a KTP). This project uses the OpenCV library to perform edge detection.
ID Card Orientation using CNN
This project conducts training on the CNN model for orientation on ID cards. This model can rotate ID Card files or images, as in the image below. This model can be a first step to help extract text from ID Cards. This model uses the efficient-net CNN architecture.
Database Chatbot
This project conducts open-source research on the NL2SQL (Natural-Language-to-SQL) model. This model can be implemented as a chatbot that can interact with the database.This project uses the Tapex model.
ID Card Detection using Mask R-CNN
This project is one part of the information extraction process in image documents. The project is a document detection. This project leverages transfer learning via fine-tuning the state of art object segmentation algorithm Mask R-CNN backboned by pre-trained ResNet-50 available in torchvision models gallery.
Deploy Web App and Database on AWS
This project discusses a tutorial for deploying a web app and database on AWS. The project create an EC2 instance containing a web application placed in a public subnet so that the public can access it. To store data from the web also create a database. The project creates an RDS instance that contains a database that is located in a private subnet.
Deploy Highly Available Architecture on AWS
This project creates a server environment that is both elastic and highly available. If there is a problem with the server, web, or app, the server can still run it well. The project utilizes Amazon EC2, VPC, ELB, and Auto Scaling. The project uses Auto Scaling, which is in 2 Availability Zones. Auto Scaling is also connected to Elastic Load Balancing (ELB).
Contact
Feel free to contact me with any questions. You can send me an email with this form.
Location:
Sidoarjo, East Java, Indonesia
Email:
aldoputradelfiero0506@gmail.com