• I'm a data enthusiast looking for an opportunity in the data science role.
  
• Skilled in machine learning models.
  
• Actively writing on medium about Data analytics and Data science.

Using Python data visualization libraries (Pandas and Seaborn) to analyze a dataset of Liga 1 Indonesian Soccer Player 2023-2024. The data of the players include player_name, market_value, nationality, birth_date, position, date_joined, contract, and club_name. The aim of this analysis is to find players with the highest market value, compare the market value of local and foreign players, see the distribution of foreign players within the club, and find the youngest players and veteran players in the league.

Using Pandas Library to analyze rice production in Indonesia 2020-2022. There are four analyses: the distribution, most productive and not productive provinces, year-by-year for columns, and year-by-year for every province.

Sentiment analysis on MLBB's recent 10.000 reviews on the Google Play Store then using Machine Learning to create the model to predict the sentiment of a review. The sentiment is divided into three categories: positive, neutral, and negative. The machine learning models used are Logistic Regression, Random Forest and Extreme Gradient Boosting.

Sellers and buyers of used cars who do not have sufficient knowledge about cars will find it difficult to determine the price of the car to be sold. This can lead to unsold cars or losses for the seller, for the buyer the loss is the difficulty of deciding to buy a used car. This project is to create a model to predict the price of a used car based on the specifications of the car. The price generated by this model will be a reference for car sellers and buyers when buying and selling used cars. The goal is for used car sellers/buyers to make quicker decisions in conducting transactions (selling/buying).

Create a model to determine property value in the City of Philadelphia based on property characteristics created by the Philadelphia Office of Property Assessment (OPA). The goal is to obtain the true value of a property which will be used as the basis for determining the property tax price.