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american_option_price

Predicts the fair value of Company XYZ's during participation rights in the X project using American Binomial Options Method.

brent_oil_price_prediction

Using RNN with LSTM neural networks, this project forecasts Brent oil prices by preprocessing historical data, training the model with dropout, and evaluating for accurate predictions.

classify_fish_species

This project aims to classify fish species using morphological features extracted from fish images, including dissimilarity, correlation, and energy.

classify_wine_class

The project implements Adaboost from scratch to classify wine classes using features from the wine dataset.

clustering_digital_wallet_users

This project aims to cluster digital wallet users based on their survey responses using the KPrototypes algorithm, which handles both numerical and categorical data, resulting in three distinct clusters characterized by different demographic and behavioral attributes.

clustering_mobilphone_sales

Cluster mobile phones by attributes for market segmentation. Employ K-means, preprocessing, and visualization tools in Python for analysis and insights.

clustering_training_customer

Analyze Banten Marine Polytechnic cadet/alumnus profiles with age, recency, frequency, and monetary methods, clustering via K-means algorithm from scratch.

compressor_control_offline_rl

The project models a compressor machine to predict parameter changes, ensuring stable pressure. It preprocesses data, employs ensemble methods, and utilizes reinforcement learning.

district_graph_coloring

Apply Greedy and Welch Powell algorithms to assign colors to map districts ensuring adjacent districts have different colors.

fracture_leg_detection

Developing a fracture detection system for leg radiographs using VGG16 pre-trained CNN, aiming to enhance diagnosis efficiency in clinical settings.

ge_visualization

Utilize the GE McKinsey Matrix methodology to assess product strategic positioning within the market using Python tools.

gold_price_prediction

A custom Radial Basis Function (RBF) neural network is implemented to predict gold prices using time series data.

hospital_revenue_prediction

Clustering hospital revenue from insurance claim payment using timeseries clustering method.

indonesian_spelling_corrector

Developing Indonesian spelling correction using RNN model on root word dataset. Preprocess with tokenization and root form conversion, train, evaluate, and potentially improve deployment.

kemenkeu_bandwidth_prediction

Forecast time series using ARIMA, employing exploratory data analysis, data preprocessing, stationarity checks, AR and MA modeling, differencing, and Python libraries.

kompas_news_hoax_detection

Automates fake news identification in Kompas articles, comparing Random Forest and Convolutional Neural Network models for text classification.

pdf_malware_detection

The project enhances GARUDA's cybersecurity by employing deep learning to classify malware in scholarly resources, utilizing Python libraries and evaluation metrics.

predicting_overweight

The project utilizes Support Vector Regression to predict individual weights from obesity data, contributing to personalized healthcare strategies.

pytorch_to_onnx_converter

Install packages, define CNN in PyTorch, load weights, export to ONNX, fix input name error, save model.

stock_trend_prediction

Employing TOBA stock data, the random forest algorithm predicts price trends, reaching a 70.2% accuracy post hyperparameter tuning and feature selection.

streamlit_app_cheat_detection

streamlit_app_clustering_training_customer

streamlit_app_hospital_revenue_predictor

streamlit_app_kemenkeu_bandwidth_predictor

streamlit_app_meeting_notes_summarizer