Dashboard Peta Interaktif ini dibuat untuk menunjukkan angka kasus Positif Corona di tiap Kecamatan di DKI Jakarta disertai data SUSPEK, PROBABLE, PELAKU PERJALANAN, KONTAK ERAT, dan DISCARDED.

Laporan ini dibuat untuk menunjukkan angka kasus dalam pentuk HEATMAP sekaligus mengenalkan terminologi baru seperti SUSPEK, PROBABLE, PELAKU PERJALANAN, KONTAK ERAT, dan DISCARDED.

Di sebuah supermarket, produk apa saja yang biasanya dibeli bersamaan? Fungsi `apriori()` dapat membantu retailer menentukan penempatan produk di rak, hingga memilih produk untuk dipromo secara 'bundling' untuk tingkatkan awareness produk yang jarang dibeli.

There is no doubt that a Sales can be translated into future's budget allocation on marketing campaign. But, do our retail provide enough data variables to forecast the next sales? External regressors are needed to better training Machine Learning models. This report examine which regressors (variables) can better the Model Performance.

My first encounter to Prophet Time Series Model, done with R.

This is my submission on Learning by Building - Algoritma course. I study the differences of Naive Bayes and Decision Tree classifier to see which models performs better to predict the Happy country based on the variables available.

With K-means Clustering combined with Principle Component Analysis, we can identify what variables make a song get a high Popularity.

As a final project, I plan to build a model to forecast Retail Sales and predicting the causal factors such as Price Markdown and Consumer Price Index. This part (as my proposal) contains Exploratory Data Analysis. I will update the final result in a few weeks

This is my submission for Machine Learning Capstone Project where I use Concrete Mixture dataset and try to build and tuning some Regression Models to find the least error between the prediction and the test data.

The Survived person on Titanic predicted with Logistic Regression Model compared with k_Nearest Neighbor method.

Machine Learning Linear Regression with House Price data from Kaggle

Engagement of a Youtube defines by their views and engagement. In this Flex Dashboard, you may find which Video Category has highest views, engagement, and also on what day the video had been published.

On this publication I use Titanic Dataset by Kaggle for studying Base R and simple Data Visualization. This is beginner level, so I would like to see if there is anything I can add on this publication.

Visualisasi Data Commuter Jabodetabek Berdasarkan Penghasilan

Jobs Gender Dashboard