Name: Ikhwanul Muslimin
Type: User
Company: Waresix
Bio: He has a masters degree in Computational Physics from Institut Teknologi Bandung, under the full Master scholarship, who are passionate about data analytics.
Location: Bogor, Jawa Barat
Blog: https://www.linkedin.com/in/ikhwanulmuslimin/
Ikhwanul Muslimin's Projects
#8WeekSQLChallenge by Danny Ma.
Kumpulan file tugas dari kursus Python for Everybody di Coursera.
Visualize the rise of COVID-19 cases globally with ggplot2.
Creating a customer segmentation using k-means clustering based on genre film rating from customer and find the best k using Hubert index and D index.
Reanalyse the data behind one of the most important discoveries of modern medicine: handwashing.
Exploratory data analysis using big data (~14 GB data) about e-commerce activity and predict if user will buy the item using XGBoost with accuracy of 61%.
Visualize my LinkedIn Connection using Plotly.
Explore a dataset from Kaggle containing a century's worth of Nobel Laureates. Who won? Who got snubbed?
Load, clean, and visualize scraped Google Play Store data to understand the Android app market.
Automatic credit card approval predictor using hypertuned parameter Logistic Regression with accuracy of 85.4%
Find the true Scala experts by exploring its development history in Git and GitHub.
This program, which was compiled using the MATLAB application, is a program that can calculate cross sections and perform multipol decomposition of the case of electromagnetic wave scattering in a system of coated spheres. This program was made as my undergraduate final project. The theory used to explain this scattering case is the Mie theory.
Program ini, yang dibuat dalam bentuk Graphical User Interface (GUI), merupakan program untuk menghitung respons penampang-lintang dari kasus hamburan pada satu buah bola. Aplikasi yang digunakan untuk membuat program ini yaitu MATLAB.
Predict the student grade using linear regression and K-Neighbors classifications with each of the accuracy > 90%
Load, clean, and explore Super Bowl data in the age of soaring ad costs and flashy halftime shows.
Increased the ROC AUC score by 2.14% of predicting the churn of users in telecommunication company using hypertuning parameter and feature engineering.