Hello there! I'm Tanesya, a data explorer who finds joy in bringing ideas to life and building things. These days, my main focus involves crafting high-quality, custom, and user-friendly R/Shiny solutions for clients at Appsilon. While I mostly do my work in R, currently, I'm also joining an adventure with Devscale Indonesia to explore the nuances of modern JavaScript-based web development.
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R/Shiny Developer @ Appsilon
Creates data visualization and interactive applications, delivering custom, user-friendly R/Shiny solutions, ensuring timely delivery of high-quality projects tailored to client needs.
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Data Scientist @ Leaf
Work closely with Performance Marketing team to fetch, analyze, forecast and visualize clients' performance marketing data from Facebook Ads API. Build and maintain Pacing & Performance dashboard.
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Data Science Instructor @ Algoritma
Mentor, teach and build custom data science course materials and corporate projects. Supervise, lead and manage the development of the company's product team.
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OSS Engineer
- Sep 2018 - Nov 2018 @ Cybercom
- Feb 2018 - May 2018 @ GSM Systems
- Jun 2014 - Jan 2017 @ GMI Network
- Dec 2013 - May 2014 @ Lintas Media Telekomunikasi
Provide reports using data from network management tools, execute CR from Optimization Engineer, building dashboards with Microsoft Excel VBA and Microsoft Access.
R/Shiny integration to googlesheet and googledrive
2023
A demo of R's shiny application made with
rhino to showcase the utilization of
googlesheet and googledrive in a shiny
application. It sprinkled with a bit of sass and
JavaScript
for a customized look.
Predicting News Sentiment with LSTM
2021
An online course of sentiment analysis using Long Short Term Memory
(LSTM) algorithm with R interface to
Keras. Topics covered include text cleaning in R using
tidytext and textclean, basics of Neural
Network, RNN and LSTM, and LSTM architecture in Keras.
Building Interactive Map for Geospatial Analysis in R
2020
An online course that teaches how to process and visualize spatial
data in R. Topics covered include data wrangling with
tidyverse, how to use sf package to work
with spatial vector, building static map with
ggplot2 and interactive map with leaflet.
While not explicitly covered in the course, I also utilized
selenium and BeautifulSoup in
python to scrape the data used for the material.