Bayu has many years of experience in software engineering as a team member, team leader, and manager, using various technologies while working on the front end, back end, and Big Data. The technologies he uses include React, React Native, Flutter, Python, Go, Java, Hadoop, NoSQL, and Elasticsearch. He is also very familiar with cloud computing services and in-house hosting, using DevOps technologies like Docker and Kubernetes.
Designed the architect of perso.id (web and mobile apps).
Managed a small team consisted of a graphic designer and tester to deliver a mobile app to fulfill the requirements.
Made adjustment and pivoted strategy in terms of technology used in Perso.id.
Implemented the apps initially using Python and Flutter, but then pivoted to use Golang and Flutter with some adjustment of the algorithms and flows used in the mobile app.
Monitored the mobile app performance in terms of latency, correctness and number of users.
Implemented a feature to highlight pages in PDF.js.
Enabled page redirection via a PDF file so that when users search for a term on the file, they can click in that term directly for redirection.
Implemented document classification based on category.
Developed a feature for document citations to track which documents have more importance.
Migrated a search platform from Solr 3.6 to the latest Apache Solr, which was quite challenging since version 3.6 and the latest version (7.6) were very different.
Translated the UX design from a Sketch file format to a web layout.
Implemented a React app as the platform's front end.
Developed a Django project that will serve as the cryptocurrency trading platform.
Migrated the existing code that the previous developer made. Unfortunately, there was not much information on the developed work, which brought some challenges to this project.
Constructed the trading platform to cover several cryptocurrencies—Bitcoin, Bitcoin Cash, Ethereum, Ripple, and Monero.
This project accepts GPS data, such as latitude and longitude, and stores them in a Cassandra database. The project was tested to handle tens of thousands of GPS devices sending data every few seconds.
This project is based on Scrapy and Splash to scrape websites with dynamic content. The code was tested to scrape the eCommerce website Zalora.co.id and Berrybenka.com. The data is then stored in database and later accessed by a web app.
This was a project to implement the back-end system for text classification. The main clients are financial institutions like banks, insurances, etc.Technologies: Hadoop (Hortonworks), HBase, Django, PostgreSQL, Apache Spark, and React.
In this project, I worked mainly on a data pipeline to classify eCommerce products based on the products images, titles, and description.
The pipeline includes web scraping to scrape many eCommerce sites (mainly fashion), cleanse the data, store it, and analyze it using a deep learning tool. In this case, it was TensorFlow.
Besides the pipeline, I also developed multi-platform mobile apps (Android and iOS) using React Native to monitor the pipeline, building a data set for model training, and communicating the results of the deep learning training.
A React Native app that uses JWT identification and a native base UI component to make it pretty. Axios and Reduce Libraries are used for managing the connection and for storage management.
I worked on the back-end and front-end for a mobile to-do list app. For the back-end side, I used Django and PostgreSQL, and for the front-end, I used React Native;
the React Native was incorporated during development so that the employees could see the results immediately.
Some other mechanisms that were implemented in the front-end were the social logins (Google and Facebook), JWT, a calendar UI, and communication with the REST API.
This project was to build a system to store GPS data on Hadoop and use its other software in the Hadoop environment. The main clients are transportation and logistics companies.Technologies: Hadoop Hortonworks and Apache Hive.
