I plan to pursue my career in Software Development, AI and Data Analytics. I would like to do the teamwork, sharing to improve abilities and connection, also love to learn something new to give better impact on work.
Right now, I spent my time learning, coding and help my mom to grow her culinary business.
Developed REST APIs for Mindhive app using Django Rest Framework and Object Relational Mapping (ORM).
Ensured code quality by implementing unit testing, code reviews and ran TDD.
Implemented the third-party APIs and improved some of the existing endpoints response speed up to 30%.
Chosen to lead the Indonesian team to finalize magic link feature creation to help users join discussions directly.
Researched and implemented a pre-trained model for wildcard algorithm as part of R&D projects.
Helped redesign the search feature by creating mockups.
Contributed to the development of the YeahNah app APIs using Flask, FastAPI, and DynamoDB.
Worked on Auth0 action flows and user data migration to new tenants.
Created some asynchronous tasks using Celery.
Contributed to developed, managed and supervised the process of IT-Banking project held by Ministry of Communication and Information Technology (Kominfo RI) and Rakamin Academy.
Built back-end for B2B Analytics mobile app using Python, PostgreSQL, Google Maps API and Elasticsearch on a VM (RHEL).
Integrated and improved machine learning models from Data Scientists into REST APIs using Flask framework.
Contributed to analyzed survey results for new system architecture at B2B.
Designed and built front-end for student scholarship web app (equipped with dashboard feature) using Vue.js and Axios.
Collected, manipulated, analyzed and interpreted data into actionable insights using SQL Bigquery, Tableau, Python, etc. Also worked on some projects to solved current problems using Advanced Statistic Analysis, Machine Learning and NLP approach.
Shared knowledge and practiced with audiences how to create basic programs in Python.
Trained to built a Laundry management using Odoo (with Ubuntu LTS).
Designed, built, and tested an online leave letter systemfor Diskominfo’s employees using Balsamiq, Power Designer, PHP, HTML2pdf, Bootstrap, Javascript and MySQL.
Wrote accountability and other reports using Microsoft Office (Word, Excel).
Graduated with Honors (GPA: 3.77 / 4.00)
Build Front-end for Kemenag RI scholarship app using Vue.js click to view site
Made a news publication app with built-in automatic text categorization. This app was written in Python using the Django framework. click to view site or code
Made Restaurant Recommendation System using Content-Based (based on serving distance, weighted ratings, restaurant tags) and Collaborative Filtering (with SVD algorithm) techniques. The program coded in Python using Surprise and MPU. click to view code
Made a simple market basket analysis for retail product recommendation using R. click to view code
Traned model to classify cancer cells type using AutoML framework (Auto-sklearn). click to view code
Made application for identifying and detecting face emotions from video and image using deep learning model (CNN). The result shows identified person's name and the percentage of each of his emotion (happy, sad, etc.) at the left detected face in the frame. click to view code
Made a model for predicting patient’s chest x-ray with Pneumonia using deep learning (CNN) and images sharpening technique. This code was written in Google Colab click to view code
Trained machine learning models (MNB, SVM, Logistic Regression, and Random Forest) on Apple Tweets Sentiment Analysis by compared their performance, also analyzed the tweets using Topic Modeling (with LDA algorithm). click to view code
Made a Movie Recommendation System with Collaborative Filtering (ALS Matrix Factorization algorithm). The program coded in Python using Spark. click to view code
Made experiment with machine learning models (Multinomial Naive Bayes, Suport Vector Machine, Logistic Regression, Random Forest, also Neural Networks) on Indonesian News Classification by compared their performance, also analyzed the features using chi squared. The best model (SVM) deployed using Flask. click to view code
This app was written in Python using Flask Framework (web based). Here I used Machine Learning Approach (Multinomial Naive Bayes to classify the intent and Rapid Automatic Keyword Extraction to predict the entity) . click to view code
This was an experiment to compare the performance of CNN and DNN model on handwritten digits prediction. I used CNN model to predict the input pattern. click to view code
This was an experiment to compare the performance of RNN model approaches (LSTM and GRU) on Indonesian SMS classification. This simple code was written in Google Colab. click to view code
Made a model for detecting words from Tokopedia user’s chat that are similar to banned words using word embedding techniques(Word2vec and FastText)and Cosine Similarity. confidential
Made a model for predicting customer churn on “Tokopedia by Me” service using machine learning algorithm, also analyzed which feature has the most impact on a customer leaving. confidential
Analyzed the performance of a new Tokopedia’s feature “Tabbed Chats” using effect size analysis(Cohen’s D). confidential
This was a simple short visualization of covid-19 using Tableau in the form of world map and line graph. click to view code
This is a rapid customer segmentation using K-Means clustering technique and high dimensional visualization. The dataset is taken from Kaggle. click to view code
Made SVM (Support Vector Machines) model using human cell records, and classify cells to whether the samples are benign or malignant. click to view code
This simple code written in Python, made to predict which drug type/medicine can be given to patient using Decision Tree click to view code
This short code made to predict customer churn using simple logistic regression and telco dataset. The goal is to understand the basic Regression. click to view code
This short code made CO2 Emission prediction value using simple linear regression. The goal is to understand the basic Regression. click to view code
This short code was written in Python, Jupyter Notebook using K-Means algorithm. click to view code
Visit my github repositories to view my old web app & other project click to view older projects