Curriculum Vitae
Dimas Dwi Armaisya
Saya lulusan baru dari Universitas Nasional dengan jurusan Informatika, saya menfokuskan pengetahuan dan keahlian spesialisasi dalam Kecerdasan Buatan (AI), Machine Learning, dan Data Science. Sebagai individu yang adaptif, bersemangat untuk belajar hal-hal baru, dan cepat belajar, saya sangat antusias untuk terus mengembangkan pengetahuan dan keterampilan saya, dengan fokus kuat pada Kecerdasan Buatan, Machine Learning, dan Data Science. Saya memiliki keterampilan yang kuat dalam pemrograman Python dan SQL, dengan pengalaman praktis dalam mengembangkan solusi Machine Learning end-to-end menggunakan kerangka kerja seperti Scikit-Learn dan TensorFlow. Kemampuan yang terbukti dalam analisis data dan visualisasi menggunakan Looker Studio, Power BI, Matplotlib, dan Seaborn.
Juni 2025
Universitas Nasional
S1 • Informatika • IPK 3.92
April 2024 - September 2024
Data Scientist
PT Telekomunikasi Indonesia (Persero) Tbk • Magang
Januari 2024 - April 2024
AI Project
Samsung Research Indonesia • Magang
1. Collected and curated over 15,000 diverse Indonesian voice and text data, laying the foundation for a high- performing ASR model by ensuring
balanced representation across dialects and scenarios.
2. Produce and standardize 15,000+ voice and text data, ensuring clean, reliable inputs for ASR model training and reducing data-related model errors
downstream.
3. Performed comprehensive manual and automated quality checks across 15,000+ data points, significantly reducing noise and inconsistencies that could
degrade model performance.
Agustus 2023 - Januari 2024
Student Machine Learning Cohort
Bangkit Academy • Organisasi
1. Conducted product research and led feature decision- making for the Capstone Product Project at Bangkit Academy using Agile methodologies. Defined key features, set implementable goals, and developed a project schedule to ensure timely delivery and alignment with user and stakeholder
expectations.
2. Design, develop, and implement a natural language processing (NLP) model with a solution that utilizes Transfer Learning and Fine Tuning with a pretrained BERT model for product features with an accuracy rate of over 87% for classifying text related to mental health.
3. Developed and deployed a Flask-based Machine Learning API to predict mental health, categorizing text-based inputs into Anxiety, Depression, and
Stress with real-time predictions.
Juli 2022 - Agustus 2022
Virtual Internship Data Scientist
Home Credit Indonesia • Magang
Process raw data into a clean format that can be used for machine learning analysis and modeling.
Created machine learning models and algorithms to address specific challenges within the credit management system, employing more than 2 different models for comparative analysis.
Applied rigorous hyperparameter adjustments to enhance the accuracy of machine learning models, setting a target accuracy rate of over 85%.
Strived for practical implementation capabilities in real-world applications, achieving an evaluation rate of more than 60%, emphasizing the practicality and impact of the developed models.
Juni 2022 - Juli 2022
Virtual Internship Data Scientist
ID/X Partners • Magang
Leveraged strong programming skills in Python to analyze and process data, aiming to enhance team efficiency through the implementation of machine learning models. Achieved an accuracy rate of over 80% in predictive modeling, contributing significantly to informed and targeted business decision-making and Applied statistical techniques using more than five Python programming language libraries to explore and manipulate quantitative data. This involved the creation of new features necessary for modeling, showcasing adaptability and proficiency in data analysis.
November 2023
TensorFlow: Data and Deployment Specialization
Coursera • 3CKT9S6BLN6C
Media
November 2023
DeepLearning.AI TensorFlow Developer Specialization
Coursera • Y5YEFBKJ7WLM
Media
Oktober 2023
Machine Learning Specialization
Coursera • NHKTK7SWTQ6U
Media
September 2023
Google Data Analytics
Coursera • HC4XWJBH4PPZ