Curriculum Vitae
Muhammad Nur Irfan
A passionate student from Polytechnic State of Jakarta majoring in Technical Information with hands-on experience through MSIB and a project-based role at Lokatani as a Machine Learning Developer. Successfully delivered an AI-powered application to solve manual inventory listing challenges for Lokatani, using Python, TensorFlow, and Scikit-learn. Well-equipped with analytical thinking, cross-functional collaboration and communication skills proven by successful on-campus projects.
Sedang berjalan
POLITEKNIK NEGERI JAKARTA
D4 • Teknik Informatika • IPK 3.86
Mei 2022
SMAN 67 JAKARTA
SMA/SMK • Ilmu Pengetahuan Alam (IPA) • Nilai rata-rata: 92.17
Juli 2025 - November 2025
Internship Information Technology (IT) - Kimia Farma Apotek (KFA)
PT Kimia Farma Tbk • Magang
Februari 2025 - Sekarang
Machine Learning Cohort
Dicoding • Part Time
Collaborated with a cross-functional team of six machine learning engineers and full-stack developers to build HexaMood, a mental health platform designed for Gen Z users. The application detects stress levels through five self-assessment questions, provides a journaling feature with sentiment analysis, and offers emotion tracking with personalized recommendations to support early stress intervention. I fine-tuned an IndoBERT-based sentiment classification model using the Transformers library, achieving 90% accuracy across five emotional categories. I also designed and deployed the full ML pipeline using FastAPI and Docker, and integrated it with the frontend via Hugging Face Spaces, enabling real-time predictions and a seamless user experience.
Februari 2025 - Sekarang
Machine Learning Developer
Lokatani • Project Base
Developed an AI-powered mobile application to automate inventory listing for agricultural stakeholders, reducing human error and increasing efficiency. As part of a 4-member team, I built a deep learning model for vegetable classification (98.2% precision) with YOLO, an OCR pipeline for digital scale readings (95% accuracy), and a demand forecasting model (R² = 0.82) to support supply planning. I also integrated a chatbot with Retrieval-Augmented Generation (RAG) for dynamic responses and deployed all ML components on Google Cloud Platform using Docker. My role included ensuring seamless client-team communication to align the solution with real-world needs and deliver measurable impact in the field.
September 2024 - Desember 2024
Data Science Trainee
PT Talenta Group • Part Time
Completed an intensive program covering SQL querying, Python programming, practical machine learning, deep learning, and natural language processing, with hands-on projects and real-world business case applications. Led a team of 4 and developed a machine learning model that segmented 750+ coffee shop transactions into 3 distinct clusters including chatbot with Python and Langchain to enhance decision-making efficiency. Achieved a project evaluation score 93.77/100 from mentors reflecting high satisfaction with business impact, technical execution, and team leadership.
September 2020 - Februari 2022
Social Media Analyst
Esportsku • Pekerja Lepas
As a freelance content creator in the esports domain, I successfully increased Instagram follower growth by 38% through audience behavior analysis and aligning content with trending esports narratives. I designed visually engaging content using Adobe Illustrator, tailored to resonate with the preferences and culture of the esports community. By closely monitoring engagement metrics via Instagram Business tools, I continuously iterated on content formats to optimize visual performance and audience interaction.
Mei 2025
Machine Learning Terapan
Dicoding • 1OP82QLWLPQK
- Machine Learning System Design
- Menyusun Proyek Machine Learning
- Studi Kasus Pertama terkait Predictive Analytics
- Studi Kasus Kedua tentang Analisis Sentimen
- Studi Kasus Ketiga dengan topik Computer Vision
- Studi Kasus Keempat mengenai Sistem Rekomendasi
Media
April 2025
Belajar Pengembangan Machine Learning
Dicoding • RVZKW295QZD5
This program provided hands-on training in deep learning, covering neural network development using TensorFlow and Keras. It included practical applications in Natural Language Processing, time series analysis with LSTM and RNN, image classification, and recommendation systems. The curriculum also introduced reinforcement learning concepts, model deployment strategies, and generative AI for content creation such as images and text.
Media
Maret 2025
Belajar Analisis Data dengan Python
Dicoding • MEPJQO67LX3V
This program provided a strong foundation in data analysis, starting with core concepts and workflows, including descriptive statistics and key considerations in data processing. Participants learned essential data wrangling techniques to clean and prepare datasets for analysis, followed by hands-on application of Exploratory Data Analysis (EDA) to uncover meaningful insights. The course also covered effective data visualization methods to enhance communication of analytical results, and introduced dashboard development using Streamlit for interactive data presentation. The program concluded with an evaluation phase, including a final exam and a capstone project, where participants applied Python to complete an end-to-end data analysis task.
Media
November 2024
Public Bootcamp Artificial Intelligence Track
Startup Campus • 2fb1d79c-2366-4f5d-91f9-6b4928ea2825
Media
Oktober 2024
Public Bootcamp Data Science Track
Startup Campus • 372169ca-da77-4e90-974a-87639656f14d