Key Skills

Software

Data Annotation Tech

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Document

Text

Top Task Types

Classification

Data Collection

Text Generation

Translation Localization

Freelancer Overview

I have hands-on experience in AI training and evaluation, where I contributed to improving conversational AI systems by engaging in dialogues with chatbots and performing response comparison tasks. This work required strong attention to detail, critical thinking, and data validation skills to ensure the accuracy and quality of outputs. Due to a signed NDA, I cannot disclose specific project details, but the experience strengthened my ability to work with AI models in a structured and systematic way. In addition to AI training, I bring a background in Information Systems with practical knowledge in data management, problem-solving, and digital content creation. I am proficient in tools such as Figma, CorelDRAW, Microsoft Office, and Google Workspace, and I have a strong interest in user experience and data-driven processes. These skills, combined with my adaptability and enthusiasm for learning, allow me to contribute effectively to AI training and data labeling projects across various industries.

Labeling Experience

Multi Turn Chatbot Response Review

Data Annotation TechTextText GenerationText Summarization

Evaluation and improvement of chatbot responses with a focus on adapting to local language style (Bahasa Indonesia). Tasks included prompt creation, model response evaluation, follow-up prompting, multi-turn chat review, response refinement, model deficiency classification, and inter-model answer comparison. The project ran for one month (5 working days per week) with an average of 5 multi-turn sessions per day. Quality assurance was maintained through double-check reviews by a reviewer.

Evaluation and improvement of chatbot responses with a focus on adapting to local language style (Bahasa Indonesia). Tasks included prompt creation, model response evaluation, follow-up prompting, multi-turn chat review, response refinement, model deficiency classification, and inter-model answer comparison. The project ran for one month (5 working days per week) with an average of 5 multi-turn sessions per day. Quality assurance was maintained through double-check reviews by a reviewer.

2025

Education

Work History