
Universitas Putra Indonesia "YPTK" Padang
My Data Science concentration provided an academic foundation in data processing and analysis. My Informatics Engineering studies covered software engineering, data structures and algorithms, relational databases, web programming, and information systems security. My thesis applied an LSTM deep-learning model to tropical cyclone track prediction and delivered the results as a web application.

Built a hybrid Next.js App Router application: static pages use SSG for fast delivery, while announcements use SSR with periodic ISR revalidation. Zod validates form schemas to protect data integrity.

My undergraduate thesis project evaluating LSTM for tropical cyclone track prediction. Across 12 experiments (3 basins × 4 timestep variations), the 8–16 window achieved a 14.2 km average error and R² of 0.999. The model was converted to ONNX to run in the browser with an Astro island-based frontend.

A car showroom website where buyers can explore vehicles, filter by specifications, and calculate down payments and monthly installments in real time. Dealers can manage inventory through a structured CMS.

A property search application built with Angular Standalone Components and TypeScript. It features side-by-side comparison, zoomable multi-level 2D floor plans, and a mortgage simulator using Bank Indonesia's annuity formula, powered by Angular Signals.
I am Ikhwan Ramadhan, a Computer Science graduate from Universitas Putra Indonesia “YPTK” Padang. My professional focus is software engineering: building applications from frontend to backend, including REST APIs, databases, testing, and deployment. Data Science is a complementary part of my academic background.
For me, development is not only about making something work. It is also about understanding why it fails, finding the cause, and improving the solution. I keep exploring technologies and approaches through the projects I build.
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This intermediate assessment tested more complex algorithmic problem-solving, including runtime optimization, choosing suitable data structures, and handling edge cases. I took it to strengthen my algorithmic foundations beyond building user interfaces.

Advanced topics in computer vision, NLP, and integrating AI models through APIs. This knowledge supported packaging my thesis LSTM model with ONNX Runtime and integrating it into a tropical cyclone prediction web application.

Although my primary focus is web development, understanding networking and data communications is important. This certification helped me understand client-server requests, latency, DNS and routing, and how to troubleshoot network issues during deployment.
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Passed HackerRank's Basic problem-solving assessment, demonstrating the ability to solve fundamental algorithms and data-structure challenges within a time limit. It reinforced my habit of breaking problems into structured steps before coding.
My primary focus is building modern, responsive, and well-structured web applications.
Building efficient REST endpoints, validating data, and integrating relational databases.
Structured development workflows using Git, functional testing, and CI/CD releases.
My academic concentration and thesis complement software engineering with foundations in data processing and model evaluation.
I am open to Junior Web Developer opportunities focused on Next.js and React.js, with full-stack and deployment experience.