Hi, I am Adli Danial

Project Team (Universiti Tun Hussein Onn Malaysia)

Project Date Start: 17 February 2019

Completion Date: 11 May 2020

Roles: Programmer Developer

Language: ActionScript from Adobe Animate CC

Project Background: Soccer Code is a mobile learning application that focused to introduce the secondary students based on computational thinking skill concept. The Soccer Code was the first of our team project under Diploma Final Year Project at Universiti Tun Hussein Onn Malaysia. A team members such as Harith Imran, Amir Hamzah and Ts. Dr. Ida Aryanie as my supervisor. Soccer Code copyright obtained by ICC UTHM in 2019 and it has published on Google Play only. Soccer Code was using Adobe Animate CC to develop the mobile learning application and it was using ActionScript as a programming language to add complex interactivity, playback control and data display in the mobile application. This mobile learning application took 4 month to complete and implement the usability testing on the High School students from Batu Pahat.

Achievement/Awards:

1. Gold in Innovation Festival Center of Diploma Studies 2019, UTHM

2. Gold in International Research And Innovation Symposium And Exposition (RISE) 2019, UTHM

3. Gold in Karnival Keusahawanan Dan Inovasi Pelajar (KKIP) 2019, UTHM

4. Silver in International e-Learning Carnival & Conference (eLCC 2019), Universiti Teknikal Malaysia Melaka (UTeM)

5. Gold in Perlis International Engineering Invention & Innovation Exhibition (Pi-ENVEX) 2020, UNIMAP

GitHub Resource: Click Here

Project Owner (Universiti Tun Hussein Onn Malaysia)

Project Date Start: 01 October 2021

Completion Date: 01 May 2022

Roles: Programmer Developer

Language: Python, C++

Project Background: IoT Based Smart Farming For Plant Disease Detection is a system based on the Internet of Things (IoT) and a Deep Learning method to develop the classification of plant diseases by using image processing. This IoT-based system was the second project of Final Year Project during the degree studies at Universiti Tun Hussein Onn Malaysia (UTHM). The system provides an image capture module and pre-process by using Tensorflow to show the result of plant disease. The IoT-based solution integrated with Artificial Intelligence (AI) has the potential to help farmers identify the disease in advance and make a better decision on how to treat it. The development of IoT Based Smart Farming For Plant Disease Detection by using Python as a programming language, Flask as a web framework written in Python and these project was running on Anaconda environment. The IoT device called ESP32-Camera to capture the disease of leaf and the system showing the image captured. The Arduino software has been introduced to setup the connection between ESP-32 Camera with IoT-based system. The classification model using Tensorflow will be determined from the image either the plant disease or not.

Achievement/Awards:

1. Gold in International Research And Innovation Symposium And Exposition (RISE) 2022, UTHM

2. Best Of The Best Innovation (Student Category) RISE, 2022

GitHub Resource: Click Here

Project Owner (Information Technology Club, Universiti Tun Hussein Onn Malaysia)

Project Date Start: 16 December 2021

Completion Date: 15 April 2022

Roles: Programmer Developer

Language: HTML, CSS(Bootstrap), JS, PHP, MySQL

Project Background: Ketupat Virtual Run is a system especially registration of virtual run that has been introduce from Information Technology Club (ITC), Faculty of Science Computer and Information Techonology, Universiti Tun Hussein Onn Malaysia (UTHM). Sports and Recreation Exco from ITC has been proposed to create an event called Ketupat Virtual Run. As an exco members, I willingly to create a registration system for students, staff and outsiders to show the current of event that related to virtual run from ITC. The development of Ketupat Virtual Run by using PHP programming language with implement the Model-View-Controller (MVC). The database should be used MySQL and ToyyibPay as a payment gateway for the transaction online such as FPX or Credit Card.

GitHub Resource: Click Here