Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Jurnal Ilmu Pendidikan Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika
Perdana Putra, Muhammad Ricky
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Education

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Analysis and Design of Responsive Web-Based Learning Media Equipped with Pomodoro Feature in the Course of Software Engineering Patmanthara, Syaad; Perdana Putra, Muhammad Ricky; Soraya, Dila Umnia
Jurnal Ilmu Pendidikan Vol 30, No 1 (2024): June
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um048v30i1p7-18

Abstract

The development of information and communication technology has brought about changes in the field of education, one of which is the emergence of web-based learning. Based on preliminary observation data collected through questionnaires, students still expressed uncertainty about their understanding of software engineering (SE) materials. The current learning media for SE include PowerPoint (PPT), e-modules, and instructional videos, which students find less engaging and challenging to comprehend. Additionally, students face distractions like games and social media, leading to difficulty maintaining focus while studying. The objectives of this research are (1) to analyze user and system needs and (2) to design web-based responsive learning media for the software engineering course, equipped with a Pomodoro feature. The research method used is research and development (R and D) with the 4D Thiagarajan development model, consisting of four stages: define, design, develop, and disseminate. However, only the definition and design stages were carried out due to research limitations. The presentation of data analysis results involves (1) needs analysis, which includes frontend analysis, learner analysis, task analysis, concept analysis, and specifying instructional objectives; (2) system design, which includes context diagrams and data flow diagrams; (3) database design, which includes Entity Relationship Diagram (ERD) and database file structure; (4) initial design in the form of a prototype; (5) technology design for development and implementation; and (6) instructional media testing design
Flood Prediction Using Machine Learning Model Integrated with Geographical Information System Perdana Putra, Muhammad Ricky; Rama Ashari; Muhirin; Azib Widad Zuhaily Imam; Kusrini
Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika Vol. 10 No. 2 (2024): Oktober 2024
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v10i2.3723

Abstract

Flooding in Indonesia is still a frequent natural disaster compared to other types of disasters. In addition, the number of flood events also shows an increase every year. This research aims to develop a flood prediction model as a preventive measure as an early warning system and flood risk mitigation management that may occur based on Geographical Information System (GIS). It is expected that areas that have the potential to experience flooding can be more proactive in making preparations before flooding. This prediction model uses a classification type machine learning (ML) algorithm with training data involving rainfall within 12 months. The model evaluation results use two techniques: confusion matrix and K-Fold cross validation and each fold is calculated for accuracy. The K-Nearest Neighbors (KNN) model with a value of K = 31 gets the highest accuracy value of 88.89%, Decision Tree (DT) of 72.22%, and Naive Bayes of 78%. The average accuracy using K-Fold resulted in 89.09% for KNN, 77.12% for DT, and 86.59% for Naive Bayes. By considering these results, this research chose the KNN method to be applied in the prediction model. The code was rewritten in the Flask framework to be used as an API and integrated with Laravel as a Backend platform and Frontend using Bootstrap, JQuery, Axios, and LeafletJS as map visualisation. With this research, it is hoped that it can be one of the solutions in predicting as well as early warning of floods so that it can provide sufficient time for affected residents to make preparations for flooding.
Co-Authors Azib Widad Zuhaily Imam Dila Umnia Soraya KUSRINI Muhirin Rama Ashari Syaad Patmanthara