cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
arif mudi priyatno
Contact Email
arifmudi@aks.or.id
Phone
+6282390449323
Journal Mail Official
institute@aks.or.id
Editorial Address
Jl. HR Soebrantas KM 16.5, Kab. Kampar, Provinsi Riau, 28293
Location
Kab. kampar,
Riau
INDONESIA
Journal of Engineering and Science Application
Published by Institute Of Advanced Knowledge and Science
ISSN : 30470544     EISSN : 30469627     DOI : https://doi.org/10.69693/jesa
Core Subject : Science, Engineering,
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT
Journal of Engineering and Science Application (JESA) is published by the Institute Of Advanced Knowledge and Science in helping academics, researchers, and practitioners to disseminate their research results. JESA is a blind peer-reviewed journal dedicated to publishing quality research results in the fields of Applied Sciences, Engineering and Information Technology. All publications in the JESA Journal are open access which allows articles to be available online for free without any subscription. JESA is a national journal with e-ISSN: 3046-9627, and is have fee of charge in the submission process and review process. Journal of Engineering and Science Application publishes articles periodically twice a year, in April and October. JESA uses Turnitin plagiarism checks, Mendeley for reference management and supported by Crossref (DOI) for identification of scientific paper.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 6 Documents
 1 
Search results for , issue "Vol. 1 No. 2 (2024): October" : 6 Documents clear
Modeling Flood Hazards in Ambon City Watersheds: Case Studies of Wai Batu Gantung, Wai Batu Gajah, Wai Tomu, Wai Batu Merah and Wai Ruhu Rakuasa, Heinrich; Latue, Philia Christi
Journal of Engineering and Science Application Vol. 1 No. 2 (2024): October
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/jesa.v1i2.6

Abstract

Flood hazard modeling in watersheds is an important step in natural disaster risk mitigation, especially in vulnerable areas such as Ambon City. This research focused on the Wai Batu Gantung, Wai Batu Gajah, Wai Tomu, Wai Batu Merah, and Wai Ruhu watersheds, using JRC Global Surface Water Mapping Layers data, NASA SRTM Digital Elevation 30 m data, and USGS Landsat 8 Level 2, Collection 2, Tier 1 data analyzed on the Google Earth Engine (GEE) platform. Prediction of built-up land in flood-prone areas was conducted by utilizing flood history analysis, hydrological modeling, and flood zone mapping. The results show that flood hazard modeling provides a better understanding of flood risk, assists in the development of safer land use planning, and increases public awareness of flood risk in Ambon City. It is hoped that the results of this research can contribute to flood risk management and sustainable regional development in the future.
Prototype of a Virtual Assistant System Integrated with AI Rahardian, Rifky Lana; Sudiatmika, I Putu Gede Abdi; Dewi, Komang Hari Santhi
Journal of Engineering and Science Application Vol. 1 No. 2 (2024): October
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/jesa.v1i2.7

Abstract

This research focuses on the development of a prototype virtual assistant system integrated with artificial intelligence (AI) using the Rational Unified Process (RUP) method. The system is designed to improve user flexibility and efficiency by allowing interaction through voice commands, removing the need for traditional input devices. Python was selected as the primary programming language due to its robust capabilities in handling AI-driven applications. The system utilizes Whisper API for speech recognition, enabling the virtual assistant to accurately interpret voice inputs. Additionally, the integration of Chat GPT API allows the assistant to process and generate responses in a natural, context-aware manner. The combination of these technologies is expected to enhance user experience by making the system more intuitive and seamless, applicable to both daily tasks and complex business environments. The RUP method, structured into phases such as inception, elaboration, construction, and transition, was applied to ensure that the development process was iterative, flexible, and aligned with user needs. The results indicate that the integration of Whisper API with Chat GPT API significantly improves the quality and accuracy of voice-based interaction, streamlining system operation while minimizing the need for complex graphical interfaces. This research demonstrates the potential of voice-driven AI systems in increasing overall operational efficiency.
Heart Disease Prediction Using Decision Tree Analysis Clarite, Princess Clair C.; Palma, Inna Vita Grace Vanya G.
Journal of Engineering and Science Application Vol. 1 No. 2 (2024): October
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/jesa.v1i2.9

Abstract

Heart disease, alternatively known as cardiovascular disease, encases various conditions that impact the heart and is the primary basis of death worldwide over the span of the past few decades. Therefore, if it is possible to predict diseases that has high mortality rate with patient's data and AI system, they would enable them to be detected and be treated in advance. The objective of the research is to use significant features and factors to design a prediction algorithm using Machine learning. The goal is to accurately classify whether a person has heart disease or not. The dataset contains 1025 records. The records are divided into two categories positive those who have heart disease and negative those who do not. It is currently standard practice to divide the data at random into roughly 70% for training and 30% for testing. The researcher used the MATLAB software tool to create a decision tree model of heart disease prediction. Using a decision tree model, it was determined that the best indicator that someone has heart disease is chest pain.
A Robust Hybrid Approach for Malware Detection: Leveraging CNN and LSTM for Encrypted Traffic Analysis Priyatno, Arif Mudi; Ningsih, Yunia; Vandika, Arnes Yuli; Muhammadong, Muhammadong
Journal of Engineering and Science Application Vol. 1 No. 2 (2024): October
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/jesa.v1i2.10

Abstract

The rapid growth in Internet usage and advancements in network technologies have escalated the risk of network attacks. As the adoption of encryption protocols increases, so does the difficulty in identifying malware within encrypted traffic. Malware represents a significant danger in cyberspace, as it compromises personal data and harms computer systems. Network attacks involve unauthorized access to networks, often aiming to disrupt or damage them, with potentially severe consequences. To counter these threats, researchers, developers, and security experts are constantly innovating new malware detection techniques. Recently, deep learning has gained traction in network security and intrusion detection systems (IDSs), with models such as Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) showing promise in detecting malicious traffic. Despite these advancements, extracting relevant features from diverse malware types remains a challenge. Current solutions demand substantial computational resources and are often inefficient for large datasets. Additionally, existing image-based feature extraction methods consume significant resources. This study tackles these issues by employing a 1D CNN alongside LSTM for the detection and classification of encrypted malicious traffic. Using the Malware Analysis benchmark dataset, which consists of 42,797 malware and 1,079 goodware API call sequences, the proposed model achieved an accuracy of 99.2%, surpassing other state-of-the-art models
Enhancing User Experience in Private Bank Mobile Banking: Insights from Management Information System Analysis Hartawan, Muhammad Syarif; Jauhari , Burhanuddin; Vandika, Arnes Yuli; Guterres, Juvinal Ximenes
Journal of Engineering and Science Application Vol. 1 No. 2 (2024): October
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/jesa.v1i2.11

Abstract

This research explores the impact of Management Information Systems (MIS) on user experience in private bank mobile banking, focusing specifically on the effectiveness of m-BCA. Utilizing a descriptive quantitative approach, the study aims to understand how mobile banking features, including accessibility, user interface, security, and functionality, influence user satisfaction. Data were collected through direct experimentation with the m-BCA application, complemented by analysis from secondary data sources and a survey of 30 users. Results indicate that 93.3% of users find m-BCA effective for routine banking needs, attributing high ratings to its convenience and functionality. However, while 80% of respondents appreciate the current security measures, 20% cite the absence of advanced security features such as fingerprint and facial recognition as a drawback. The study also reveals mixed feedback on the user interface; while the straightforward design aids usability, 10% of users express a desire for a more visually appealing interface. Despite these areas for improvement, m-BCA’s comprehensive set of features is generally seen as effective, supporting users in performing essential transactions with ease and reliability. The findings suggest that enhancing interface aesthetics and integrating advanced security options could further boost user engagement and trust in mobile banking applications, underscoring MIS’s role in meeting evolving customer expectations in digital banking.
Realtime Face Recognition System with Viola-Jones and Local Binary Pattern Histogram (LBPH) Method Ridwan, Ahmad; Ferdian, Rian; Parenreng, Jumadi Mabe; Rasyid, M. Udin Harun Al
Journal of Engineering and Science Application Vol. 1 No. 2 (2024): October
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/jesa.v1i2.12

Abstract

The face is one of the body parts that a detection system can detect. This is what underlies the existence of face detection. One technology that uses face identification is biometric identification. The Viola-Jones method determines whether an object is a face by extracting features in a face image and classifying it to decide whether or not it is a face. However, the Viola-Jones method has the disadvantage that it can only detect human faces. This research will combine the Viola-Jones method to recognize human faces with the Local Binary Pattern Histogram (LBPH) method. The result is that the system can detect and identify up to two human faces facing forward, sideways, up, and down for the database. An accuracy calculation is also added to measure the accuracy of face recognition after the database is retrieved and trained. This average percentage of correctness is taken from comparing the predicted face to be recognized with the face that will be recognized. The result will be compared again with the number of photos taken during the recognition process and multiplied by 100%.

Page 1 of 1 | Total Record : 6

 1 

Filter by Year

2024 2024


Reset
Filter By Issues
All Issue Vol. 2 No. 2 (2025): October Vol. 2 No. 1 (2025): April Vol. 1 No. 2 (2024): October Vol. 1 No. 1 (2024): April