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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 23 Documents
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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%.
Analysis and Evaluation of Land Suitability in Kupang City, Indonesia for Sustainable Settlement Development Rakuasa, Heinrich
Journal of Engineering and Science Application Vol. 2 No. 1 (2025): April
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/jesa.v2i1.13

Abstract

Kupang City, as the capital of Nusa Tenggara Timur Province, faces significant challenges in land management and settlement development due to rapid population growth and urbanization. This study aims to analyze and evaluate land suitability for sustainable settlement development, considering relevant environmental factors. The method used is Spatial Multi-Criteria Analysis (SMCA), which integrates geospatial data from the Digital Elevation Model (DEM), including slope, road networks, rivers, economic activity centers, and coastlines. The analysis results indicate that out of the total area analyzed, 7,227.04 hectares have high suitability, 4,341.12 hectares have moderate suitability, and 3,967.85 hectares have low suitability. Areas with high suitability are generally located near roads, economic activity centers, have lower slope gradients, and are far from rivers and coastlines, making them ideal for infrastructure development. The discussion emphasizes the importance of spatial and participatory-based spatial planning, as well as the need for monitoring low-suitability areas to prevent disaster risks. In conclusion, this study provides policy recommendations for more sustainable settlement development in Kupang City, integrating land suitability analysis and involving the community in the planning process, thereby creating
Human Resource Transformation through the Development of the AKHLAK Core Values Model to Enhance Organizational Performance Efficiency Hasibuan, Abdurrozzaq; Nasution, Suhela Putri
Journal of Engineering and Science Application Vol. 2 No. 1 (2025): April
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/jesa.v2i1.16

Abstract

The increasingly dynamic business environment compels State-Owned Enterprises (SOEs) to undergo comprehensive transformation, particularly in the management of human resources (HR). PT Perkebunan Nusantara IV (PTPN IV), as a plantation-sector SOE, faces challenges in fostering a work culture that is adaptive, competent, and value-driven. The background of this research stems from the limited effectiveness of organizational values internalization and the suboptimal efficiency of organizational performance. The central research question is how to develop an HR transformation model based on the Core Values of AKHLAK (Trustworthy, Competent, Harmonious, Loyal, Adaptive, and Collaborative) that can enhance organizational performance efficiency. This study aims to design and test a value-based model of AKHLAK implementation within the framework of work culture transformation at PTPN IV. The research applies a mixed methods approach, combining quantitative surveys, in-depth interviews, and document analysis. Preliminary findings indicate that AKHLAK values are significantly associated with the development of work behavior and habits that support sustainable organizational performance. The proposed model is expected to serve as a strategic reference for value-based HR transformation in SOEs.
The Duration of Sodium Methoxide Catalyst Impregnation in Methanol and Its Impact on the Reduction Monoglyceride Content in Biodiesel Production Sinaga, Boy Andika; Darma, Frandika; Rahmadhani, Rahmadhani
Journal of Engineering and Science Application Vol. 2 No. 1 (2025): April
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/jesa.v2i1.17

Abstract

Biodiesel is one of the most promising alternatives to replace conventional fuel products, specifically diesel. The increasing use of biodiesel is currently a focus of many researchers aiming to improve its quality, one of which involves reducing the monoglyceride content. High monoglyceride content can cumulatively affect the performance of diesel engines. Several techniques are used to reduce the monoglyceride content in biodiesel, one of which is maximizing the transesterification reaction. This study focuses on the preparation stage before the transesterification reaction, where the treatment involves variations in the impregnation of sodium methoxide (NaOCH3) in methanol (CH3OH). The impregnation durations tested were 0, 10, 20, 30, and 40 minutes during chemical mixing. The transesterification process was then carried out at reaction temperatures of 62°C and 64°C. The results indicate that the duration of impregnation between sodium methoxide (NaOCH3) and methanol (CH3OH) affects the reduction of the monoglyceride content. The optimal condition identified in this study was an impregnation duration of 20 minutes at a reaction temperature of 62°C, which resulted in a monoglyceride content of 0.3629%.
Spatial Analysis of Vegetation Density Using MSARVI Algorithm and Sentinel-2A Imagery in Ternate City, Indonesia Rakuasa, Heinrich; Budnikov, Viktor Vladimirovich
Journal of Engineering and Science Application Vol. 2 No. 1 (2025): April
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/jesa.v2i1.14

Abstract

This study aims to analyze vegetation density in Ternate City, Indonesia, using the Modified Soil-Adjusted and Atmospherically Resistant Vegetation Index (MSARVI) algorithm and Sentinel-2A images processed through Google Earth Engine. The analysis results show that the vegetation density index values range from -0.54 to 1.16, with normalization resulting in four density classes: low, medium, dense, and very dense. Ternate Island sub-district had the largest area of very dense vegetation (4,133.12 hectares), while Ternate Tengah sub-district showed the lowest vegetation density, reflecting the significant impact of urbanization. This study revealed that despite anthropogenic pressures, Ternate Island remains an ecologically critical zone. These findings emphasize the importance of conservation efforts and afforestation initiatives to improve environmental resilience amidst the growing challenges of climate change and urban development.
Harmony of Technology and Nature: A Systematic Analysis of Renewable Energy Development Prasetya, Luhur Adi; Wibawanto, Slamet; Mahandi, Yogi Dwi
Journal of Engineering and Science Application Vol. 2 No. 1 (2025): April
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/jesa.v2i1.15

Abstract

The transition to renewable energy is an important step to address the energy crisis and global climate change. Renewable energy technologies, such as solar panels, wind turbines, and energy storage systems, have developed rapidly with increasing efficiency, such as the 45% efficiency of solar panels. However, key implementation challenges include dependence on weather conditions that affect the stability of energy supply as well as cost and infrastructure constraints. Fiscal incentives and carbon pricing policies have proven effective in driving renewable energy adoption, as seen in Germany and China. On the other hand, artificial intelligence (AI) and blockchain technologies are playing a role in improving energy distribution efficiency and power consumption optimization, while the renewable energy sector has created millions of jobs with a projected increase to 35 million by 2030. However, investment inequality between developed and developing countries remains a major challenge. Therefore, accelerating the green energy transition requires policies that simplify licensing procedures, support technological innovation, and encourage collaboration between the public and private sectors. This research highlights the importance of a holistic approach covering technology, policy and investment aspects to realize a more efficient, inclusive and environmentally sustainable energy system.
Stock Price Prediction Modeling Using Recurrent Neural Network and Long-Short Term Memory Salsabila, Afrida Nur; Anwariningsih, Sri Huning; Susilo, Dahlan
Journal of Engineering and Science Application Vol. 2 No. 1 (2025): April
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/jesa.v2i1.20

Abstract

Stock price fluctuations were very difficult to predict the direction of the changes. There were generally estimated to follow three analysis techniques: technical, fundamental, and sentiment. Technical analysis involves observing prices in the past, fundamental analysis is related to the analysis of ongoing business situations, while sentiment analysis includes stock prices that were affected by business aspects, current information, and business activities. Valid price data of the BCA Company used was the stock price from 2019 until 2024. The purpose of this study is to find alternative models of the RNN and LSTM models. The methods used in this study are the documentation method and the optimization method. Accuracy measurements used Mean Square Error (MSE) and Mean Absolute Error (MAE) metrics. The results of stock prediction using the RNN model got poor results with epoch 10 obtaining an accuracy of 61.3%, while using the LSTM model obtained quite good results with epoch 10 obtaining an accuracy of 87.7%. Stock predictions using the combined RNN-LSTM models were able to get good results with epoch 10 obtaining an accuracy of 93.3%.
Globalization And Digital Transformation As Demographic And Green Economic Policies In Southeast Asia Hamka, Hamka
Journal of Engineering and Science Application Vol. 2 No. 1 (2025): April
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/jesa.v2i1.23

Abstract

Developing countries in Southeast Asia are still relatively young compared to other regions around the world. However, recent statistics suggest that the situation is beginning to change in this regard, with many of these populations aging at a much faster rate than in many other countries. These developments require urgent policy action to create a sustainable path to economic growth before demographic changes become less benign in the medium term. discusses the economic consequences of population aging, rising economic support ratios, and declining potential growth rates. It is critical for developing countries in Southeast Asia to increase their total productivity (TFP) growth rates to achieve more sustainable economic outcomes. By conducting panel regressions using data from 82 countries over the study period 1996–2019, our study shows that increasing research and development (R&D) spending and facilitating structural changes that transform the digital economy landscape are key policy options that boost TFP growth. Globalization has significantly affected the economy, ecology, and society over the past decade. Meanwhile, the green economy has emerged as an important policy framework for growth and development in both developed and developing countries. The current study is an attempt to provide a detailed overview of globalization, green economy, and climate challenges to draw some implications. There is disagreement between competing green economy discourses and various definitions, all of which have problems. Recognizing the environmental impacts of natural resource depletion and the economic benefits of environmental management are common examples of operationalizations of the green economy. The new study also examines the impact of climate change on the green economy and infrastructure development.
Covid-19 Risk Model Development Using Fuzzy Logic For The Reopening Of Face-To-Face Classes Candia Jr, Jose; Gonzales, Ike; Frayco, Joenil; Jabel, Cristy Lou; Ronquillo, Ariston; Sambalod, Zarina Gail D.
Journal of Engineering and Science Application Vol. 2 No. 2 (2025): October
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/jesa.v2i2.31

Abstract

COVID-19 pandemic had caused a global crisis in the education sector due to the urgent closure of schools to prevent the spread of the virus. After so much effort to curb the transmission of Coronavirus, the Philippine government has finally approved the re-opening of face-to-face classes in colleges and universities. However, responding to educational needs might pose COVID risks to the academic community. Thus, this study used the Fuzzy Logic to develop a model to measure the risk associated with COVID under the Northeastern Mindanao State University – Tagbina campus condition. Results showed that developed model using Fuzzy Logic algorithm produced satisfying result after expert validation in assessing Covid-19 risk transmission. Further, using the developed model, the campus has 38.5% risk, classified as "Low”. Despite challenges in opinions of multiple experts, the model was able to draw conclusion in support to campus management’s decision-making pertaining to campus risk of covid transmission.
Trends and Potential of Geographic Information Systems in Dengue Management: Bibliometric Analysis Crispin, Andrian Reinaldo; Edbert, Edbert; Hulu, Victor Trismanjaya; Kamble, Pratik Bibhisan; Dharma, Abdi
Journal of Engineering and Science Application Vol. 2 No. 2 (2025): October
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/jesa.v2i2.32

Abstract

Dengue fever remains a significant public health issue in many countries. Its high prevalence highlights the need for effective tools like Geographic Information Systems (GIS) to help predict and manage the spread of the disease. This study aims to examine and summarize the role of GIS in mapping and communicating dengue transmission patterns. A bibliometric approach was used to collect relevant literature from databases such as Google Scholar, Scopus, and PubMed. Out of 440 identified articles, only 11 met the inclusion criteria. Data extracted included publication years (2013–2023), journal titles, study designs, populations, interventions, outcomes, and reported benefits of GIS in dengue-related research. Qualitative analysis was conducted by organizing and presenting key findings. The results show that GIS is valuable in identifying current outbreak areas, detecting high-risk zones through spatial clustering, improving the accuracy of case predictions, and supporting ongoing surveillance efforts. Additionally, GIS contributes to more informed decision-making in dengue prevention and control programs. Overall, GIS plays an essential role in understanding disease dynamics, enhancing early warning systems, and guiding public health responses to dengue outbreaks.

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