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Andri Pranolo
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Office 1 ASCEE Secretariat RUMAH KOTAK Jl. Kranginan, Mertosanan Kulon, Potorono, Kec. Banguntapan, Kabupaten Bantul, Daerah Istimewa Yogyakarta 55196, Indonesia Office 2 ASCEE Secretariat Jl. Raya Janti No.130B, Karang Janbe, Karangjambe, Kec. Banguntapan, Kabupaten Bantul, Daerah Istimewa Yogyakarta 55198, Indonesia
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Applied Engineering and Technology
Published by Association for Scientific Computing Electronics and Engineering
ISSN : -     EISSN : 28294998     DOI : http://dx.doi.org/10.31763/aet
Core Subject : Science, Engineering,
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology
Applied Engineering and Technology provides a forum for information on innovation, research, development, and demonstration in the areas of Engineering and Technology applied to improve the optimization operation of engineering and technology for human life and industries. The journal publishes original papers, review articles, technical notes, and letters to the editor. Authors are encouraged to submit manuscripts that bridge the gaps between research, development, and implementation. The breadth of coverage ranges from innovative technologies and systems of implementation and application development to better human life and industry. The following scope are welcome: Aerospace Engineering, Automobile Engineering, Applied Mathematics, Applied Physics, Bioinformatics, Biophysics, Biotechnology, Chemical Engineering, Chemical Physics, Civil Engineering, Computational Physics, Computer Engineering, Electrical Engineering, Electronic Engineering, Energy Engineering, Environment Engineering, Information Technology, Marine engineering, Mechanical engineering, Medical Engineering, Medical imaging, Medical Physics, Nanotechnology, Ocean Engineering, Optical engineering, Photonics, Robotics, Urban Engineering and Other related engineering topics in general.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 53 Documents
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Performance analysis of random forest on quartile classification journal Sucahyo, Cornaldo Beliarding; Rizqini, Fajriwati Qoyyum; Naufal, Ayyub; Yandratama, Hengky; Shiddiqy, Jabar Ash; Utama, Agung Bella Putra; Putri, Nastiti Susetyo Fanany; Wibawa, Aji Prasetya
Applied Engineering and Technology Vol 3, No 1 (2024): April 2024
Publisher : ASCEE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/aet.v3i1.1189

Abstract

Journals play a pivotal role in disseminating scientific knowledge, housing a multitude of valuable research articles. In this digital age, the evaluation of journals and their quality is essential. The SCImago Journal Rank (SJR) stands as one of the prominent platforms for ranking journals, categorizing them into five index classes: Q1, Q2, Q3, Q4, and NQ. Determining these index classes often relies on classification methodologies. This research, drawing inspiration from the Cross-Industry Standard Process for Data Mining (CRISP-DM), seeks to employ the Random Forest method to classify journals, thus contributing to the refinement of journal ranking processes. Random Forest stands out as a robust choice due to its remarkable ability to mitigate overfitting, a common challenge in machine learning classification tasks. In the context of approximating SJR index classes, Random Forest, when utilizing the Gini index, exhibits promise, albeit with an initial accuracy rate of 62.12%. The Gini index, an impurity measure, enables Random Forest to make informed decisions while classifying journals into their respective SJR index classes. However, it is worth noting that this accuracy rate represents a starting point, and further refinement and feature engineering may enhance the model's performance. This research underscores the significance of machine learning techniques in the domain of journal classification and journal-ranking systems. By harnessing the power of Random Forest, this study aims to facilitate more accurate and efficient categorization of journals, thereby aiding researchers, academics, and institutions in identifying and accessing high-quality scientific literature.
AQuamoAS: unmasking a wireless sensor-based ensemble for air quality monitor and alert system Geteloma, Victor Ochuko; Aghware, Fidelis Obukohwo; Adigwe, Wilfred; Odiakaose, Chukwufunaya Chris; Ashioba, Nwanze Chukwudi; Okpor, Margareth Dumebi; Ojugo, Arnold Adimabua; Ejeh, Patrick Ogholuwarami; Ako, Rita Erhovwo; Ojei, Emmanuel Obiajulu
Applied Engineering and Technology Vol 3, No 2 (2024): August 2024
Publisher : ASCEE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/aet.v3i2.1409

Abstract

The increased awareness by residents of their environment to maintain safe health states has consequently, birthed the integration of info tech to help resolve societal issues. These, and its adopted approaches have become critical and imperative in virtualization to help bridge the lapses in human mundane tasks and endeavors. Its positive impacts on society cannot be underestimated. Study advances a low-cost wireless sensor-based ensemble to effectively manage air quality tasks. Thus, we integrate an IoT framework to effectively monitors environment changes via microcontrollers, sensors, and blynk to assist users to monitor temperature, humidity, detect the presence of harmful gases in/out door environs. The blynk provides vital knowledge to the user. Our AQuaMoAS algorithm makes for an accurate and user-friendly mode using cloud services to ease monitor and data visualization. The system was tested at 3 different stages of rainy, sunny and heat with pollutant via alpha est method. For all functions at varying conditions, result revealed 70.7% humidity, 29.5OC, and 206 ppm on a sunny day. 51.5% humidity, 20.4OC and 198ppm on a rainy, and 43.1 humidity, 45.6OC, 199ppm air quality on heat and 66.5% humidity, 30.2 OC and 363 ppm air quality on application of air pollutant were observed
Impact of Foaming Agent: Water Ratio on Foam Stability of Lightweight Concrete Prajapati, Abhilasha; Kumar, Rajesh; Maiti, Soumitra; lakhani, Rajni; Yadav, Amit
Applied Engineering and Technology Vol 3, No 2 (2024): August 2024
Publisher : ASCEE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/aet.v3i2.1397

Abstract

Foamed concrete, renowned for its lightweight nature and thermal insulating properties, has gained substantial interest in the construction industry. The stability of foamed concrete is directly related to the stability of preformed foam used for making foamed concrete. Foam stability is the prime factor which influences the overall performance and properties of the foamed concrete. Foam stability refers to the ability of the foam to maintain its structure and volume over time. The stability of foamed concrete is greatly impacted by the selection of the foaming agent and the ratio of foaming agent to water (FA/W). Protein based foaming agent (as per ASTM C796/C796M-19) has been used for this study. An excess of water can weaken the foam structure, leading to instability, while inadequate water can lead to issues such as reduced workability and uneven distribution of foam within the mixture. This paper investigates the effect of FA:W ratio on the stability of foam concrete. Three different FA:W ratio i.e. 1:10, 1:20 and 1:30 has been used for this study. Respective slumps to these ratios have also been investigated at different time intervals to check their consistencies. Three mix proportions were used to produce foam concrete of 1000kg/m3 density. Impact of aforementioned FA/W ratios on the properties of foamed concrete (As per; IS 2185 part-4) were discussed in this article.
[AET Volume 2 Nomor 3] Environmental, medical, and educational research sustainability in the age of technology: An editorial review Pranolo, Andri; Hernandez, Leonel; Wibawa, Aji Prasetya
Applied Engineering and Technology Vol 2, No 3 (2023): December 2023
Publisher : ASCEE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/aet.v2i3.1363

Abstract

The six articles on Applied Engineering and Technology Volume 2 No 3 December 2023 have significant relevance in current engineering and technological developments to the three sectors: Environmental sustainability, Medical, and Education. First, in an era that increasingly pays attention to environmental sustainability, as reflected in efforts to mitigate the environmental impact of the oil and gas industry, Effiom's research on developing bio-based drilling fluid becomes relevant and reflects the industry's efforts to adopt environmentally friendly solutions in the oil and gas exploration process [1]. This research develops and optimizes local pear seed-based biocyte fluid. Throughout the world, oil exploration and exploitation have had severe environmental impacts. So, it is very important to develop drilling fluid for oil exploration. This research optimizes drilling fluids by using biodegradable materials. The optimized drilling fluid contains environmentally friendly and cost-effective characteristics and is expected to be widely used in oil exploration, reducing adverse environmental impacts. Princewill et al. [2] conducted a safety and economic evaluation of boil-off gas (BOG) in global petroleum (LPG) storage tanks. BOG production impacts safety and economic profitability in the liquefied petroleum gas supply chain. This research evaluates BOG production due to heat leaks in storage tanks by analyzing thermodynamic properties and heat transfer equations. The research results show that maintaining isolation and external factors minimizes BOG formation. Therefore, this research provides essential guidance and suggestions for the safety and economic benefits of the liquefied petroleum gas supply chain. Finally, Yudanto et al. [3] used computational fluid dynamics (CFD) and Taguchi methods to calculate the CPU cooling system. The performance and stability of electronic devices are significant for users in today's rapid development of information technology. This study analyzes the impact of different cooling system configurations on CPU temperatures and provides practical insights into electronic thermite design. Through numerical simulations, the research results provide an essential reference for developing computer hardware design. Second, Agughasi and Srinivasiah [4] developed a semisupervised method for characterizing multiple chest X-ray images in the medical field. Accurate marker images are critical for training supervised learning models in medical image handling. However, manually tagging a large number of images requires time and effort. Therefore, this study suggests using unsupervised cluster technology-based K-Means and Self-Organizing Maps to produce reliable images. In this way, medical imaging processing costs can be reduced significantly, speeding up the research and application process. Meanwhile, in the education sector, Mariscal et al. [5] developed the mobile application MobILcaps to improve information literacy for social science students in higher education as a relevant instrument to facilitate teaching. Information literacy is crucial for developing individuals and society in today's information era. Based on cognitive, constructivist, and connectivity theories, this application has provided multimedia resources for students to facilitate independent learning. By working with teachers and students, this application provides practical tools and avenues for increasing students' information literacy levels. In addition, Riva et al. [6] developed AdPisika as an electronic learning system tailored to improve student academic achievement. In today's educational environment, personalized learning is critical to increasing the impact of learning for students. This research, based on learning style models and machine learning algorithms, personally optimizes learning materials, thereby improving students' learning performance. This system has significantly improved students' academic performance through experimental verification, providing practical ways to align education. In conclusion, these studies make essential contributions and provide valuable references and guidance for applying engineering and technology research and practice in the fields of Environmental sustainability, Medical, and Education. Future research could investigate the depth and breadth of these areas and test the feasibility and effectiveness of such research through practical applications and experimental testing. In the context of environmental sustainability potential research includes exploration in the development of bio-based drilling fluid using alternative materials that are more environmentally friendly, research on green technology to reduce the impact of boil-off gas (BOG) in the LPG industry, and research on processor types and system configurations as well as the development of more efficient materials and more innovative cooling technology to improve the performance of the CPU cooling system. In the medical field, deepen semi-supervised labeling methods for medical image processing can focus on developing more sophisticated algorithms and further validation of various medical datasets. Meanwhile, in the educational context, developing broader mobile applications could increase information literacy. It could be useful if it adapted to various disciplines and research on integrating more advanced AI technology for adaptive e-learning systems more effectively.
Enhanced data augmentation for predicting consumer churn rate with monetization and retention strategies: a pilot study Geteloma, Victor Ochuko; Aghware, Fidelis Obukohwo; Adigwe, Wilfred; Odiakaose, Chukwufunaya Chris; Ashioba, Nwanze Chukwudi; Okpor, Margareth Dumebi; Ojugo, Arnold Adimabua; Ejeh, Patrick Ogholuwarami; Ako, Rita Erhovwo; Ojei, Emmanuel Obiajulu
Applied Engineering and Technology Vol 3, No 1 (2024): April 2024
Publisher : ASCEE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/aet.v3i1.1408

Abstract

Customer retention and monetization have since been the pillar of many successful firms and businesses as keeping an old customer is far more economical than gaining a new one – which, in turn, reduce customer churn rate. Previous studies have focused on the use of single heuristics as well as provisioned no retention strategy. To curb this, our study posits the use of the recen-cy-frequency-monetization framework as strategy for customer retention and monetization impacts. With dataset retrieved from Kaggle, and partitioned into train and test dataset/folds to ease model construction and training. Study adopt a tree-based Random Forest ensemble with synthetic minority oversampling technique edited nearest neighbor (SMOTEEN). Various benchmark models were trained to asssess how well each performs against our proposed ensemble. The application was tested using an application programming interface Flask and integrated using streamlit into a device. Our RF-ensemble resulted in a 0.9902 accuracy prior to applying SMOTEENN; while, LR, KNN, Naïve Bayes and SVM yielded an accuracy of 0.9219, 0.9435, 0.9508 and 0.9008 respectively. With SMOTEENN applied, our ensemble had an accuracy of 0.9919; while LR, KNN, Naïve Bayes, and SVM yielded an accuracy of 0.9805, 0.921, 0.9125, and 0.8145 respectively. RF has shown it can be implemented with SMOTEENN to yield enhanced prediction for customer churn prediction using Python
Deep learning-based cervical lesion segmentation in colposcopic images Mukku, Lalasa; Thomas, Jyothi
Applied Engineering and Technology Vol 3, No 1 (2024): April 2024
Publisher : ASCEE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/aet.v3i1.1345

Abstract

Artificial intelligence assisted cancer detection has changed the ream of diagnosis precision. This study aims to propose a segmentation network using artificial intelligence for accurately segmenting the cervix region and acetowhite lesions in cervigram images, addressing the shortage of skilled colposcopists and streamlining the training process. A computational approach is employed to develop and train a deep learning model specifically tailored for cervix region and acetowhite lesion segmentation in cervigram images. A dataset acquired in collaboration with KIDWAI memorial cancer research institute is used for building the model. Cervigram images are collected for training and validation, and a deep learning architecture is constructed and trained using annotated datasets. The segmentation network  based on efficientnet architecture and atrous spatial pyramid pooling is designed to accurately identify and delineate the target regions, with performance evaluation conducted using precision, accuracy, recall, dice score, and specificity metrics. The proposed segmentation network achieves a precision of 0.7387±0.1541, accuracy of 0.9291, recall of 0.7912±0.1439, dice score of 0.7431±0.1506, and specificity of 0.9589±0.0131, indicating its reliability and robustness in segmenting cervix regions and acetowhite lesions in cervigram images. This research demonstrates the feasibility and effectiveness of using artificial intelligence-based computational models for cervix region and acetowhite lesion segmentation in cervigram images. It provides a foundation for further investigations into classifying cervix malignancy using AI techniques, potentially enhancing early detection and treatment of cervical cancer while addressing the shortage of skilled professionals in the field 
Optimizing Energy Output for Oscillating Water Column (OWC) Wave Energy Converter System at Pantai Baron, Gunung Kidul, DI Yogyakarta Kurniawan, Aries Taufiq; Budiman, Arief; Budiarto, Rachmawan; Prasetyo, Ridwan Budi
Applied Engineering and Technology Vol 3, No 2 (2024): August 2024
Publisher : ASCEE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/aet.v3i2.1773

Abstract

The prototypes of the Oscillating Water Column (OWC) system constructed by BPPT at Pantai Baron, Gunung Kidul, in 2005  and 2006 were not sustainable. Based on its condition and location, the root cause of the problem was defined. Maximizing the total efficiency and capacity factor (Cf) of the OWC system was the main factor for optimizing energy output. Collecting  factors that constructed the total efficiency and capacity factor of the OWC system was conducted. Selecting the appropriate  turbine, generator, and chamber system led to an increase in the total efficiency of the OWC system. Reducing the effect of  wave diffraction, finding optimum wave data for forecasting, finding optimum water depth area to avoid wave breaking area,  reducing corrosion chance by selecting the optimum height of the OWC system, and using a control system to minimize stalling  on turbine were factors that constructed capacity factor
A compact patch antenna for wireless sensor network applications in WLAN Ahmed, Md. Firoz; Bashir, Samiul; Paul, Pronab Kumar; Islam, Md. Bipul; Uddin, A.N.M. Shihab; Kabir, M. Hasnat
Applied Engineering and Technology Vol 3, No 3 (2024): December 2024
Publisher : ASCEE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/aet.v3i3.1702

Abstract

In wireless sensor networks (WSNs), antennas play a crucial role in enlarging network capacity, prolonging transmission distances, fostering spatial reuse, and minimizing interference. This paper delineates a miniature rectangular patch antenna featuring partial grounding, meticulously engineered for the WLAN (wireless local area network) to promote real-time operations within WSNs. The main goal is to augment the creation and execution of a patch antenna that aligns with the typical size and power constraints of WSN nodes. The antenna is engineered and simulated for a 2.4 GHz WLAN frequency band (2.4 – 2.48 GHz) by leveraging CST Microwave Studio 2024. It is fabricated on a 45 mm × 50 mm FR4 substrate (εr = 4.3, thickness = 1.4 mm, loss tangent = 0.025). The antenna is energized via a 50 Ω microstrip inset-feed line. This antenna demonstrates a substantial bandwidth of 159.729 MHz (2.31963 GHz to 2.479359 GHz), an impressive return loss of – 48.15956 dB, a VSWR (voltage standing wave ratio) of 1.007848, a directivity of 4.7 dBi, a gain of 3.04 dBi, and an efficiency of 68.21%. These performance indicators illustrate the antenna’s effectiveness in enabling short-range communication within WSNs. With its compact design, broad bandwidth, and strong performance metrics, this antenna is an efficient and cost-effective solution suitable for various applications in WSNs, including industrial automation, environmental monitoring, healthcare, and smart city initiatives, ensuring reliable and high-quality wireless communication.
Sustainable urban development: a case study on green infrastructure implementation in Kota City India Lal, Shiv; Choudhary, Saaransh; Kakodia, Ashok Kumar
Applied Engineering and Technology Vol 3, No 3 (2024): December 2024
Publisher : ASCEE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/aet.v3i3.1741

Abstract

Kota City is known as an educational city with increasing urbanization, requiring a sustainable development approach to address environmental and social challenges. One of the solutions implemented is green infrastructure, which integrates natural elements to improve ecological quality, reduce environmental pressure, and improve people's welfare. This study aims to evaluate the effectiveness of green infrastructure in supporting sustainable development in Kota City. The approaches studied include rainwater management, renewable energy (solar, wind, nuclear, hydro), sustainable transportation, and red light-free zone policies to reduce energy consumption and pollution. The study results show that implementing green infrastructure significantly lowers urban temperatures, improves flood management, improves air quality, and improves energy efficiency. These approaches can help for sustainable urban development. This research provides benefits in the form of a greener, more efficient, and sustainable urban development model. With this approach, Kota city can be an example for other cities in creating a healthier, environmentally friendly environment and improving the economic and social welfare of the community.
Analysis of horizontal milling machine vibration on the influence of gear module cutters with sizes M1 and M1.5 Zaira, Jupri Yanda; Haiqal, Muhammad; Sitinjak, Bherry Arif; Prasetyo, Yoga Ali; Hasibuan, Muhammad Refky; Alhabib, Fauzan; Sinaga, Indra; Hardyanto, Rio
Applied Engineering and Technology Vol 3, No 3 (2024): December 2024
Publisher : ASCEE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/aet.v3i3.1762

Abstract

This study examines the effect of vibrations on the horizontal milling machine type 1216 during gear manufacturing using cutter modules with diameters of 50 mm and 55.25 mm, each at a cutting depth of 1 mm. Displacement, velocity, and acceleration measurements were conducted in vertical, horizontal, and axial directions using a VM-6370 vibration meter, with the average vibration amplitudes analyzed. The results revealed that the 55.25 mm cutter produced the highest vibration amplitude in the horizontal direction, reaching 353.270 mm/s², while the lowest was in the vertical direction at 171.293 mm/s². For the 50 mm cutter, the highest amplitude occurred in the vertical direction at 0.1336 mm and the lowest in the horizontal direction at 0.0583 mm. These findings demonstrate that larger cutter modules generate higher vibration amplitudes, significantly affecting the precision and surface quality of gear manufacturing. The study emphasizes the importance of selecting appropriate cutter sizes to minimize vibrations, optimize manufacturing processes, and improve product quality. By providing a detailed analysis of the relationship between cutter size and vibration levels, this research is a valuable reference for enhancing the efficiency and accuracy of gear cutting in industrial applications.

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