Journal of Engineering and Scientific Research

Design of a Co-Working Space Building with a Biomimicry Architecture Concept in Bandar Lampung

K. Alifah, P. Kurniawan, N. Ifadianto — Mon, 01 Jun 2026 00:00:00 +0000

The economic development in Bandar Lampung is becoming increasingly competitive, leading to higher demand and marketing of office spaces as business actors will need new spaces. Therefore, co-working spaces become a beneficial solution in overcoming these challenges, serving as workspaces and venues for collaboration. However, working continuously indoors can cause feelings of boredom and stress. Several workplace studies show that contact with nature experienced at work or in the office can improve health. One approach is to bring the concept of nature into the building through Biomimicry Architecture by adopting the principles of nature's mechanisms. By adopting these principles, Biomimicry Architecture can also help minimize stress levels for workers in the co-working space; thereby, creating a more comfortable working environment and reducing stress. Based on the analysis and design concepts for the co-working space with the biomimicry architecture concept, biomimicry can address issues related to air pollution by adapting nature's mechanisms. The biomimicry concept in the co-working space applies three principles mass composition, interior layout, exterior layout, skin facade, and utility systems in the building.

Generation Expansion Planning: A Bibliometric Review

W. Sunanda — Mon, 01 Jun 2026 00:00:00 +0000

Generation expansion planning is a prominent topic of energy-related scientific discourse. Due to operational constraints, the penetration of renewable energy sources, and uncertainty, there have been numerous changes in the planning of generation expansion. This article provides a bibliometric analysis of recent research on generational expansion planning. Relevant authors, sources, terms, disciplines, and conceptual analysis are used for bibliometric analysis. This bibliometric is based on a Scopus database data set for the years 2013 to 2023.

The Volumetric Performance Analysis and Rutting of PG76 Asphalt Mixture with Fly ash as Filler

H. F. Tambunan, B. C. Marina, B. H. Sipayung — Mon, 01 Jun 2026 00:00:00 +0000

Hot asphalt mixture is a type of pavement that is often used in a variety of traffic conditions and diverse environments. Permanent deformation in hot asphalt mixtures is damage caused by ambient temperature, aggregate quality and binding materials. This study shows the effect of using different types of binding materials, asphalt pen 60/70 and asphalt Pg76 with fly ash additives by analyzing the volumetric characteristics and rutting performance of asphalt mixtures. The results showed that the Pg76 mixture had a lower KAO value (6.5%) compared to the 60/70 pen mixture (6.6%). Based on volumetric analysis, the addition of fly ash as a filler has different effects depending on the type of asphalt used, which can be seen from the correlation values of VIM, VMA and VFB >0.7. The stability of the marshall in the PG76 FA mixture has a value of 1686.04 kg and the Pen 60/70 FA of 1407.58 kg. The addition of FA to hot asphalt mixtures can reduce moisture damage with an IRS value of more than 90%. The rutting performance of the PG76 FA mixture has better performance as evidenced by its higher dynamic stability values and lower deformation rate than the Pen 60/70 FA mixture. Temperature has a significant influence on the rutting performance of both mixtures especially in the Pen 60/70 FA mixture. The higher the test temperature indicates the greater the total deformation value, higher deformation rate, and lower dynamic stability in both mixtures.

Impact of Copper (Cu) and Lead (Pb) Conductive Materials on the Radiation Performance of Printed Circuit Dipole Antennas

Mon, 01 Jun 2026 00:00:00 +0000

The Fermentation-Destillation Optimization of Palm Juice for High-Content Bioethanol: Literature Review

Hasanuddin — Mon, 01 Jun 2026 00:00:00 +0000

The Identification of the Way Ratai Geothermal System and Menanga Fault Through Derivative Analysis and 3D Modeling of Gravity Data

Ilham Dani, Virna Amelia, Rifanny Dwi Anwar, Nayla Julita Putri — Tue, 16 Jun 2026 00:00:00 +0000

The gravity method is one of the most commonly used geophysical exploration methods for deep ground structure, especially in the geothermal prospect area. In this study the Way RataiGeothermal System and Menanga Faulthave been successfully identified in PesawaranRegency, Lampung Province using full Bouguer anomaly informations. The interpretation process was also performed through the First Horizontal Derivative (FHD), besides the Second Vertical Derivative (SVD) to emphasize anomalies whilst mapping density contrast limits related with fault and fracture-zones. The subsequent step was to predict the rock density distribution and to assist in interpreting the subsurface geology, 3D modelling was conducted. Results of interpretations show a low density area related to the Way Ratai geothermal system and linear anomaly patterns, which are believed to correspond the Menanga Fault. These results indicate that there are permeable bodies which act as pathways for the hydrothermal fluids to migrate. The tectonic control has been proved to be the significant preparation mechanism for geothermal system. In general, it has proved that the derivative or 3D modeling of the gravity method would be viable in geothermal survey.

Jr Thermal Comfort Analysis of Design Element in El’s Coffee Roastery Building Bandar Lampung: A Case Study of the Use of Glass Facades in a Tropical Climate

A. F. abdullah, D. Lisa — Tue, 16 Jun 2026 00:00:00 +0000

Indonesia's tropical climate, characterized by high humidity, hot temperatures,
and intense solar radiation year-round, demands a more adaptive and thoughtful
architectural design approach. In this context, building designers need to
consider the balance between aesthetics and thermal comfort for space users. The
use of glass, for example, can provide abundant natural lighting and enhance a
building's visual character, but it can also increase the heat load of interior
spaces if not equipped with appropriate mitigation strategies. Therefore,
implementing effective air circulation, such as air conditioning devices, shading
devices, and reflective protective coatings, is crucial to reducing excess heat.
Facade design that is responsive to tropical climates is key to achieving optimal
building performance. This study examines the thermal comfort analysis and
application of architectural design elements to the El's Coffee Roastery building
in Bandar Lampung, with a particular focus on the function and quality of the
glass facade as a key element influencing the building's appearance and
performance in a tropical climate.

Identification of Hydrocarbon Prospect Zones in The AI-1 Well, The Central Sumatra Basin

R. C. Wibowo, A Irawan, O. Dewanto — Tue, 16 Jun 2026 00:00:00 +0000

The Central Sumatra Basin is one of the largest hydrocarbon producing back arc basins in Indonesia. Determining the hydrocarbon prospect zone in this basin uses the well logging method and petrophysical analysis which is carried out to determine rock physical parameters such as shale volume, porosity, water saturation, net reservoir and net pay in the Menggala Formation and Pematang Formation as well as to validate the hydrocarbon content so that a value can be obtained. net (net pay) which is able to describe the thickness of the reservoir. In this research, 4 hydrocarbon prospect zones were found in the Menggala Formation at a depth of 5962.32-6125.03 feet and in the Pematang Formation there were 5 hydrocarbon prospect zones at a depth of 6142.39-6444.12 feet. In the Menggala Formation, the physical parameters of the reservoir rock were obtained, namely shale volume values of 15.1%-24.7%, porosity of 15.84%-18.07%, and water saturation of 29.15%-35.18. Meanwhile, in the Pematang Formation, the physical parameters of the reservoir rock were obtained, namely shale volume values of 4.13%-21.72%, porosity of 16.93%-19.04%, and water saturation of 28.83%-34.04%. These two formations have good quality porosity and the fluid type is gas. Based on the final results of the petrophysical analysis, it can be seen that the prospect zone in the Menggala Formation and Pematang Sumur AI-1 Formation of the Central Sumatra Basin as a whole is a hydrocarbon zone. This is because most prospect zones have a net gross value close to 1.

Spatial Analysis of Landslide Vulnerability Using Weighted Overlay Based on GIS in Balik Bukit

Stefano Wahyudi, Azizah Dea Putri, Liana Sinaga, Aprido Lumbanraja — Mon, 01 Jun 2026 00:00:00 +0000

Balik Bukit District in West Lampung Regency is an area with high susceptibility to landslides, which are difficult to predict and pose significant threats to human safety. This study aims to comprehensively map landslide vulnerability zones as a foundation for mitigation strategies. The method used is the Weighted Overlay approach based on Geographic Information Systems (GIS), analyzing eight triggering parameters: slope steepness, slope aspect, slope length, lithology, distance from faults, soil type, soil depth, and rainfall. The research produced a risk map classifying the study area into three categories: low risk (4,878.442 ha), moderate risk (8,487.104 ha), and high risk (1,230.959 ha). Slope steepness was identified as the most dominant factor. This map is expected to serve as a strategic guide for the government and local communities in developing adaptive spatial planning and more effective disaster mitigation plans.

Three-Phase Load Balancing Optimization using Mixed Integer-Linear Programming Model: A Case Study at Electrical Engineering Building, University of Lampung

Mon, 01 Jun 2026 00:00:00 +0000

Load imbalance in a three-phase low voltage distribution system is a significant operational challenge and can result in voltage drops and reduced efficiency. Based on the daily three-phase load profile of the electrical engineering academic building at the University of Lampung, particularly during operating hours, the R-phase overloaded (+13.64% deviation). Meanwhile, the S-phase underloaded (-1.70% deviation), and the T-phase underloaded (-11.94% deviation). This study implements an optimization model to balance loads by relocating load units between phases. This model was developed using Mixed-Integer Linear Programming (MILP) framework to produce practical and implementable recommendations. An innovative approach to dynamic load identification is introduced, where the model intelligently determines which loads are active at each time interval based on aggregate power data from the power meter data acquisition system. The optimal solution involved relocating six air conditioning units from the overloaded Phase R (three to Phase S and three to Phase T). This implementation successfully achieved a near-perfectly balanced system, validated by an 11.83% reduction in the aggregate load imbalance metric.

Scalable Automated Proctoring: Integrating Browser-Native Artificial Intelligence and Continuous Trust Evaluation

somnath, Prathamesh Bomble, omkar, vrushabh — Mon, 01 Jun 2026 00:00:00 +0000

Abstract—The ability of most insitutions to make an agreement
swiftly to remote education highlighted numerous integrity issues,
thus established the need for an application-wise authentic
proctoring strategy. Nonetheless, present automated solution for
proctoring is either based upon sophisticated deep convolutional
network (such a deep YOLO network) time-consuming requires
great deal of computer power or constantly intrusive online
desktop application to integrate the knowledge from students not
being located together with test location. Many of these approach
disqualify the students utilizing common computer parts they
were in all probability to use to even go on the web with, com
promise the citizens of those pupils, two the ability to meddle with
evidence acquired on a far more powerful proctoring solution.
We propose a stream-lined, wholly virtual multi-modal AI based
Proctoring system integrated to a Django platform (PostgreSQL
server for data storage) to get over those limitations. In this
project, we demonstrated a system of make sure the proctoring
software unwilling run while offline onto a pupil computer. This
project we used the enormous computer-processing and memory
learning pipeline is similar to repacement by existing proctoring
systems with a lean angular multiplier modality spatially-tracer
system using Face–based facial recognitions of pupil to do Gaze
Traccing (em the result straight away) for objects detection
during image minutely track for obiquitous objects on pupil
view(s). Fourth, using all of those background sound analysis
plus ongoing browser app up to a modern ”Trust Value”. The
trust value will evaluate the behavior of student through out the
whole duration exam. This propose to features a way to design
a proctoring system that utilizes minimal amount of bandwidth
and computational resource, can be expanded to accomodate
many students taking a test simulteneously and comport to
accommodate with the student wellbeing- rather than likely make
any of these metrics deteriorate.
Index Terms—Remote Proctoring, Uncertainty Estimation,
Multi-Modal Fusion, YOLOv11, LSTM, Edge Computing.

CareMatrix: An Integrated Smart Healthcare System

Jaydeep Kumbhar, Omkar Burungale, Praveen Barapatre, Satish Khalse — Mon, 01 Jun 2026 00:00:00 +0000

The increasing demand for real-time, patient-centric
healthcare has accelerated the integration of Internet of Things
(IoT) technologies with intelligent analytics. Traditional health
care models rely on episodic patient visits and are inadequate for
continuous monitoring and early detection of critical conditions.
This paper presents CareMatrix, an integrated smart healthcare
system combining IoT-based Remote Patient Monitoring (RPM)
with machine learning for real-time anomaly detection.
The system utilizes an ESP32 microcontroller integrated with
a MAX30102 sensor to acquire physiological parameters such
as heart rate and oxygen saturation (SpO2). The data are
preprocessed at the edge and transmitted via WiFi to the
ThingSpeak cloud using REST APIs for real-time storage and
visualization.
A Random Forest classifier trained on 10,000 patient records
achieves an accuracy of 92.4%, precision of 91.2%, recall of
90.8%, and F1-score of 91.0%. The system generates alerts within
2–3 seconds upon detecting abnormal conditions, enabling timely
intervention.
The proposed framework provides a scalable and efficient
solution for continuous healthcare monitoring and supports
proactive, data-driven decision-making.