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Electronic Journal of Education, Social Economics and Technology
Published by SAINTIS Publishing
ISSN : -     EISSN : 27236250     DOI : https://doi.org/10.33122/ejeset
Core Subject : Religion, Economy, Humanities, Health, Science, Education, Art, Social, Engineering,
Religion Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Nursing Public Health Social Sciences Veterinary Other
Electronic Journal of Education, Social Economics and Technology (eJESET) with ISSN 2723-6250 (online) is a open-access, peer-reviewed multidisciplinary international journal. The journal aims to provide an international platform for researchers, professionals and scientists for solve of problems with multidisciplinary approaches on all topics related to educational, social science, economics and technology to exchange, sharing and disseminate theoretical of current research results as widely as possible. Electronic Journal of Education, Social Economics and Technology (eJESET) publishes the latest research results in multidisciplinary approaches on all topics related to educational, social science, economics and technology. First published in 2020. The Journal is published biannually and is available in open access electronic version.
Arjuna Subject : Ilmu Sosial - Ilmu Sosial (Lain-Lain)
Articles 169 Documents
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Search results for , issue "Vol 6, No 2 (2025)" : 169 Documents clear
Dermascan: Convolutional Neural Network-Based Skin Cancer Early Detection System Agustin, Arellia; Nurhaida, Ida
Electronic Journal of Education, Social Economics and Technology Vol 6, No 2 (2025)
Publisher : SAINTIS Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33122/ejeset.v6i2.1243

Abstract

Skin cancer continues to show a significant global increase in incidence, and early detection remains essential to reducing mortality rates. Conventional diagnostic techniques such as biopsy are invasive, require considerable processing time, and are not always accessible, particularly in remote or resource-limited healthcare environments, indicating the need for an intelligent and efficient diagnostic support system. This study develops a lightweight Convolutional Neural Network (CNN) model designed to classify seven types of skin lesions using the HAM10000 dataset consisting of 10,015 dermatoscopic images. The preprocessing pipeline involved resizing, normalization, oversampling, and dataset splitting. The training process was conducted for a maximum of 40 epochs and concluded automatically at epoch 29 using early stopping to prevent overfitting. The experimental results demonstrated that the proposed model achieved an accuracy of 98%, and surpassed common pretrained architectures including ResNet50V2 (83%) and VGG19 (67%), with precision, recall, and F1-score metrics showing consistent performance across all lesion classes. The final trained model was integrated into the Dermascan web platform, enabling real-time automated lesion classification from user-uploaded images. These findings confirm that the lightweight CNN model offers a reliable, fast, and accessible tool for early skin cancer detection that can be beneficial for both clinical decision-support and wider public healthcare applications.
Comparative Performance Evaluation of ARIMA, SARIMA, and LSTM for Daily Shallot Price Forecasting in Palembang City Miranda, Fatreisya Ayu; Tania, Ken Ditha; Kurnia, Rizka Dhini
Electronic Journal of Education, Social Economics and Technology Vol 6, No 2 (2025)
Publisher : SAINTIS Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33122/ejeset.v%vi%i.1323

Abstract

Shallots are a food commodity that often experiences price fluctuations and is one of the contributors to inflation in the city of Palembang. This study compares the ARIMA, SARIMA, and LSTM methods in predicting shallot prices using daily data start from January 2020 to October 2025. The Data of shallot price were obtained through the official website of Bank Indonesia. The stages of the study included data collection, pre-processing, visualization and decomposition, split data, modeling, and performance evaluation using the RMSE, MAE, and MAPE metrics. Model performance assessment reveals that ARIMA(1,1,1) method provided the most optimal performance with the lowest error value in comparison with the remaining two other methods, namely SARIMA and LSTM. The SARIMA(1,1,1)(2,1,1)7 model produced a slightly higher error rate, although its performance remains superior than LSTM model. The LSTM method produced the highest error in this study. These findings indicate that the pattern of shallot price data in Palembang tends to follow linear and seasonal trends that are not too complex, so that classical statistical approaches are still superior to deep learning models in capturing these data patterns. This research provides practical contributions as a decision-making support tool for the government and business actors in planning the distribution and stabilization of shallot prices in Palembang City.
Colonial Narratives and “Narrative Colonization”: Analysis of Junior High School Social Studies Textbooks (2004-2023) Daud, Mohamad Rezki; Wardana, Amika; Budiman, Budiman
Electronic Journal of Education, Social Economics and Technology Vol 6, No 2 (2025)
Publisher : SAINTIS Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33122/ejeset.v6i2.1131

Abstract

The theme of colonization is a crucial subject in the teaching of Social Studies at the junior high school level. The process represents a dynamic phase, as colonial domination occurred differently across regions of Indonesia. These variations affect the historical narratives presented in textbooks. This study aims to analyze the narratives of colonization in Social Studies textbooks and their regional representations. The method employed is qualitative content analysis. Data validity and reliability were ensured through four criteria: credibility, transferability, dependability, and confirmability. Data analysis followed the stages of formulating research questions, defining categories, coding data, rechecking, and interpreting the findings. The study examined 27 textbooks, consisting of 7 (seven) from the Competency-Based Curriculum, 10 (ten) from the School-Based Curriculum, 5 (five) from the 2013 Curriculum, and 5 (five) from the Merdeka Curriculum. The findings reveal that, regionally, the complexity of colonial history demonstrates the dominance of certain areas in the narratives of Social Studies textbooks. Java and Sumatra dominate the accounts. The narratives of these regions are more diverse because of their roles as centers of resistance and colonial policy. Conversely, other regions, particularly Papua, are minimally represented despite having their own colonial experiences. This imbalance indicates uneven regional representation of colonial history in the textbooks. Moreover, the analysis shows that colonial narratives often reflect ambiguities in interpreting Indonesian history, especially concerning division, manipulation, and the dual impacts experienced during and after colonization.
Identification of Style and Characteristics of Colonial Buildings of URC City Post in Lhokseumawe City Sari, Febri Tika; Dafrina, Armelia; Andriani, Dela; Fidyati, Fidyati; Muthmainah, Muthmainah; Saptari, Mochamad Ari; Sofyan, Diana Khairani
Electronic Journal of Education, Social Economics and Technology Vol 6, No 2 (2025)
Publisher : SAINTIS Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33122/ejeset.v6i2.1333

Abstract

The URC City Police Post building in Lhokseumawe City is a legacy of Dutch Colonial Architecture, showcasing a blend of European style (Dutch Land) and local Indonesian elements, known as the Indische Empire Style. This building has a distinctive visual character and is monumental. Some of the main characteristics of colonial architecture found in this building include the presence of sturdy materials such as specially blended cement, terrazzo for floors, Geveltoppen, acroterie roofs, a geometric symmetrical facade, the use of wooden-framed windows, and dormer elements. Classical European decoration (pillars, capitula) is combined with local decorative variations, such as on the cripedoma (entrance decoration) or tympanon. This study aims to identify and analyze the style and characteristics of colonial architecture found in the URC City Police Post building, located in Banda Sakti District, Lhokseumawe City. The research method used is descriptive with a qualitative approach through field surveys, photographic documentation of the object, and direct observation of building elements.
Analysis of Sustainability Report Disclosure Quality from Economic, Environmental, and Social Perspectives at PT Petrokimia Gresik Hadawia, Siti; Kholmi, Masiyah; Rumijati, Aniek
Electronic Journal of Education, Social Economics and Technology Vol 6, No 2 (2025)
Publisher : SAINTIS Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33122/ejeset.v6i2.1233

Abstract

Sustainability reporting is essential for corporate transparency and accountability, yet the quality of such disclosures in Indonesia remains limited. PT Petrokimia Gresik, as a major chemical producer, faces scrutiny regarding its environmental and social impacts, which are not fully reflected in its sustainability reporting. This study examines the quality of the company’s 2023 Sustainability Report based on the economic (GRI 200), environmental (GRI 300), and social (GRI 400) dimensions, referring to the GRI Standards 2021 and the triple bottom line framework. A descriptive qualitative method was employed through interviews with CSR personnel and content analysis of the report. Disclosure quality was assessed using a 0–15 index aligned with compliance criteria. The findings indicate that the report falls into the “Partially Applied” category with an overall score of 58%. The environmental dimension achieved the highest score (71%), followed by economic (60%) and social (48%). The low performance in social reporting stems from limited quantitative data, human resource constraints, and missing disclosures such as human rights assessments (GRI 412). Although the company supports the SDGs, improving reporting quality particularly completeness and data quantification is necessary to strengthen transparency and stakeholder trust.
Escalation of Visual Accentuation of the Connecting Corridor of the Grand Mosque Bakrie Area for Strengthening the Identity of Kisaran City Yasmin, Shirin Alya; Mirsa, Rinaldi; Rahman, Muhammad Abdul
Electronic Journal of Education, Social Economics and Technology Vol 6, No 2 (2025)
Publisher : SAINTIS Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33122/ejeset.v6i2.1296

Abstract

The Bakrie Mosque is a religious tourism area with strategic potential in shaping the identity of the city. This study discusses the concepts of accentuation and escalation in the development of the mosque area as an effort to strengthen its appeal, social function, and city image. Accentuation is understood as the affirmation of the visual, architectural, and narrative character of the area, while escalation refers to the increase in capacity, facilities, and diversification of tourism activities. The study aims to identify visual characteristics and formulate design guidelines that align the public corridor with the mosque's grandeur. Using a qualitative descriptive approach with a case study strategy, data were collected through structured observation and visual recording of street elements within a 500-meter radius. The results indicate that applying these concepts contributes significantly to creating a sustainable tourism ecosystem and positioning the Bakrie Mosque as a representative city icon. The analysis reveals a visual disparity between the landmark and micro-street elements, necessitating a "Visual Harmonization" strategy. This article provides a conceptual perspective that can be utilized in development strategies for other religious tourism areas.
Cash Flow Prediction System of PT Gudang Garam Using ERP-Integrated LSTM Novandi, Muhammad Ananta Arya; Nurhaida, Ida; Sofia, Irma Paramita; Nurhidayah, Fitriyah
Electronic Journal of Education, Social Economics and Technology Vol 6, No 2 (2025)
Publisher : SAINTIS Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33122/ejeset.v6i2.1235

Abstract

Enterprise Resource Planning (ERP) applications such as Odoo generally do not have predictive analytics capabilities for time series data and are limited to recording historical financial data. The limitations of ERP systems make companies dependent on traditional statistical models such as ARIMA, which often fail to capture complex non-linear patterns in financial data. However, the ability to accurately predict cash flow is crucial for strategic financial management in companies. This study aims to develop and evaluate a predictive model using a Long Short-Term Memory (LSTM) approach that is accurate and integrated into Odoo ERP. The research method includes designing a microservices architecture with FastAPI as a bridge between Odoo ERP, the predictive model, and prediction graph visualization. The LSTM model is evaluated by comparing it with the ARIMA model using 3,740 Daily cash flow data, with evaluation metrics MAE, MAPE, R2. System testing will use Black Box Testing and White Box Testing. The research results show that LSTM significantly outperforms the ARIMA model with an R2 evaluation of 0.8801 and an accuracy of 96.62%. The system testing results also yielded positive outcomes as the integration architecture runs stably and functionally. This research contributes by providing an Odoo ERP system that has predictive analysis capabilities with interactive graphical visualizations through Grafana, which helps companies make decisions effectively.
Factors Affecting Accounting Students in Using Qris as an Electronic Payment Method Thohiri, Roza; Siregar, Indra; Muda, Iskandar
Electronic Journal of Education, Social Economics and Technology Vol 6, No 2 (2025)
Publisher : SAINTIS Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33122/ejeset.v6i2.1266

Abstract

This study aims to examine how the ease, speed, security, and accounting literacy in the use of QRIS affect accounting students' interest in it as their electronic payment method. The study uses a quantitative approach by distributing a Likert scale questionnaire to accounting students at Medan State University who were selected through purposive sampling. The analysis was conducted through validity, reliability, heteroscedasticity, multicollinearity, autocorrelation, t-test, F-test, and multiple linear regression tests. The results revealed that convenience, speed, and security had a positive and significant effect on interest in using QRIS. On the other hand, accounting literacy did not show a significant effect even though the coefficient was positive. Simultaneously, all independent variables were proven to have an effect on interest in using QRIS and were highly significant. The study concludes that student interest is more determined by the aspects of convenience, speed, and security of transactions, while accounting literacy is not a determining factor in the use of QRIS.
Experimental Study on the Effect of Rice Husk Charcoal as an Adsorbent in Bioethanol Purification through Distillation Suryadi, Suryadi; Sayuthi, Muhammad; Putra, M. Iqbal Adhya; Yusuf, Edy; Habibi, Muhammad
Electronic Journal of Education, Social Economics and Technology Vol 6, No 2 (2025)
Publisher : SAINTIS Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33122/ejeset.v6i2.1358

Abstract

This study investigates the effect of using rice husk charcoal as an adsorbent in adsorption-assisted distillation for bioethanol purification. The research is motivated by the need for more efficient, low-cost, and sustainable bioethanol purification methods, considering the limitations of conventional distillation due to azeotrope formation and high energy consumption. An experimental laboratory method was employed by varying the mass of rice husk charcoal at 3 g, 5 g, and 7 g under a constant operating temperature of 78 °C and an initial ethanol concentration of 70%. Performance parameters analyzed included ethanol concentration improvement, separation efficiency, bioethanol yield, and condenser performance. The results indicate that increasing adsorbent mass significantly enhances ethanol purity, with the highest concentration of 89.4% and maximum separation efficiency achieved at 7 g of adsorbent. However, the highest bioethanol yield was obtained at 3 g of adsorbent, indicating a trade-off between product purity and quantity. Overall, rice husk charcoal is proven to be an effective, environmentally friendly alternative adsorbent with strong potential for application in small- to medium-scale bioethanol purification systems.

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