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INDONESIA
Jurnal Sistem Cerdas
Published by Asosiasi Prakarsa Indonesia Cerdas
ISSN : -     EISSN : 26228254     DOI : -
Core Subject : Science, Education, Engineering,
Automotive Engineering Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering
Jurnal Sistem Cerdas dengan eISSN : 2622-8254 adalah media publikasi hasil penelitian yang mendukung penelitian dan pengembangan kota, desa, sektor dan kesistemam lainnya. Jurnal ini diterbitkan oleh Asosiasi Prakarsa Indonesia Cerdas (APIC) dan terbit setiap empat bulan sekali.
Arjuna Subject : Umum - Umum
Articles 13 Documents
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Search results for , issue "Vol. 8 No. 1 (2025)" : 13 Documents clear
Implementation of 360° Virtual Reality using Sky View as Information Media for Infrastructure Infrastructure in Education Sector Latifah, Ayu; Rizal Nurul Hadi, Muhamad
Jurnal Sistem Cerdas Vol. 8 No. 1 (2025)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v8i1.451

Abstract

The rapid advancement of information technology has had a significant impact on various sectors, including education. One educational institution in Garut, Yayasan Al Musaddadiyah, faces challenges in effectively conveying information to prospective students. Traditional media such as brochures and pamphlets often fail to provide a comprehensive depiction and better visualization of the facilities and educational environment at the institution. As a solution, this research developed a Virtual Reality (VR) 360° media with a Sky View perspective to visualize the existing facilities and infrastructure at Yayasan Al Musaddadiyah. The study utilized the Multimedia Development Life Cycle (MDLC) method in the VR application development process. MDLC was chosen because it provides a systematic approach at each development stage, from concept to implementation and evaluation. In this research, various multimedia elements such as images, videos, and audio were integrated into the VR application to create an immersive and interactive experience for users. By leveraging VR 360° Sky View technology, prospective students and parents can directly view the educational environment and available facilities at the institution without physically visiting the location. Evaluation results showed that the use of VR-based information media successfully increased the interest and understanding of prospective students towards Yayasan Al Musaddadiyah. Additionally, this application proved effective in expanding the reach of information about the institution, particularly in the increasingly connected digital era. Thus, the development of VR-based information media not only provides a practical solution to the institution’s communication challenges but also opens up new opportunities as a promotional or marketing strategy for educational institutions in the future.
Development of an Intelligent System for Early Diagnosis of Diseases in Toddlers Using Forward Chaining and Dempster-shafer Integration Pratama, Yusuf Hendra; Firmansyah, Firmansyah; Arfin, Ahmad
Jurnal Sistem Cerdas Vol. 8 No. 1 (2025)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v8i1.469

Abstract

Toddlerhood is an important period in a child's growth and development. In this period children will be vulnerable to disease. There are several types of diseases that range in toddlers such as diarrhea, pneumonia, malaria, etc. The problems faced are the limited access and quality of health services in some areas where health costs are still relatively high, the availability of health workers is also not always available, and the lack of knowledge related to toddler health. So, a system is needed that can provide knowledge and first aid information related to the health of toddlers which is expected to help in reducing the mortality rate of toddlers, especially for the types of diseases that can cause death such as diarrhea, pneumonia and malaria. The methods used in this research are Forward Chaining and Dempster-shafer. The result of this research is an intelligent system that applies forward chaining and dempster-shafer methods to diagnose early diseases in toddlers. The test results carried out in this research show an accuracy value of 90% of 10 tests. The results of Blackbox and usability testing conducted also show that the developed system is as expected and feasible to use
Analysis of Customer Feedback for an e-Commerce Application Based on Artificial Neural Networks Sri Anita; Army, Widya Lelisa; Nugroho, Arif
Jurnal Sistem Cerdas Vol. 8 No. 1 (2025)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v8i1.473

Abstract

With the rise of the Internet, e-commerce platforms have become one of the primary shopping channels for consumers. Establishing an efficient and intelligent customer service system is a crucial challenge for these platforms. This research aims to analyze how the interactivity of e-commerce applications and customer feedback from online shopping experiences can influence consumer loyalty and the likelihood of repurchase. To evaluate customer loyalty, we utilize an artificial neural network, which is processed using the SPSS application. The findings indicate that the relationship between interactivity, consumer feedback, and loyalty has a confidence level of 85.4%. A relationship between variables is considered strong if the R-squared value is above 50%, while a value below 50% indicates a weaker relationship.
Alphabet Learning Media Using Image Classification for Speech-Impaired Students in Special Education Schools Novita, Rice; Rahmawita M, Medyantiwi; Safiq Tama, Naufal
Jurnal Sistem Cerdas Vol. 8 No. 1 (2025)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v8i1.478

Abstract

This research aims to develop an image classification-based learning medium for teaching the alphabet to students with speech impairments in special schools (SLB). The technique used in image classification is Random Forest with a dataset of 5,400 images, including 1 default image and 26 alphabet classes. The software development follows the waterfall model, including requirements analysis, system design, implementation, and testing, with system design utilizing object-oriented analysis and design (OOAD). Evaluation metrics, including accuracy (100.00%), precision (1.00), recall (1.00), and F1 score (1.00), indicate the model’s outstanding performance. The system was tested on 10 students with speech impairments, showing an average improvement in ability from 5.9 in the pretest to 12.8 in the posttest, demonstrating consistent gains among participants. This image classification-based learning medium is expected to support the learning process for students with speech impairments in SLB effectively
User Experience Analysis of MyPertamina Application Using User Experience Questionnaire (UEQ) and System Usability Scale (SUS) Sakdiah, Gewik; Ahsyar, Tengku Khairil; Megawati, Megawati; Angraini, Angraini
Jurnal Sistem Cerdas Vol. 8 No. 1 (2025)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v8i1.486

Abstract

MyPertamina is a digital wallet application developed by PT Pertamina (Persero) to facilitate cashless fuel payments and offer loyalty programs. Despite exceeding 10 million downloads, the application received a 3.3 rating on Google Play Store as of May 2023, indicating user complaints. This study analyzes the user experience of the MyPertamina application using the User Experience Questionnaire (UEQ) and System Usability Scale (SUS). Respondents were active users selected purposively through online questionnaires. The study results show all UEQ dimensions scored within the neutral range, with the highest score on Perspicuity (mean 0.453) and the lowest on Novelty (mean -0.068). SUS measurements place the application in the Marginal Low category under acceptability ranges and grade D in the grade scale, indicating significant room for improvement. However, the application received a ”Good” rating in the adjective rating category, reflecting its utility despite suboptimal performance. In conclusion, the MyPertamina application requires enhancements to meet user expectations and improve overall user experience
Thermal Image-Based Multi-Class Semantic Segmentation for Autonomous Vehicle Navigation in Restricted Environments Fazri, Nurul; Susilawati, Helfy; Haqiqi, Mokh. Mirza Etnisa; Satyawan, Arief Suryadi
Jurnal Sistem Cerdas Vol. 8 No. 1 (2025)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v8i1.489

Abstract

Technological advancements have propelled the development of environmentally friendly transportation, with autonomous vehicles (AVs) and thermal imaging playing pivotal roles in achieving sustainable urban mobility. This study explores the application of the SegNet deep learning architecture for multi-class semantic segmentation of thermal images in constrained environments. The methodology encompasses data acquisition using a thermal camera in urban settings, annotation of 3,001 thermal images across 10 object classes, and rigorous model training with a high-performance system. SegNet demonstrated robust learning capabilities, achieving a training accuracy of 96.7% and a final loss of 0.096 after 120 epochs. Testing results revealed strong performance for distinct objects like motorcycles (F1 score: 0.63) and poles (F1 score: 0.84), but challenges in segmenting complex patterns such as buildings (F1 score: 0.34) and trees (F1 score: 0.42). Visual analysis corroborated these findings, highlighting strengths in segmenting well-defined objects while addressing difficulties in handling variability and elongated structures. Despite these limitations, the study establishes SegNet's potential for thermal image segmentation in AV systems. This research contributes to the advancement of computer vision in autonomous navigation, fostering sustainable and green transportation solutions while emphasizing areas for further refinement to enhance performance in complex environments.
Analysis of The Influence of Trust on User Satisfaction of Mobile Application E-Commerce Using DeLone and McLean Method Amani, Nailul; Megawati, Megawati; Maita, Idria; Nur Salisah, Febi; Marsal, Arif
Jurnal Sistem Cerdas Vol. 8 No. 1 (2025)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v8i1.490

Abstract

Lazada is one of the mobile-platform based e-commerce that has more than 100 million downloads. Lazada is an e-commerce site that offers several necessities such as mobile phones or tablets; household appliances, health and beauty, men's and women's fashion, baby and children's equipment, and electronics. User satisfaction is one of the important factors in the success of e-commerce implementation. However, there are still many complaints felt by Lazada application users which have an impact on user trust and satisfaction. Therefore, this study aims to determine the level of user satisfaction and how the trust factor influences user satisfaction on the Lazada mobile application using the DeLone& McLean model by adding the trust variable. Respondents in this study were Lazada application users in Pekanbaru City. This study uses a quantitative approach by distributing questionnaires online and sampling using a purposive sampling technique. The total data collected from 100 respondents was analyzed using the PLS-SEM technique with the help of the SmartPLS 4.0 tool. The results of this study indicate that Information Quality, Trust, and Use have a significant influence on user satisfaction and user satisfaction has a significant effect on trust. Of the 10 hypotheses proposed, four were rejected, namely information quality on trust, service quality on user satisfaction, system quality on user satisfaction, and trust on net benefit.
Land Cover Analysis with Fully Convolutional Network Ihwan, Abib Raifmuaffah; Lapatta, Nouval Trezandy; Joefrie, Yuri Yudhaswana; Anshori, Yusuf; Syahrullah, Syahrullah
Jurnal Sistem Cerdas Vol. 8 No. 1 (2025)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v8i1.496

Abstract

This study analyses land cover in Morowali Regency using Sentinel-2 satellite imagery and the Fully Convolutional Network (FCN) algorithm. Land cover analysis in this area is crucial for monitoring rapid industrialization, especially in the mining sector. The methodology includes retrieving image data from Google Earth Engine, image processing to eliminate cloud influences, and model training using the European Space Agency (ESA) datasets. The results of the analysis show that 50% of the Morowali Regency area has the potential to be planted with trees, followed by 20% for water areas, and the rest for bushes, development land, and empty land. This study proves that FCN can be relied on to predict land potential with high accuracy with a loss value of 1.3001.
Performance Analysis Of Green Supply Chain Management Using AHP And OMAX Methods Aditya Tri Pratama; Ernawati, Dira; Rahmawati, Nur
Jurnal Sistem Cerdas Vol. 8 No. 1 (2025)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v8i1.498

Abstract

The manufacturing industry in Indonesia has experienced significant growth, leading to a high level of urgency concerning environmental pollution. Currently, within the manufacturing sector, there is an increased emphasis on environmental protection and sustainable production, which has become a key priority for companies. One approach to preventing environmental pollution is the implementation of Green Supply Chain Management (GSCM). PT. XYZ is one of the companies that has not yet fully implemented this concept. This is evident from the considerable amount of waste and scrap materials from ship production that remain poorly managed. Based on these circumstances, this study was conducted with the objective of evaluating the performance level of Green Supply Chain Management at the company. The research adopts the Green SCOR model, using Analytical Hierarchy Process (AHP) for weighting and Objective Matrix (OMAX) for scoring. Data processing is carried out using five Green SCOR models: plan, source, make, deliver, and return, resulting in a total of 26 Key Performance Indicators (KPIs). Out of the 26 KPIs, 5 fall under the red category, 6 are categorized as yellow, and the remaining 15 are in the green category. The final performance score for Green SCM activities at the company is 7.890, which falls within the yellow category. This indicates an average performance level, where the achievement of the performance indicators has not yet reached the target, although it is nearing the desired goal.
Analysis Of Plastic Pellets Production Process To Reduce Waste Using Lean Six Sigma Method And FMEA Muhammad Hafiz Aziz; Dira Ernawati
Jurnal Sistem Cerdas Vol. 8 No. 1 (2025)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v8i1.499

Abstract

The rapid development of the industry has increased plastic production to meet market demand, which has led to a rise in plastic waste volume. One way to reduce plastic waste is by processing it into plastic pellets. CV. XYZ is a company that produces plastic pellets from PP, PS, and PE waste in Gresik, East Java. In its production process, the company faces issues such as high lead times of 990 minutes and non-standard product quality, including defects like clumping, cutting failures, and broken plastic pellets. This study aims to reduce waste and minimize lead time by applying the lean six sigma method with a DMAIC and FMEA approach. Three dominant types of waste were identified: storage, defects, and transportation. The implementation of improvement proposals successfully reduced lead time from 990 minutes to 780 minutes. The average sigma level was recorded at 3.14 with a DPMO of 50009, which falls into the good category for the average industry in Indonesia. Recommendations include demand forecasting, operator training, supplier selection, improving raw material quality, material handling, and utilizing conveyors in certain areas while minimizing non-value-added activities. Through the design of process activity mapping and big picture mapping, the efficiency of plastic pellet production can increase from 50.51% to 64.10%

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