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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 177 Documents
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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%
Design of a Greenhouse System for Vegetable Plants Based on the Internet of Things Janne Deivy Ticoh; Junaedy Alexandrya Kaengke; Ridwan, Ridwan
Jurnal Sistem Cerdas Vol. 8 No. 1 (2025)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v8i1.501

Abstract

This research aims to overcome the problem of lack of efficiency in Green House management in North Sulawesi. Where management is still done manually. The main problem in this research is the high cost of procuring a control system and farmers' lack of understanding regarding the Internet of Things (IoT). To solve this problem, an IoT based Green House control system was developed which integrates various sensors to monitor and control temperature, humidity and light intensity automatically. This system uses an ESP32 microcontroller and the Blynk application to facilitate remote monitoring. Trial results shows that this system is able to maintain optimal environmental conditions for plant growth, increase productivity, and reduce the risk of damage due to climate change. By implementing this system, it is hoped that farmers in North Sulawesi can optimize the use of resources and increase the quality and quantity of harvests make an important contribution to development of sustainable agriculture in the tropic
Analysis of Reverse Logistics Implementation in Improving Operational Efficiency Arzety, Zahra; Pulansari, Farida
Jurnal Sistem Cerdas Vol. 8 No. 1 (2025)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v8i1.502

Abstract

In the era of globalization and increasingly fierce competition, some industrial companies are required to focus not only on product and distribution efficiency but also on post-consumer product management. Supply chain issues need to be considered because they are related to the productivity of the company, if the supply chain management of a company runs well, the company's goals will be achieved, and vice versa. In addition to helping implement the principle of reducing, reusing, and recycling, reverse logistics also acts as feedback from customers on the product (finished or unfinished), including the sustainability aspect of the product. The frequent return of kWh (kilowatt-hour) meters in households thatoccur returns/defects and are returned from the reporting of consumers or customers that still exist and also the handling of companies that have not met the standards and strategies for the future. The results of the analysis of the maturity level of the implementation of reverse logistics in these three companies can be categorized at level 3 (Developed Level) with the results of measurements using MSI (Method of Successive Interval) successively are 2.549; 2.292; 2.459; 2.932; 2.677. With the calculation of scores on IFE and EFE in the IE matrix, it is in quadrant II (medium-high).
Customer Segmentation Analysis Through RFM-D Model and K-Means Algorithm Refri Martiansah; Siti Monalisa; Fitriani Muttakin; Mona Fronita
Jurnal Sistem Cerdas Vol. 8 No. 1 (2025)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v8i1.504

Abstract

This research analyzes customer segmentation through the RFM-D (Recency, Frequency, Monetary, and Diversity) model and the K-Means algorithm. The data comes from sales transactions at Café Z from January 2023 to February 2024, with 10,212 entries. The applied methodology includes several stages: data pre-processing, cleaning, transformation, normalization, and clustering. Clustering validation was carried out using the Davies-Bouldin Index (DBI) to ensure the quality of the clusters formed. The analysis results identified three customer clusters based on purchasing behavior, indicating that the K-Means algorithm effectively groups customers. These findings provide insight for companies to design marketing strategies that are more focused and appropriate to the characteristics of each customer segment. Companies can improve operational efficiency, increase customer satisfaction, and maximize profitability by utilizing this segmentation. This research contributes to optimizing resource allocation and personalizing marketing approaches, ultimately strengthening customer relationships.
Leveraging BERT and T5 for Comprehensive Text Summarization on Indonesian Articles Satya, Mohammad Wahyu Bagus Dwi; Luthfiarta, Ardytha
Jurnal Sistem Cerdas Vol. 8 No. 2 (2025): August
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v8i2.458

Abstract

One of the main challenges in the field of Natural Language Processing (NLP) is developing systems for automatic text summarization. These systems typically fall into two categories: extractive and abstractive. Extractive techniques generate summaries by selecting important sentences or phrases directly from the original text, whereas abstractive techniques focus on rephrasing or paraphrasing the content, producing summaries that resemble human-written ones. In this research, models based on Transformer architectures, including BERT and T5, were used, which have been shown to effectively summarize texts in various languages, including Indonesian. The dataset used was INDOSUM, consisting of Indonesian news articles. The best results were achieved with the T5 model, using the abstractive approach, recorded ROUGE-1, ROUGE-2, and ROUGE-L scores of 69.36%, 61.27%, and 66.17%, respectively. On the other hand, the extractive BERT model achieved ROUGE-1, ROUGE-2, and ROUGE-L scores of 70.82%, 63.99%, and 58.40%.

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