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INDONESIA
Sistemasi: Jurnal Sistem Informasi
Published by Universitas Islam Indragiri
ISSN : 23028149     EISSN : 25409719     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Sistemasi adalah nama terbitan jurnal ilmiah dalam bidang ilmu sains komputer program studi Sistem Informasi Universitas Islam Indragiri, Tembilahan Riau. Jurnal Sistemasi Terbit 3x setahun yaitu bulan Januari, Mei dan September,Focus dan Scope Umum dari Sistemasi yaitu Bidang Sistem Informasi, Teknologi Informasi,Computer Science,Rekayasa Perangkat Lunak,Teknik Informatika
Arjuna Subject : -
Articles 920 Documents
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Weather Classification in West Java using Ensemble Learning on Meteorological Data Azzahra, Cynthia Nur; Chrisnanto, Yulison Herry; Abdillah, Gunawan
Sistemasi: Jurnal Sistem Informasi Vol 14, No 5 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i5.5343

Abstract

Weather classification in West Java presents several challenges, particularly related to class imbalance in the dataset and the complexity of meteorological variables. This study aims to improve classification accuracy by proposing a stacking classifier approach that combines Support Vector Machine (SVM) and Random Forest as base learners, with Logistic Regression serving as the meta-classifier. To address the class imbalance, the Synthetic Minority Oversampling Technique (SMOTE) was applied, while model optimization was conducted using GridSearchCV. Weather data from the Indonesian Meteorological, Climatological, and Geophysical Agency (BMKG) for December 2024 was used and processed through transformation, normalization, and outlier handling. The dataset was then split into training and testing sets with ratios of 70:30, 80:20, and 90:10. The stacking classifier without SMOTE achieved the highest accuracy of 86.73%, but suffered from overfitting, indicated by a 13.27% gap between training and validation accuracy. The application of SMOTE improved the recall for minority classes to 76.3% and reduced overfitting, with the accuracy gap narrowing to less than 1%. The most stable performance was achieved with an 80:20 train-test split, where the SMOTE-applied and hyperparameter-optimized model reached an accuracy of 85.97%, an F1-score of 68.99%, and a statistically significant t-test result (p < 0.001). These findings demonstrate that the combination of stacking classifiers, SMOTE, and hyperparameter tuning effectively mitigates class bias and enhances model generalization, outperforming single-model classifiers in handling imbalanced weather data.
Usability of the GrabMerchant Application: An Evaluation using the System Usability Scale and the Retrospective Think Aloud Method Handayani, Rima; Maria, Evi
Sistemasi: Jurnal Sistem Informasi Vol 14, No 4 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i4.5283

Abstract

GrabMerchant is an application used by GrabFood and GrabMart business partners to manage various business operations, including order processing, inventory management, and promotional activities. Despite its widespread use, user satisfaction remains relatively low, with an average rating of 3.8 out of 5 based on 214,000 reviews—lower than its competitor, GoBiz, which has a rating of 4.1 out of 5 from 195,000 reviews. Several issues reported by users—such as errors in the notification feature, inventory management, and promotion setup—indicate potential usability problems. This study aims to evaluate the usability level of the GrabMerchant application using the System Usability Scale (SUS) and the Retrospective Think Aloud (RTA) method. The SUS method is used to measure users’ perceptions of the application's ease of use, while the RTA method helps assess effectiveness and efficiency, as well as identify issues that may not be detected through quantitative measurements. The findings show that GrabMerchant received a SUS score of 74.01, which places its usability in the “Good” category based on the adjective rating scale. The application’s effectiveness rate was recorded at 93%, indicating high success in task completion, while efficiency was measured at 0.35 goals per second, suggesting that task completion time could still be improved. Furthermore, the study identified several key issues, including difficulty locating features, an unappealing interface design, and a lack of user guidance. Based on these findings, the study proposes several recommendations, such as adding a search feature, optimizing the user interface—e.g., by clarifying icon layouts, minimizing redundancy, improving contrast, and using more distinct color variations for feature icons—as well as providing simulators and in-app tutorials. Implementing these recommendations is expected to improve the overall usability of the GrabMerchant application, enhance the user experience, and ultimately increase user loyalty.
Evaluating the User Experience of a Mobile Ticketing Application using the User Experience Questionnaire (UEQ) Bailaen, Elsa Anjamilen; Bangkalang, Dwi Hosanna
Sistemasi: Jurnal Sistem Informasi Vol 14, No 3 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i3.5243

Abstract

The digitalization of the mobile ticketing sector in Indonesia has seen significant growth, with a projected 50% increase in mobile ticketing app usage by 2025. Popular applications such as Traveloka, Tiket.com, Agoda, and Booking.com dominate the market, yet they face several technical challenges, including navigation difficulties, unclear interfaces, performance bugs during peak hours, slow application response times, and limited features. This study employed the User Experience Questionnaire (UEQ) method and involved 578 respondents selected through purposive sampling. The criteria included active users of one of the mobile ticketing apps and individuals aged between 20 and 40 years. The results of the t-test revealed that Agoda needs to improve the perspicuity aspect by simplifying its dense user interface, particularly in accommodation and travel ticket searches. Regarding efficiency, Traveloka, Agoda, and Booking.com must enhance their search systems and address bugs/errors that disrupt performance during peak usage times. For stimulation, Traveloka should enhance user experience by providing a more dynamic and responsive layout when navigating pages or performing searches. In terms of novelty, both Agoda and Booking.com are advised to integrate local e-wallets such as GoPay, OVO, and DANA, as well as bank transfer options, since currently they only support credit card payments. These findings highlight the critical role of UX in improving user satisfaction and suggest that continuous user-centered development is essential for maintaining competitiveness in the mobile ticketing industry.
Image Classification of Indonesian Snacks using Convolutional Neural Network Eliyen, Kunti; Izzah, Abidatul; Aullia, Fikha Rizky
Sistemasi: Jurnal Sistem Informasi Vol 14, No 3 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i3.4647

Abstract

Each region in Indonesia has its own unique and distinctive culinary traditions. However, many people are still unfamiliar with the names of traditional Indonesian snacks, especially those that originate from regions other than their own. Promoting these traditional snacks is essential as an initial step in educating both domestic and international audiences about Indonesia’s cultural diversity. Culinary heritage is also a key factor in attracting tourists to visit a region. One way to address this issue is through image classification of Indonesian traditional snacks using Convolutional Neural Networks (CNN). This study uses a dataset consisting of 30 images across 10 classes, with 3 images per class. The model was trained over 40 epochs and achieved an accuracy of 86%. The testing phase yielded a recall of 86%, precision of 91%, and an F1-score of 88%.
Evaluating User Experience of OpenProject at PT Promanufacture Indonesia Salatiga using the User Experience Questionnaire (UEQ) Method Adventien, Irene Puspa; Maria (SCOPUS ID: 57093633500), Evi
Sistemasi: Jurnal Sistem Informasi Vol 14, No 3 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i3.5185

Abstract

The purpose of this study is to evaluate the user experience of OpenProject at PT Promanufacture Indonesia Salatiga using the User Experience Questionnaire (UEQ) method. The UEQ method was chosen for its effectiveness in measuring user satisfaction and analyzing the quality of user experience across six main evaluation scales: attractiveness, perspicuity, efficiency, dependability, stimulation, and novelty. Data were collected from 100 OpenProject users at PT Promanufacture Indonesia Salatiga and analyzed based on the average scores for each scale category. The results showed that most categories received positive ratings, with average scores above 0.8, except for the attractiveness scale, which fell into the "below average" category. The benchmark analysis indicated that the dependability scale ranked as "excellent," while the perspicuity and efficiency scales were categorized as "above average." The stimulation and novelty scales were rated as "good." These findings suggest that OpenProject excels in efficiency, dependability, and novelty, although improvements in visual appeal are necessary to enhance user comfort. This study contributes to the development of user experience theory in digital project management systems and reinforces the validity of the UEQ as a UX evaluation tool in professional software environments. It also highlights that while attractiveness may not be a primary factor in project management systems, it still plays a role in fostering user engagement. Therefore, UX models for enterprise software should strike a balance between functionality and aesthetics. The results of this research provide valuable insights for companies seeking to improve user experience and the effectiveness of project management systems.
Application of Artificial Intelligence using K-Means for Programming Question Assessment Waliyyudin, Waliyyudin; Ibrahim, Ichsan
Sistemasi: Jurnal Sistem Informasi Vol 14, No 4 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i4.5360

Abstract

The manual assessment of programming assignments remains a significant challenge in educational settings due to its time-consuming nature and susceptibility to human error. Observational studies of course instructors reveal that over 40% have made grading mistakes, often due to fatigue or inconsistent evaluation standards. This study aims to develop an automated assessment system using artificial intelligence to enhance both objectivity and efficiency in the evaluation process. The method employed is the K-Means clustering algorithm, chosen for its ability to group answers based on similarities in logic and code structure rather than mere textual similarity. Five assessment categories were used as clustering standards: Logic and Algorithm, Data Structures, Object-Oriented Programming (OOP), Implementation, and Error Handling. The system was developed using an Agile Development approach and evaluated with student responses from programming courses. System performance was validated quantitatively by comparing cluster results against ground truth labels from manual grading. The system achieved 87% clustering accuracy, reduced the average grading time to 4.5 seconds per answer (compared to 13 seconds manually—representing a 65% efficiency gain), and decreased the inter-rater score standard deviation from 7.5 to 2.8 points. The results indicate that the system can deliver accurate real-time feedback. This study focused on programming questions ranging from easy to hard difficulty levels. In the future, the system could be enhanced by integrating advanced syntax analysis and expanding the evaluation criteria to support large-scale deployment.
Implementation of COBIT 2019 for Designing Hospital Performance Improvement Recommendations Radja, Carrisa Adnyana Putri; Budiraharjo, Raden; Chazar, Chalifa
Sistemasi: Jurnal Sistem Informasi Vol 14, No 3 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i3.5076

Abstract

Service delivery at Kiwari Regional Public Hospital (RSUD Kiwari) in Bandung continues to face various challenges in meeting established standards. These challenges primarily stem from inefficiencies in business processes, particularly in patient registration, medical consultations, inpatient services, and patient transfers. These issues were previously identified through bottleneck analysis using a process mining approach. The identified bottlenecks indicate delays in several stages of the hospital service process. This study aims to provide improvement recommendations to enhance the hospital's business process capabilities based on the bottleneck analysis results obtained from process mining. The research adopts the COBIT 2019 framework to assess and improve business process capabilities, with a focus on the DSS06 (Deliver, Service, and Support) domain, deemed most relevant to the hospital’s current challenges. COBIT 2019 was selected for its systematic approach to measuring and enhancing IT process capabilities. The findings indicate that the current business process capability level at RSUD Kiwari Bandung is at Level 2, while the target level is Level 3. To achieve this goal, the study proposes a set of improvement recommendations that can serve as an evaluation tool and a guide to improving IT governance and service efficiency at RSUD Kiwari Bandung.
Maturity Level Analysis of the BAZNAS Sukabumi Regency Website using the COBIT 2019 Framework in the BAI02 Domain yuniar, siti rahma; saepudin, sudin; satria, hendri eka
Sistemasi: Jurnal Sistem Informasi Vol 14, No 5 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i5.5359

Abstract

The BAZNAS Sukabumi Regency website plays a vital role in supporting transparent and efficient digital zakat services. However, challenges remain in updating features and optimizing the management of information system requirements, which hinder full digital transformation. These issues highlight the need for an evaluation of the maturity level of the information systems in use. This study aims to assess the maturity level of information system requirements management on the BAZNAS Sukabumi Regency website using the COBIT 2019 framework, specifically within the BAI02 domain (Managed Requirements Definition). The research methodology includes observation, interviews, and literature review, analyzed based on the capability level model in COBIT 2019. The findings indicate that the maturity level is at Level 3 (Established Process), which means the processes are standardized, documented, and consistently implemented. However, there is a gap compared to the desired (TO-BE) state of Level 4 (Predictable), particularly in areas such as monitoring, performance measurement, and quantitative and systematic risk management. The study concludes that while the BAZNAS Sukabumi Regency website demonstrates good information system management practices, improvements are still needed in control mechanisms, continuous performance measurement, and periodic evaluations. Recommendations focus on enhancing governance practices, strengthening performance metric documentation, and developing strategies to sustainably improve information system capabilities.
Analysis of User Satisfaction Level Of the Online Lecture Information System (Sikuli) using The EUCS Method at Universitas Muhammadiyah Riau Raihan, Muhammad; Jazman, Muhammad; Ahsyar, Tengku Khairil; Anofrizen, Anofrizen
Sistemasi: Jurnal Sistem Informasi Vol 14, No 4 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i4.5279

Abstract

The effectiveness of an information system is a key determinant of user pleasure, specifically within digital gaining knowledge of platforms. This studies seeks to evaluate the satisfaction degree of customers towards the the Online Lecture Information System (SIKULI) at Universitas Muhammadiyah Riau, employing the EUCS method. The study similarly investigates the tremendous participants to user satisfaction by using analyzing 5 dimensions from the EUCS making use of a quantitative technique, the studies implemented accidental sampling, related to ninety nine lively college students as respondents. facts evaluation was achieved the use of the SmartPLS software to discover the electricity and course of relationships a number of the variables. The analysis found out that simplest ease of use and timeliness had a statistically tremendous effect on user satisfaction, whereas content, accuracy, and format did not exhibit outstanding effects. those effects emphasize that ease of use and timeliness are key factors in improving satisfaction with SIKULI. consequently, this have a look at offers sensible pointers for technical improvements to optimize the performance of academic information systems.
Applying Artificial Intelligence to Analyze Emotions in Social Media Comments using Large Language Models Astiti, Sarah; Iswandi, Iswandi; Putra, Tomy Nanda; Darmansah, Darmansah
Sistemasi: Jurnal Sistem Informasi Vol 14, No 3 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i3.5187

Abstract

Advancements in Large Language Models (LLMs) have opened new opportunities for emotion analysis in social media comments. This study aims to explore the application of LLMs in classifying users' emotions based on their comment texts across various social media platforms. The methodology involves collecting comment data from Twitter, Facebook, and YouTube, followed by text preprocessing using Natural Language Processing (NLP) techniques. LLMs such as GPT and BERT are evaluated for their ability to detect primary emotions including happiness, sadness, anger, and fear. The results show a precision of 0.89 (89%), recall of 0.80 (80%), and an F1-score of 0.84 (84%). These findings indicate that LLMs offer higher accuracy compared to conventional sentiment analysis methods, particularly in their ability to understand linguistic context and nuances.

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