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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 40 Documents
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Search results for , issue "Vol 14, No 6 (2025): Sistemasi: Jurnal Sistem Informasi" : 40 Documents clear
Lung Cancer Classification using the Naïve Bayes Method with SMOTE Akbar, Ananda Ikhwana Khairur; Astuti, Yani Parti
Sistemasi: Jurnal Sistem Informasi Vol 14, No 6 (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.v14i6.5607

Abstract

The primary challenges addressed in this study include delays in the early detection of lung cancer due to non-specific initial symptoms, the limitations of the Naïve Bayes algorithm in processing categorical data such as symptoms, gender, and smoking habits, as well as class imbalance issues in the dataset that can affect model accuracy. To overcome these challenges, the SMOTE (Synthetic Minority Over-sampling Technique) method was applied to improve classification performance. This study aims to implement the Naïve Bayes algorithm for lung cancer classification and compare its performance on imbalanced data versus data balanced using SMOTE. The methodology consists of data preprocessing, encoding, applying SMOTE for balancing, and classification using Naïve Bayes. Evaluation was performed using three data split ratios: 80:20, 70:30, and 60:40. The results show that applying SMOTE led to performance improvements, with the most significant gains observed at the 60:40 split ratio. In this case, model accuracy improved from 88.29% to 93.19%. For the “Yes” (positive) class, precision remained at 0.96, recall at 0.91, and F1-score at 0.93. However, for the “No” (negative) class, precision improved from 0.40 to 0.90, recall from 0.60 to 0.96, and F1-score from 0.48 to 0.93. Conversely, slight decreases in accuracy were observed for the 80:20 and 70:30 ratios after SMOTE application. These findings demonstrate that SMOTE significantly enhances model performance at the 60:40 ratio, not only in terms of accuracy but also in recall and F1-score, which are crucial for reducing false negatives in the minority (“Yes”) class. This is especially critical in early detection, as correctly identifying actual cancer cases is more important than merely maintaining overall accuracy. Although SMOTE did not always improve accuracy at other ratios, it still contributed to better cancer case detection. Therefore, its application should be considered carefully, balancing overall accuracy with clinically meaningful metrics.
CNN-Based Model for Classifying Regional Types on Shipping Label Images Widodo, Wahyu Kurniawan Ade Nur; Triyanto, Wiwit Agus; Setiaji, Pratomo
Sistemasi: Jurnal Sistem Informasi Vol 14, No 6 (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.v14i6.5584

Abstract

The rapid growth of the e-commerce sector has led to a significant surge in shipping volumes in Indonesia. In logistics systems, a shipping receipt serves as a crucial document containing destination information such as address, city/regency, and postal code. Errors or delays in classifying destination regions not only generate additional operational costs (e.g., reshipment fees and service penalties) but may also reduce customer satisfaction and harm the reputation of service providers. This study proposes the implementation of a Convolutional Neural Network (CNN) model to automatically classify region types in shipping receipt images, aiming to minimize manual errors and accelerate processing time. CNN was chosen for its ability to recognize complex visual patterns in digital documents without requiring manual feature extraction. The dataset used in this study consists of 1,540 shipping receipt images from various courier services, labeled as REG_JAWA and REG_LUARJAWA. The research process includes image preprocessing (resizing, normalization, augmentation), CNN architecture design, model training with early stopping, and performance evaluation using accuracy, precision, recall, and F1-score metrics. The results demonstrate that the model achieved a testing accuracy of 99.87%, precision of 99.71%, and recall of 100%, highlighting its strong potential for real-world implementation in logistics systems to improve efficiency and reliability of deliveries.
Designing a Prototype Information System for a Building Material Store using the Zachman Framework Adzikra, Kaysha Soffa Marwa Nabila; Saepudin, Sudin; Ekasatria, Hendri; Mupaat, Mupaat
Sistemasi: Jurnal Sistem Informasi Vol 14, No 6 (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.v14i6.5499

Abstract

The growing need for digitalization of business processes in the retail sector requires information systems capable of supporting operational efficiency and accurate decision-making. This study aims to design an inventory management information system for CV. Berjuang Sakti using an Enterprise Architecture approach based on the Zachman Framework. The previously applied manual system had led to several issues, including inaccurate record-keeping, data inconsistencies, and delayed reporting. The Zachman Framework was applied to structure the system design across six main perspectives: Planner, Owner, Designer, Builder, Implementer, and User. The design results include stakeholder-based requirements analysis, system modeling (ERD, Use Case Diagram, and Activity Diagram), and a user interface prototype featuring real-time stock tracking, transaction management, and reporting. Usability testing using the System Usability Scale (SUS) with 15 respondents produced a score of 72.3, categorized as “Good,” indicating that the system is feasible and effective in supporting the daily operations of CV. Berjuang Sakti. These findings provide practical implications for improving efficiency and accuracy in inventory management through the adoption of a structured and measurable system architecture.
High Precision Deep Learning Model for Road Damage Classification using Transfer Learning Ghofur, Muhammad Abdul; Murdifin, Murdifin; Hardandrito, Awan Gumilang; 'Uyun, Shofwatul
Sistemasi: Jurnal Sistem Informasi Vol 14, No 6 (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.v14i6.5707

Abstract

Roads are critical infrastructure that frequently experience damage, directly impacting transportation safety and efficiency. Manual road damage inspection is time-consuming and resource-intensive, highlighting the need for automated, image-based approaches. This study compares two Convolutional Neural Network (CNN) architectures—MobileNetV2 with transfer learning and a custom-built CNN—for classifying road surface damage severity. The dataset consists of 1,800 road surface images evenly distributed across three categories: good, minor damage, and severe damage. All images were normalized, augmented, and resized, followed by evaluation using 5-Fold Cross-Validation to ensure robust performance. Experimental results show that MobileNetV2 achieved an accuracy of 98%, outperforming the custom CNN, which achieved 89%. These findings demonstrate the effectiveness of transfer learning in improving classification accuracy with limited data and highlight the potential of MobileNetV2 for efficient, real-time road damage detection systems that can be integrated into intelligent infrastructure monitoring solutions.
Application of OLAP based Business Intelligence and Predictive Analysis (Random Forest Classifier and ARIMA) in a Fintech P2P Lending Company Olivia, Kristiana; Papilaya, Frederik Samuel
Sistemasi: Jurnal Sistem Informasi Vol 14, No 6 (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.v14i6.5663

Abstract

The rising rate of non-performing loans (NPLs) in the financial technology (fintech) P2P lending industry has become a serious challenge, including for PT XYZ, which focuses on funding the MSME sector. This study applies Business Intelligence using OLAP and predictive analytics at PT XYZ over a two-year period. The dataset consists of records from January 2023 to December 2024, comprising 276,320 loan transactions and 267,542 repayment records. The OLAP approach was employed to explore loan transactions, repayment performance, and delinquency patterns across multiple dimensions, such as account, time, payment method, and bank used. The results of this exploration were visualized through three interactive dashboards tailored to the analysis focus. Predictive analysis was conducted using a Random Forest Classifier, which identified loan_amount as the most influential variable in predicting potential delinquency. However, the model’s performance was relatively limited, achieving an accuracy of 61.47%, precision of 38.33%, and recall of 36.89%. Delinquency trend forecasting using the ARIMA (2,1,1) model indicated an increase in overdue cases up to March 2025, followed by a decline in subsequent months. The model evaluation yielded MAPE of 39.74%, sMAPE of 33.32%, and RMSE of 1086.77, suggesting moderately adequate predictive accuracy but with a relatively high error rate. This study recommends implementing incentives for OBA (Online Borrower Accounts) with good repayment performance and restricting loan ceilings based on an automated risk score. Further development is advised by enriching the dataset with additional variables and enhancing predictive models through techniques such as oversampling (e.g., SMOTE) and hyperparameter tuning to maximize accuracy.
Implementation of Safety Stock and ROP Methods in the Inventory Information System of Kava Kudus Coffee Shop Taufiq, Muhammad Bagas; Setiawan, R Rhoedy; Irawan, Yudie
Sistemasi: Jurnal Sistem Informasi Vol 14, No 6 (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.v14i6.5541

Abstract

Manual stock management, particularly through paper based record keeping, remains a challenge for culinary businesses such as Kava Coffee Shop in Kudus. Issues such as inaccurate records, delayed reordering, and the absence of notifications for expired or damaged ingredients can lead to stockouts or overstocking. This study aims to design a web-based inventory information system incorporating the Safety Stock and Reorder Point (ROP) methods to optimize the management of perishable raw materials. The system was developed using the Waterfall model, covering requirements analysis, design with Use Case and Activity Diagrams, feature implementation, and testing through the Black-box method. Key system features include minimum stock notifications, expiration tracking, transaction management, and damaged goods returns. Testing results show that the system performs according to specifications, achieving a 100% success rate across functional scenarios. Compared to previous studies, this system demonstrates superiority by being web-based, focusing on perishable goods, and offering integrated features. Therefore, the system can enhance record accuracy, accelerate decision-making, and ensure the availability and quality of raw materials at Kava Coffee Shop.
Does JASTIP as Facilitating Condition Affect the E-Marketplace Adoption in Developing Region? Sipahelut, Novelia; Inan, Dedi I; Juita, Ratna; Indra, Muhamad
Sistemasi: Jurnal Sistem Informasi Vol 14, No 6 (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.v14i6.5393

Abstract

E-marketplaces are expanding in developing regions but face barriers related to logistics costs and infrastructure. JASTIP, an informal proxy shopping service, has emerged as a potential solution to improve accessibility. This study examines the influence of perceived cost, social influence, hedonic motivation, and facilitating conditions on e-marketplace adoption using a modified UTAUT model analyzed through PLS-SEM with data from 185 respondents in West Papua. The findings show that hedonic motivation and social influence significantly increase user intention, perceived cost directly affects usage behavior, and facilitating conditions strengthen intention but do not directly influence usage. These results emphasize the role of JASTIP in reducing costs and improving accessibility. This study recommends improving JASTIP access and infrastructure, implementing flexible pricing policies, and promoting community-based marketing to enhance e-marketplace adoption in developing regions.
Design of an Archiving Information System using the Agile Scrum Method Setiawan, Denny Farissa; Rahardja, Yani
Sistemasi: Jurnal Sistem Informasi Vol 14, No 6 (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.v14i6.5429

Abstract

This study aims to design and implement a web-based archiving information system at PT Sarana Tirta Ungaran using the Agile Scrum methodology. The background of this research lies in the challenges of manual archive management, which often lead to difficulties in document retrieval, risks of data loss, and inefficient use of storage space. By adopting the Agile approach, the system was developed iteratively through stages such as product backlog, sprint planning, and daily Scrum, allowing for dynamic adjustments to user requirements. The system incorporates four types of user roles—super admin, admin, director, and general administrative staff—with key features including login, archive management (CRUD), document search, and activity logs. The design process employed UML, covering use case diagrams, activity diagrams, and class diagrams. Testing results demonstrate that the system improves archiving efficiency, accelerates information access, and supports the digitalization process within the company. Therefore, this information system is expected to enhance overall organizational performance.
Computika: A Mobile-based Interactive Learning Media for Computer Systems Subject in Vocational High Schools Hidayat, Rahmat; Rian, Rahmad Al; Herlandy, Pratama Benny; Novalia, Melly
Sistemasi: Jurnal Sistem Informasi Vol 14, No 6 (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.v14i6.5715

Abstract

Vocational high school students often face difficulties in understanding computer systems, creating the need for an innovative and interactive learning medium. This study aims to develop Computika, a mobile-based learning platform designed to enhance students’ comprehension of computer systems. The research employed a Research and Development (R&D) approach using the 4D development model (Define, Design, Develop, Disseminate). Validation was conducted by subject-matter experts, media experts, and tested on 21 students. The validation results indicated a very high level of feasibility: 100% from subject-matter experts, 94% from media experts, and positive responses from both students (94%) and teachers (91%). These findings confirm that Computika is highly feasible to be implemented as an innovative interactive learning solution that improves students’ understanding and learning motivation in computer systems courses.
Designing Chatbot Interface to Accelerate Services at Disdukcapil Salatiga Sheviana, Laela Sheviana; Cahyono, Ariya Dwika
Sistemasi: Jurnal Sistem Informasi Vol 14, No 6 (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.v14i6.5596

Abstract

Managing population documents such as lost or damaged ID cards (KTP) and Family Cards (KK) remains a challenge for the public due to complex procedures, lengthy processing times, and limited access to information. This study aims to design a chatbot interface to simplify the document management process using a Design Thinking approach focused on user needs. Design Thinking consists of five stages: Empathize (identifying user problems), Define (formulating the core issues), Ideate (generating solution ideas), Prototype (creating initial designs), and Test (evaluating the solution). The prototype was tested on 37 respondents to assess its quality. The analysis results show that the average score for all statements ranged between 3 and 4, indicating positive feedback on the design. All items were validated with an r-count value > 0.3, with the highest value being 0.864, while the reliability test produced a Cronbach’s Alpha of 0.863, demonstrating excellent internal consistency. Overall, the chatbot was considered effective, user-friendly, and capable of supporting digital transformation at the Civil Registry Office (Disdukcapil). The trial also indicated a potential increase in user satisfaction of up to 85% and a 60% improvement in information retrieval efficiency compared to conventional methods. These findings suggest the proposed solution as a viable digital alternative to accelerate services, reduce queues, and enhance transparency and public satisfaction.

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