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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 1 (2025): Sistemasi: Jurnal Sistem Informasi" : 40 Documents clear
Analysis and Evaluation of User Satisfaction using a Combination of Technology Acceptance Model (TAM) and WEBQUAL 4.0 Methods for Website-based Online Information Systems Tarwoto, Tarwoto; Ma'arifah, Windiya
Sistemasi: Jurnal Sistem Informasi Vol 14, No 1 (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.v14i1.3680

Abstract

The advancement of information and communication technology in the era of Industry 4.0 has driven the utilization of the internet, particularly in website-based information systems. This study focuses on evaluating user satisfaction by involving the IT team and analyzing aspects such as usability, accessibility, and the ability to present information on the website amikompurwokerto.ac.id. By adopting the Technology Acceptance Model (TAM) and Webqual 4.0 approaches, this research integrates the results from both methods to improve system quality. The findings reveal a positive relationship between factors such as user attitude, employee satisfaction, individual usage, ease of access perception, and perceived benefits, which influence internet usage intensity. Factors like availability, information quality, and service interaction also influence and significantly impact the improvement of information system quality. This research offers comprehensive insights into user satisfaction evaluation in an academic environment.
Implementation of Fuzzy Multiple Attribute Decision Making (FMADM) and Simple Additive Weighting (SAW) for Selecting the Best Stocks Nasution, Saddam Ali Habibie; Sriani, Sriani
Sistemasi: Jurnal Sistem Informasi Vol 14, No 1 (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.v14i1.4935

Abstract

Stock investment is an attractive option for modern society to enhance long-term asset value, despite significant risks, especially for novice investors who often face limited understanding of fundamental stock analysis. Such analysis involves various complex financial indicators. This study combines the Fuzzy Multiple Attribute Decision Making (FMADM) method and the Simple Additive Weighting (SAW) method to assist investors in selecting the best stocks in the banking sector. FMADM is applied to address data uncertainty using a fuzzy approach, while SAW calculates the final score based on criteria weights and performance. The research data were obtained from company financial reports for the 2019–2023 period, focusing on seven key criteria: Return on Assets (ROA), Return on Equity (ROE), Earnings Per Share (EPS), Net Profit Margin (NPM), Price-to-Book Value (PBV), Debt-to-Equity Ratio (DER), and Dividend Yield (DY). The study aims to develop a decision support system to simplify the investment analysis process while reducing the risk of decision-making errors for investors. The findings indicate that alternative A35/Bank BTPN Syariah (BTPS) ranked first with a final score of 0.7120, followed by A42/Bank Mega (MEGA) in second place with a score of 0.7074, and A08/Bank Central Asia (BBCA) in third place with a score of 0.6988. This system provides a practical solution for more structured and efficient investment decisions.
User Satisfaction Analysis of MyTelkomsel Application using Importance-Performance Analysis (IPA) and End-User Computing Satisfaction (EUCS) Methods Maulana, Bima; Rahmawita, Medyantiwi; Syaifullah, Syaifullah; Jazman, Muhammad
Sistemasi: Jurnal Sistem Informasi Vol 14, No 1 (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.v14i1.4866

Abstract

This study was conducted to analyze user satisfaction with the MyTelkomsel application using the End-User Computing Satisfaction (EUCS) and Importance-Performance Analysis (IPA) methods. The EUCS approach was employed to evaluate user satisfaction based on five key dimensions: content, accuracy, format, ease of use, and timeliness. Meanwhile, the IPA method was applied to identify features that require improvement based on the levels of importance and performance perceived by users. A quantitative method was used in this study, involving data collection through questionnaires distributed to active MyTelkomsel users. The results of the study revealed several dimensions that significantly contribute to user satisfaction, as well as areas that require prioritized improvements to enhance the quality of the application. The researchers hope that the findings of this study will assist developers in improving the application's quality to boost user satisfaction and loyalty.
Customer Satisfaction Analysis of ShopeeFood Service Quality using E-Servqual Method and Importance-Performance Analysis Yanti, Rahma; Megawati, Megawati; Zarnelly, Zarnelly; Saputra, Eki; Marsal, Arif
Sistemasi: Jurnal Sistem Informasi Vol 14, No 1 (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.v14i1.4785

Abstract

ShopeeFood was launched in April 2020. However, since its initial release, traffic to ShopeeFood services did not immediately perform well, as the platform had to compete with major players like GoFood and GrabFood, which are already well-known among the public. Numerous negative customer reviews about ShopeeFood indicate that customer satisfaction with the company's performance remains low. To measure the level of customer satisfaction, this study employed the E-Service Quality (E-Servqual) and Importance-Performance Analysis (IPA) methods. The results of the study show that, on average, the seven dimensions of E-Servqual measured exhibit a gap, with the average gap being negative. The highest gap was found in the "Responsiveness" dimension (-0.32), while the lowest gap was in the "Efficiency" dimension (-0.01). These findings indicate a discrepancy between customer expectations and satisfaction, suggesting that ShopeeFood's services are perceived as less satisfactory by its users. Data analysis revealed that the Importance-Performance Analysis (IPA) matrix for ShopeeFood's service quality highlights several attributes as top priorities for improvement. These attributes, identified through the Cartesian diagram of the Importance-Performance Analysis, fall under Quadrant I, specifically R11, RE16, and C19.
Exploring Organizational Motivation for Implementing Big Data Analytics: A Systematic Literature Review Suroto, Suroto
Sistemasi: Jurnal Sistem Informasi Vol 14, No 1 (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.v14i1.4513

Abstract

The objective of this study is to gain insights into the motivations behind organizations in adopting Big Data Analytics (BDA) by conducting a systematic literature review that provides the key determinants of BDA implementation in different sectors. This study follows the PRISMA guidelines using the PICOC principle to formulate research questions and establish inclusion criteria, and involves a systematic literature search followed by analysis to synthesize findings related to motivations for BDA adoption across sectors. The results of this study on the different sectors, including manufacturing, the public sector, Healthcare, education, and retail, have revealed that operational efficiency, product innovation, data management, and the management support of the organization act as the motivating factors in any BDA adoption decision. This study concludes that the motivation for BDA adoption across sectors is influenced by factors such as technological capabilities, organizational support, environmental pressures, and economic incentives, with specific differences in each sector indicating unique challenges and benefits, and offers a basis for further research and practical applications in the field of BDA.
UI/UX Model of Personnel Information System at the Synod Office using Design Thinking Method Dewi, Stefani Fransisca; Hartomo, Kristoko Dwi
Sistemasi: Jurnal Sistem Informasi Vol 14, No 1 (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.v14i1.4992

Abstract

The GKJ Synod Office is the administrative center for the Javanese Christian Churches, managing several service units such as correspondence, licensing for institutions/foundations, finance, and publishing materials for spiritual development. The GKJ Synod Office still faces issues related to employee data management, requiring technology to help address these challenges. The research uses the Design Thinking method, as it focuses on a user-centered approach, understanding the problems and limitations of users to create designs that align with their needs. This study results in a User Interface (UI) and User Experience (UX) model for a web-based employee information system that can be adopted by synods of churches across Indonesia. System testing was conducted to measure user satisfaction with the design of the employee information system, using the System Usability Scale (SUS) method. The final result for the admin was 88, and for the superadmin, it was 91. Based on the SUS Score interpretation criteria, the resulting system design received a grade (A), an adjective rating of (excellent), and acceptability ranges (acceptable), indicating a high level of user satisfaction.
Performance Comparison of LSTM and GRU Methods in Predicting Cryptocurrency Closing Prices Satria Andromeda, Rayhan; Winarsih, Nurul Anisa Sri
Sistemasi: Jurnal Sistem Informasi Vol 14, No 1 (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.v14i1.4880

Abstract

Technological advancements have increased interest in cryptocurrency investments, particularly Bitcoin and Ethereum, despite the high price volatility that remains a major challenge for investors. This study aims to predict cryptocurrency price fluctuations using Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) models, both of which are well-regarded for time series data analysis. Model performance was evaluated using parameters such as learning rate, timestamps, batch size, number of epochs, and Early Stopping callbacks. The evaluation metrics included Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE), and the coefficient of determination (R²). The results indicate that the GRU model outperforms LSTM in predicting cryptocurrency prices. For Bitcoin data, GRU achieved a MAPE of 0.38%, RMSE of 343.02, and R² of 0.9988, surpassing LSTM, which recorded a MAPE of 0.41%, RMSE of 356.01, and R² of 0.9987. Similarly, for Ethereum data, GRU achieved a MAPE of 0.45%, RMSE of 20.89, and R² of 0.9983, outperforming LSTM with a MAPE of 0.49%, RMSE of 22.29, and R² of 0.9980. These findings demonstrate that GRU is more accurate and efficient in modeling cryptocurrency price patterns, offering strategic opportunities for investors to make more informed decisions in navigating the complexities of the cryptocurrency market.
Pekalongan Regency Tourism Recommendation System with Content based Filtering Salsabilla, Cinta; Utomo, Danang Wahyu
Sistemasi: Jurnal Sistem Informasi Vol 14, No 1 (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.v14i1.4839

Abstract

This study implements content-based filtering for a tourist recommendation system in Pekalongan Regency. The method utilizes the TF-IDF algorithm to measure the weight of tourist attraction categories and cosine similarity to assess the similarity between attractions based on their categories. The dataset, provided by the Pekalongan Regency Tourism Office, includes eight categories: nature, water, artificial, culture, hills, beaches, camping, and adventure. The system is designed through the calculation of TF-IDF and cosine similarity to generate relevant recommendations. The findings show that the system effectively provides recommendations aligned with user preferences by presenting a list of tourist attractions with relevant categories. This system assists tourists in discovering destinations that match their interests while supporting the promotion of tourism in Pekalongan Regency.
Face Recognition for Personal Data Collection using Eigenface, Support Vector Machine, and Viola Jones Method Mardedi, Lalu Zazuli Azhar; Zulfikri, Muhammad; Syahrir, Moch.; Latif, Kurniadin Abd.; Apriani, Apriani
Sistemasi: Jurnal Sistem Informasi Vol 14, No 1 (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.v14i1.4728

Abstract

Personal data recording through facial recognition is a modern solution for individual identification; however, the main challenge lies in the accuracy and reliability of the system under various conditions. This study examines the implementation of machine learning as a solution, utilizing video and photo data for face detection and recognition. The study’s goal is to evaluate the effectiveness of facial image recognition by combining several methods, aiming for practical application across diverse settings, such as offices and schools. The methodology includes segmentation testing for edge detection, feature extraction, and real-time recognition. The system was developed using Eigenface, Support Vector Machine, and Viola-Jones methods, trained over 20 sessions. The results indicate that the system can recognize faces under both daytime and nighttime conditions, achieving 87% accuracy during the day and 81% at night. These findings make a significant contribution to the development of security systems based on facial recognition and emphasize the potential of this technology to enhance personal data security across various contexts
Application of Double Exponential Smoothing Method for Forecasting Laptop Sales Nurhayati, Rafika; Yusron, Rizqi Darma Rusdiyan; Sabilla, Wilda Imama; Rosiani, Ulla Delfana
Sistemasi: Jurnal Sistem Informasi Vol 14, No 1 (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.v14i1.4368

Abstract

PT Indo Bismar is a retail company focused on laptop sales. The company experiences fluctuations in laptop sales each month, which impacts inventory management as it becomes challenging to predict demand accurately. Consequently, PT Indo Bismar faces financial losses due to unsold laptops. To address this issue, a sales forecasting system has been designed to optimize inventory management more effectively and efficiently.This study applies the double exponential smoothing method to forecast laptop sales and uses the Mean Absolute Percentage Error (MAPE) to measure forecasting accuracy. The double exponential smoothing method was tested through a trial-and-error approach. This process produced varying alpha and beta values for different laptop brands and models. It involved repeated iterations to test each combination until the optimal values that yielded the best forecasting accuracy were identified. After obtaining the MAPE results through the trial-and-error approach, the average system MAPE was calculated to evaluate the overall accuracy of the system, resulting in 16.58%. This indicates that the sales forecasting system demonstrates good accuracy, as the error rate falls within the range of 10% to 20%. Therefore, the use of the double exponential smoothing method can assist PT Indo Bismar in managing inventory and making strategic decisions for future laptop sales

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