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Kab. indragiri hilir,
Riau
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
Parameter Optimisation of Support Vector Machine using Genetic Algorithm for Cyberbullying Detection Alqowiy, Mohd Qorib; Utami, Ema
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.v14i1.4870

Abstract

The rapid development of technology has greatly facilitated various daily activities, including communication. Several social media platforms enable users to connect with one another easily. However, this progress often comes with negative impacts. One such impact is cyberbullying, which has become a growing concern. To address this issue, many researchers have proposed solutions for detecting cyberbullying. Among these, the Support Vector Machine (SVM) method is commonly used because it delivers more accurate results compared to other algorithms. However, determining the optimal kernel parameters for SVM remains a challenge. To overcome this, various search algorithms have been suggested to optimize SVM parameters. This study utilizes a genetic algorithm to find the optimal values for the C and gamma parameters. The results demonstrate an accuracy improvement, with the genetic algorithm achieving an accuracy of 86%. This highlights the effectiveness of genetic algorithms in optimizing SVM parameters for cyberbullying detection.
Analysis of the E-Performance System and Competence on Employee Performance with Work Motivation as a Mediator Syafrinadina, Syafrinadina; Prawirosumarto, Suharno; Lusiana, Lusiana
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.v14i1.4802

Abstract

This study aims to assess the impact of the e-performance system and human resource (HR) competencies on employee performance, with work motivation as an intervening variable at the Regional Secretariat Office of Indragiri Hilir Regency. Using Structural Equation Modeling (SEM) with Partial Least Squares (PLS) 3.0, data were collected through a questionnaire distributed to 177 respondents. The analysis revealed several key findings. First, the e-performance system positively and significantly influences work motivation. Similarly, HR competencies have a positive and significant effect on work motivation. Additionally, the e-performance system directly impacts employee performance in a positive and significant way. However, the relationship between HR competencies and employee performance was found to be positive but not significant. Work motivation, on the other hand, has a positive and significant influence on employee performance. Furthermore, work motivation mediates the relationship between the e-performance system and employee performance, as well as between HR competencies and employee performance, both with positive and significant effects. These findings highlight the critical role of motivation in enhancing employee performance through e-performance systems and HR competencies.
Measurement of User Satisfaction of ELSIMIL Application in Stunting Prevention in Indonesia using EUCS Method Zacky, M.; Saputra, Eki
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.v14i1.4627

Abstract

Stunting is a long-term nutritional problem diagnosed in children under two years old and characterized by shorter height difference compared to children of the same age. A public health concern, stunting increases a child's risk of illness and death and stunts their ability to thrive intellectually and physically. The government has given primary responsibility for preventing stunting to the National Population and Family Planning Agency (BKKBN). One of BKKBN's efforts is to develop the ELSIMIL application, which is a media application for screening, mentoring and preventing stunting. However, during the implementation of the use of the ELSIMIL application, there are many problems faced by the family assistance team and prospective brides, one of which is the lack of knowledge of prospective brides in running the ELSIMIL application, for example: during the registration of bride and groom data, there are still many errors in inputting data so that the results issued in the form of an ELSIMIL certificate do not match the condition of the prospective bride and groom. This study uses the End-User Computing Satisfaction (EUCS) method to assess user satisfaction in running the ELSIMIL application. This study shows that the content variable has a significant influence on user satisfaction compared to other variables such as accuracy, format, ease of use, and timeliness. The more relevant and quality information is presented, the more satisfied users will be. However, simultaneously all variables affect user satisfaction. The implications of these findings can provide valuable guidance for digital platform developers and related parties in designing more targeted and effective interventions, as well as facilitating desired behavioral changes in society.
UI/UX Analysis of Klik Pelalawan Application using Design Thinking Approach and System Usability Scale (SUS) Ramadhan, Rifky; Anofrizen, Anofrizen; Saputra, Eki; Syaifullah, Syaifullah
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.v14i1.4926

Abstract

This study aims to redesign the UI/UX of the Klik Pelalawan application to enhance user comfort. Klik Pelalawan is a mobile application designed as a platform for submitting complaints or aspirations from the public to the local government of Pelalawan Regency. An initial assessment of the application's UI/UX was conducted using the System Usability Scale (SUS) method, accompanied by a survey of 35 residents of Pelalawan Regency. The assessment resulted in a score of 43, indicating that the application's usability level requires improvement. To address this issue, an analysis and redesign process was carried out using the Design Thinking methodology, which consists of five stages: empathize, define, ideate, prototype, and testing. During the testing phase, the redesigned UI/UX was reevaluated by 40 residents of Pelalawan Regency using the SUS method and a questionnaire. The new design achieved a score of 77, signifying that the redesigned UI/UX has successfully improved user comfort for the Klik Pelalawan application.
Analysis of User Satisfaction Levels for X Mobile Application in Pekanbaru using End-User Computing Satisfaction (EUCS) and Technology Acceptance Model (TAM) Methods Butar Butar, Febiola Siska; Zarnelly, Zarnelly; Jazman, Muhammad; Novita, Rice; 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.v14i1.4851

Abstract

Mobile X is a digital innovation in banking transactions, combining mobile banking, internet banking, and e-money functions into a single platform. However, Mobile X faces several usage challenges that lead to user dissatisfaction. Therefore, an analysis of user satisfaction is essential to improve customer loyalty. The End-User Computing Satisfaction (EUCS) and Technology Acceptance Model (TAM) methods are evaluation tools used to measure user satisfaction with an application system. This study employed a quantitative approach by distributing questionnaires to 100 respondents, determined using the Lameshow equation. The research model was analyzed through demographic analysis and model analysis using PLS-SEM, resulting in both internal and external models. The findings revealed that three hypotheses were accepted: the content variable (p-value = 0.495), the perceived usefulness variable (p-value = 0.007), and the timeliness variable (p-value = 0.001). Meanwhile, three hypotheses were rejected: the accuracy variable (p-value = 0.734), the content variable (p-value = 0.495), and the format variable (p-value = 0.184). Additionally, three user satisfaction factors were found to be significant for the accepted variables, indicating that meeting user expectations, perceived usefulness, information quality, and timeliness positively contribute to user satisfaction. This demonstrates that these factors effectively address user needs and enhance overall satisfaction with the Mobile X application.
Implementation of Face Recognition, Attendance Detection, and Geolocation using TensorFlow Lite and Google ML Kit in a Mobile Attendance Application Ahmad, Fajar Abdillah; Pratiwi, Nunik
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.v14i1.4775

Abstract

Attendance applications are increasingly needed across various sectors, including education, government, and offices. However, challenges such as identity fraud and location manipulation remain unresolved. This study aims to develop a mobile attendance system that integrates face recognition, liveness detection, geolocation, and permission features, along with push notifications via user email. Additional features such as profile updates and attendance history are also included in the mobile application in real-time. The system ensures valid attendance by utilizing TensorFlow Lite for real-time face recognition and liveness detection, and Google ML Kit to enable geolocation features for user location verification. The Waterfall method was employed in this study, covering analysis, design, implementation, testing, and finalization phases. The results of this study demonstrate the ease and convenience of using the attendance system, with successful integration of face recognition, liveness detection, and geolocation into the mobile attendance application.
Indonesian Political Party Website Portal Evaluation Rank based on Manual and Automated Usability Score Abdillah, Rosyid; Riski, Raulia; Asfari, Ully
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.v14i1.4441

Abstract

As Indonesia approaches a crucial election year in 2024, the digital engagement of political parties website plays a significant role in shaping the government's future direction. This study evaluates the usability of 17 official political party websites using both manual expert assessments and automated tools, providing insights and recommendations for improving their digital presence on basic layer of information. Based on the study of 17 political party websites in Indonesia, manual usability testing by experts showed an average agreement rate of 80%, with layout receiving the lowest score of 70%. Automated usability testing revealed that 5.9% of the websites received a grade B, 17.6% grade C, 41.2% grade D, 23.5% grade E, and 11.8% grade F, resulting in a comprehensive ranking from two different perspectives.
The Moving Average Algorithm for Forecasting Palm Oil Fresh Fruit Bunch (FFB) Prices Siregar, Zaid Ubay; Santoso, Heri
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.v14i1.4977

Abstract

Fresh Fruit Bunches (FFB) of oil palm are the main raw material in the production of Crude Palm Oil (CPO). Efforts to forecast FFB prices are crucial to help mitigate the negative impacts of price fluctuations, which are influenced by various external and internal factors. The problem addressed in this study is the fluctuation in FFB prices, which presents a major challenge for both farmers and stakeholders in the palm oil industry. The method used in this research is a quantitative approach with descriptive methods, applying the Moving Average algorithm. The results of the study show that the Moving Average algorithm is used to forecast FFB prices by calculating the average price over a specific time period. The accuracy of the forecast is evaluated using several metrics: first, the Root Mean Squared Error (RMSE) with a value of 137.19, indicating moderate forecasting error; second, the Mean Absolute Percentage Error (MAPE) with a value of 6.09%, indicating good accuracy; and third, the Mean Absolute Error (MAE) with a value of 117.0, indicating relatively small errors. The accuracy system is derived by comparing the forecasts with actual data and calculating metrics such as RMSE, MAPE, and MAE. These metrics help assess the accuracy of the FFB price forecasting model and allow for adjustments to improve forecasting results.
Classification using Convolutional Neural Network Algorithms for Pest Detection in Water Spinach Hikmianto, Riki; Utami, Ema
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.v14i1.4871

Abstract

This study examines the application of Convolutional Neural Network (CNN) algorithms in detecting pests on water spinach plants using two CNN architectures: MobileNetV2 and VGG16. Monitoring diseased leaves during the plant growth phase is a critical step, and AI-based solutions are essential to enhance the accuracy of automated pest detection. In this research, a dataset of water spinach leaf images, both pest-infected and healthy, was collected to train the two CNN architectures. MobileNetV2 was selected for its ability to deliver high performance with low computational complexity, while VGG16 was used as a benchmark due to its deeper architecture and widespread use in various image recognition tasks. The testing results indicate that MobileNetV2 achieved a detection accuracy of 84%, while VGG16 yielded an accuracy of 83%. Thus, MobileNetV2 is considered superior for this pest detection application as it provides a balance between high accuracy and optimal computational efficiency. The study concludes that MobileNetV2 is a more suitable architecture for pest detection systems in water spinach plants, particularly for applications requiring high performance on resource-constrained devices.
Integrating K-Means Clustering and K-Nearest Neighbor Classification for Effective Scholarship Recipient Selection Daulay, Suandi; Wandri, Rizky
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.v14i1.4818

Abstract

This research is important because public interest in the KIP Kuliah Scholarship continues to increase. However, many educational institutions still use manual selection which is prone to bias and less effective in data management. Therefore, a method is required to make the selection process more efficient; the K-Means and K-Nearest Neighbor methods are two data processing methods that have been proven effective in various applications, including in the field of data processing. In this study, the K-Means and K-Nearest Neighbor methods are used to select scholarship recipients to increase efficiency in the process. Based on the processing carried out, there were 1257 participants who were then grouped into three clusters: Cluster 0 with 739 data points, Cluster 1 with 290 data points, and Cluster 2 with 228 data points. Testing using the K-Nearest Neighbor algorithm was carried out by evaluating the appropriate k values, specifically 27, 31, 35, 41, 45, and expanded to 185 to obtain the optimal value, namely K-155 and produced as many as 155 people who were deemed worthy and qualified according to the specified criteria. The combination of K-Means and K-NN algorithms resulted in an accuracy of 89.72% accomplished in 16 seconds. This combo can recognize data with excellent accuracy in a fast time while minimizing errors. The test results suggest that this technique is effective in selecting applicants based on the criteria and quotas established, thus it can be used as a guideline for future selection.

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