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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 13, No 6 (2024): Sistemasi: Jurnal Sistem Informasi" : 40 Documents clear
Augmented Reality based Gamified Mandarin Learning Application Adam, Steffi; Marfuah, Marfuah; Afifah, Ummul Fitri; Abdullah, Abdullah
Sistemasi: Jurnal Sistem Informasi Vol 13, No 6 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Most Chinese-heritage parents will teach their children Mandarin as early as possible. Parents will do various things such as providing additional Mandarin tutoring or enrolling their children in schools that teach Mandarin. Unfortunately, many children become bored and unwilling to learn Mandarin because Mandarin has a complex language structure, starting from writing, pronunciation, and grammar. This study aims to develop a Mandarin language learning application based on augmented reality that incorporates gamification elements to increase children's learning motivation. The development method used is waterfall. The results of this study show that with the existence of a gamified Mandarin language learning application based on augmented reality, Mandarin learning becomes more tangible, thus it is expected to facilitate increasing children's motivation to learn Mandarin.
Analysis of Mobile JKN Application Service Quality With E-GovQual Method and IPA Ananda, Randy Rizki; Hapsari, Indriani Noor
Sistemasi: Jurnal Sistem Informasi Vol 13, No 6 (2024): 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.v13i6.4537

Abstract

This study aims to evaluate the quality of Mobile JKN application services using 6 dimensions of E-GovQual, and provide recommendations for improving service quality based on the results of Importance Performance Analysis (IPA) analysis. This research uses a quantitative descriptive method. Questionnaires were distributed by visiting BPJS Kesehatan Tigaraksa Branch Office and Metro Hospitals Cikupa. Then, 110 respondents were obtained who had filled out the questionnaire online via Google Forms and were included in the category of Mobile JKN application users. The questionnaire instrument test was conducted on 55 respondents to test its validity and reliability. Data processing was carried out by conducting descriptive statistical tests, R-Square tests, hypothesis tests (significant), as well as gap analysis (GAP) and Importance Performance Analysis (IPA) quadrants. The results of the coefficient of determination (R-Square) show that overall, the variables of ease of use, reliability, trust, content and appearance, functionality and interaction and citizen support significantly affect service quality by 88.6%. Based on the performance gap value (GAP) and assessment expectations of -0.19, there is a main priority scale in quadrant A to make improvements, namely on the information displayed in the Mobile JKN application is precise and detailed (EF 4), all features in the Mobile JKN application function properly (FI 1), the Mobile JKN application has displayed all the information needed by users (CA 1), information about the scope of health and information has provided clarity (CA 2), the accuracy of the summary of information data and graphics and colors in the system (CA 5), and BPJS Kesehatan staff show a responsive attitude in solving my problem (CS 1). These recommendations are top priorities for improving the service quality of the Mobile JKN application.
Audit of Information Tecnology Governance at BKKBN Riau Province using the 2019 Cobit Framework Fandi, Ridho Arif; Jazman, Muhammad; Fronita, Mona; Saputra, Eki
Sistemasi: Jurnal Sistem Informasi Vol 13, No 6 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

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Abstract

The implementation of Information Technology in government agencies has been used to enhance management processes and productivity, making them more accurate and faster, which leads to an improvement in the organization's ability to achieve Governance Management Objectives (GMO) and Good Corporate Governance. The BKKBN of Riau Province has implemented Information Technology in its execution in the form of SIGA (Sistem Informasi Keluarga) and Srikandi (Sistem Informasi Kearsipan Dinamis Terintegrasi). BKKBN is a non-ministerial government agency tasked with population control through family planning and prosperous family programs. Cobit 2019 is an international standard for assessing IT governance and management within companies, which also provides solutions for improving those issues.This research aims to measure the level of organizational capability in IT implementation. The results of the analysis of the Design factor objective APO-09-Managed Service Agreements and DSS-01 Managed Operations have the highest importance value, which is 60. The measurement results for APO-09 reached 74% at capability level 3 with the status of Largely Achieved or not yet achieved, while DSS-01 reached a value of 79% at level 3, which means both process objectives are at level 2, indicating that the process activities have achieved their goals by performing a number of basic but complete activities. With these results, both process objectives require improvement based on recommendations formulated from the gap analysis to achieve the expected capability.
A Fall Risk Detection Model for Infants While Sleeping based on Convolutional Neural Networks Hendra, Acep; Supeno, Handoko
Sistemasi: Jurnal Sistem Informasi Vol 13, No 6 (2024): 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.v13i6.4644

Abstract

Falling from a bed is a common problem among infants, often leading to serious injuries such as head trauma, fractures, and even long-term neurological damage. According to data from the World Health Organization (WHO), falls are a leading cause of unintentional injuries among children, especially infants. To prevent these incidents, an effective early detection system is needed. Traditional approaches, such as motion sensors and surveillance cameras, have been employed to monitor infant movements and detect fall risks. However, sensor-based systems face limitations in terms of accuracy and coverage area. As an alternative, computer vision techniques have shown rapid advancements in recent years, with Convolutional Neural Networks (CNNs) proving to be highly effective in recognizing visual patterns, including human motion and posture detection. In this study, we propose a CNN-based model to detect the risk of infants falling from a bed while sleeping. The CNN architecture is designed to accurately recognize movements indicative of fall risks, such as approaching the edge of the bed or sudden changes in posture. Our contributions include (1) the design of a CNN architecture that supports effective and efficient training for fall risk detection, and (2) the creation of a dataset to classify infants as either safe or at risk of falling. Experimental results demonstrate that our proposed system achieves high accuracy in detecting potential fall risks, providing a reliable solution for infant safety monitoring.
Analysis of Public Sentiment on Election Results using Naïve Bayes in Social Media X Muliana, Ahmad Syakir; Lestarini, Dinda; Raflesia, Sarifah Putri
Sistemasi: Jurnal Sistem Informasi Vol 13, No 6 (2024): 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.v13i6.4592

Abstract

The objective of the research is to examine the public opinion regarding the 2024 Indonesian election results by applying Naïve Bayes to social media data obtained from platform X of Twitter. A dataset comprising 2,500 election-related tweets was obtained by web scraping and then subjected to tokenization, stopword elimination, stemming, and TF-IDF weighting for preprocessing. The application of the Synthetic Minority Oversampling Technique (SMOTE) was attempted to mitigate class imbalance. The performance of the Naïve Bayes model was assessed using Stratified K-Fold Cross-Validation. The model achieved an average accuracy of 66.90% on the test set and 80% during cross-validation. The results demonstrate successful categorization of positive sentiment, although the model encountered difficulties in precisely detection of negative and neutral sentiments. The results underscore significant consequences for policymakers and political parties in formulating effective communication strategies. Further study is advised to investigate sophisticated algorithms to improve the accuracy of sentiment classification, namely in detecting neutral sentiments.
Project Management of Information System using Scrum Framework in the Development Of Mediahome SMM Website Afriansah, Ari; Sembiring, Falentino; Ayuningsih, Rieska Rahayu; Saepudin, Sudin
Sistemasi: Jurnal Sistem Informasi Vol 13, No 6 (2024): 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.v13i6.4764

Abstract

This research aims to develop a website named Mediahome, focusing on providing social media marketing (SMM) services such as selling followers, likes, and views for social media platforms like Instagram and YouTube. The website is expected to make it easier for users to access services at more affordable prices compared to other online stores and to provide convenience for resellers in marketing their services. The Scrum framework was utilized for project development, proving effective in facilitating the iterative and structured management of tasks. During the development process, some technical issues arose, particularly related to the migration of servers from DomaiNesia to ProviderIndo. However, these issues were successfully resolved by redirecting the nameserver, allowing the website to be launched as planned. The final outcome of this project is a fully operational website accessible at https://arimediahome.xyz, ready to serve users' social media marketing needs.
Enhanced Brain Tumor Classification through Gamma Correction in Deep Learning Naufal, Muhammad; Al Azies, Harun; Brilianto, Rivaldo Mersis
Sistemasi: Jurnal Sistem Informasi Vol 13, No 6 (2024): 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.v13i6.4474

Abstract

Classification of brain tumors is a problem in computer-aided diagnosis (CAD). This study classifies three classes of brain tumors: gliomas, meningiomas, and pituitary tumors. Image enhancement is useful for improving the quality of images to be recognized by Computer-Aided Diagnosis (CAD) systems. Gamma correction is one spatial method aimed at manipulating contrast. This method operates with a spatial approach and has relatively low computational time but yields satisfactory results in certain cases. This research compares Gamma Correction with Convolutional Neural Network (CNN) in the classification of brain tumor types. The CNN method without Gamma Correction achieves an accuracy of 86.52%, precision of 83.63%, sensitivity of 86.11%, and specificity of 93.27%. The application of Gamma Correction at 1.5 results in improved performance with an accuracy of 88.80%, precision of 86.49%, sensitivity of 88.06%, and specificity of 94.50%. Meanwhile, Gamma Correction at 0.5 shows an accuracy of 88.59%, precision of 87.59%, sensitivity of 86.68%, and specificity of 94.17%. Overall, the implementation of Gamma Correction in the classification of brain tumor types successfully enhances the CNN classification performance in terms of precision, sensitivity, and specificity compared to without its use.
Performance Comparison of IoT Classification Models using Ensemble Stacking and Feature Importance setiawan, nabila putri; Nugraha, Adhitya; Luthfiarta, Ardytha; Mulyana, Yudha
Sistemasi: Jurnal Sistem Informasi Vol 13, No 6 (2024): 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.v13i6.4673

Abstract

Internet of Things (IoT) security is becoming a top priority as the number of connected devices increases online. This research utilizes the CIC IoT ATTACK 2023 dataset from the University of Brunswick, which consists of 46 million data on various types of attacks on IoT devices, such as DDoS, DoS, Brute Force, Spoofing, and Mirai attacks. To address the imbalance in the dataset, a random undersampling technique is applied to ensure the machine learning model is not biased towards the majority class. The ensemble learning approach was chosen due to its ability to combine the strengths of multiple algorithms, thus improving accuracy and stability in detecting complex IoT attacks. The algorithms used include gradient boosting, bagging, voting, and stacking. In particular, the stacking model, which combines the bagging classifier and gradient boosting, achieved the highest accuracy of 93%. Although the accuracy of the stacking model decreased to 92.4% after feature selection, the precision, recall, and F1-score remained high at 92.0. In addition, the computation time was also reduced from 2111.69 seconds to 1208.27 seconds. These findings indicate that ensemble learning approaches and feature selection techniques have great potential in improving IoT security, providing more reliable and efficient threat detection solutions.
Designing Attack Surface in Early Childhood Education System Environment using Risk Assessment and Enterprise Architecture Approach Setiawan, Dadang; Oktaria, Dita; Prabowo, Sidik; Indrasari, Elizabeth Sastrina
Sistemasi: Jurnal Sistem Informasi Vol 13, No 6 (2024): 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.v13i6.4623

Abstract

As digital technologies increasingly permeate the education sector, the need to safeguard sensitive personal data within early childhood education systems becomes paramount. In Indonesia, where the adoption of digital tools in education is rapidly expanding, these systems are particularly vulnerable due to the hybrid nature of their processes, varying levels of digital literacy among stakeholders, and a complex regulatory environment. This research addresses the challenge of securing Indonesia’s early childhood education systems by designing a minimized attack surface through the integration of ISO 27005-based risk assessment and the TOGAF enterprise architecture framework. ISO 27005 provides a systematic methodology for identifying, assessing, and mitigating information security risks, ensuring compliance with the Indonesian Personal Data Protection Law (UUPDP). TOGAF is utilized to structure the enterprise architecture, aligning IT strategies with institutional goals while embedding robust security measures across the digital infrastructure. The research methodology involves identifying critical assets and potential threats, evaluating these threats using ISO 27005, and developing a secure architecture tailored to the unique needs of Indonesian early childhood education systems. The proposed framework is validated through application in a case study involving several Indonesian early childhood education institutions. This approach not only enhances the security posture of these institutions but also aligns with cultural and regulatory considerations, offering a comprehensive solution for protecting vulnerable educational environments in Indonesia.
Development of Mobile-Based Learning Media Introduces Two-Dimentional Figure in Elementary Schools Praciska, Mia Tri; Hikmawan, Rizki; Widodo, Suprih
Sistemasi: Jurnal Sistem Informasi Vol 13, No 6 (2024): 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.v13i6.4539

Abstract

The use of mobile learning media can improve the quality of education by allowing students to access the learning process from home which can improve their understanding of the material. The purpose of the research is to develop mobile-based learning media introduces two-dimentional figure in elementary schools. This type of research uses R&D (Research and Development) with the ADDIE development model which includes Analyst, Design, Development, Implementation, and Evaluate. The results of the research show that mobile-based learning media introduces two-dimentional figure in elementary schools with the main features, namely material content, videos, textbooks, and student ability tests accompanied by discussion questions. The System Usability Scale (SUS) is used to evaluate the effectiveness of learning media. The research results show that the media has a high level of satisfaction, with an expert validation score of 88.33, a score of 74.09 in the one-to-one test, a score of 80.33 in small groups, a score of 99.47 in the field test. The application was also assessed as successful through black box testing. This study also found that mobile-based learning media on the introduction of two-dimentional figure can be used online or in the classroom, and the application is successful on various versions of Android.

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