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SMART : Jurnal Teknologi Informasi dan Komputer
Published by Gayaku Publisher
ISSN : -     EISSN : 29636388     DOI : https://doi.org/10.58222/sj.v1i1.818
Core Subject : Science, Education, Engineering,
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science
SMART Jurnal Teknologi Informasi dan Komputer or SMART Journal of Information Technology and Computer Science is published by Gayaku Publisher. SMART publishes research papers in the fields of Information Technology and Computer Science. SMART is committed to publishing high quality articles in Indonesian and English that can serve as key references for researchers in the fields of Information Technology and Computer Science. The scope of this journal encompasses to study of Computer Science, Information Technology, Digital Media, Information System, Knowledge Management, System Management, Data Mining, Internet Of Things IOT, Artificial Intelligence AI, Robotic, Computer Networks, Cyber Security. The scope of SMART Journal of Information Technology and Computer Science is as follows: Domain Specific Frameworks and Applications IT Management dan IT Governance eGovernment eHealthcare, eLearning, eManufacturing, eCommerce ERP dan Supply Chain Management Business Process Management Smart Systems Smart City Smart Cloud Technology Smart Appliances and Wearable Computing Devices Robotic Systems Smart Sensor Networks Information Infrastructure for Smart Living Spaces Intelligent Transportation Systems Models, Methods and Techniques Conceptual Modeling, Languages and design Software Engineering Information centric Networking Human Computer Interaction Media, Game and Mobile Technologies Data Mining Information Retrievel Information Security Image Processing and Pattern Recognition Remote Sensing Natural Language Processing
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 47 Documents
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Design and Build an Android-Based Student Attendance System Using LBS and Qrcode at IAIN Salatiga Maulana Ayub Dwi Saputra
SMART : Jurnal Teknologi Informasi dan Komputer Vol. 1 No. 2 (2022): July-December
Publisher : Gayaku Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58222/c14ex554

Abstract

IAIN Salatiga as an educational institution continues to strive to make improvements where there are still processes that are carried out manually which can be improved with a touch of existing technology. One of the activities that can be improved from this learning process is the student attendance and attendance process, which previously was still carried out manually using How to provide an attendance list signed by the student, then the data is entered into the IAIN Salatiga academic information system application by manual input into the system. This process has several problems, firstly, attendance data is invalid, the second problem is that lecturers often forget to verify the attendance list that has been signed by students, attendance data stored in the database does not display the actual data in real time and sometimes there are courses that are not recorded in the database. teaching journal. The technological media chosen in this research are Android-based mobile devices, LBS and QR Code. The system developed is integrated with IAIN Salatiga's SI-Mona and SIAKAD applications so that lecturer teaching journal data, lecture evidence and student attendance lists become one undivided data unit
Image Optimization of Ancient Arabic Manuscripts with a Combination of Image Enhancement and Sharpening Hanifatus S. Widihasaniputri; Wahju Tjahjo Saputro; Dewi Chirzah
SMART : Jurnal Teknologi Informasi dan Komputer Vol. 4 No. 1 (2025): January-June
Publisher : Gayaku Publisher

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

Abstract

Ancient manuscripts are rare collections owned by every nation in theworld. The contents of a written text or document often also provideinformation on aspects of the nation's culture of the community concerned.Various efforts have been made to conserve these cultural objects, such asdigitizing manuscripts into digital images. This study aims to improve theimage of the ancient Arabic script using image enhancement and sharpeningmethods. The image enhancement used in this study is the gamma methodand the log transformation method combined using the sharpening method.The results showed that the sharpening method could improve the legibilityof an ancient manuscript.
Analisis Pemanfaatan Teknologi Informasi dalam Meningkatkan Kualitas Pendidikan di Era Digital Lela Budiarti; Alwendi; Andi Saputra Mandopa
SMART : Jurnal Teknologi Informasi dan Komputer Vol. 4 No. 2 (2025): July - December
Publisher : Gayaku Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58222/70pwb198

Abstract

Digital innovation is an important aspect in improving educational performance in the era of ever-evolving technology. This study aims to explore the impact of implementing a digital-based management system in improving school operational efficiency and the quality of education. The focus of the problem in this study is how the implementation of technology can improve various managerial aspects in the world of education, including administrative management, learning processes, and communication between educators, students, and parents. The use of Information Technology in education has become a key factor in improving the quality of learning in the digital era. This study aims to analyze how the application of ICT contributes to improving the quality of education, both in terms of learning methods, access to information, and the effectiveness of interactions between educators and students. The research methods used are literature studies and qualitative analysis of various ICT implementations in formal and non-formal education environments. The results of the study show that the use of ICT, such as e-learning platforms, digital learning applications, and educational social media, can enrich the learning process, increase learning motivation, and expand the reach of education to previously difficult-to-reach areas. However, challenges such as the digital divide, lack of teacher training, and limited infrastructure still need serious attention. Thus, optimal and sustainable ICT integration is needed to support the achievement of quality education in the digital era.
Design of an Information System for Quantitative and Qualitative Analysis of Patient Medical Records at Puskesmas XYZ Andes Nanda Pratama
SMART : Jurnal Teknologi Informasi dan Komputer Vol. 4 No. 1 (2025): January-June
Publisher : Gayaku Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58222/q4rx5259

Abstract

The quantitative and qualitative analysis of medical records is a critical component of medical record management that ensures the completeness, accuracy, and consistency of patient health data in primary healthcare facilities. However, this process at Puskesmas XYZ is still conducted manually using paper forms, resulting in slow processing times, high risk of error, and difficulty in compiling aggregate reports. This research designs a web-based information system for quantitative and qualitative analysis of patient medical records using the Systems Development Life Cycle (SDLC) method with the Waterfall model. The system is built using the PHP CodeIgniter 4 framework, MySQL database, and a Bootstrap-based interface. The quantitative analysis module covers four review components: identification, authentication, recording, and reporting. The qualitative analysis module covers two components: consistency diagnosis and recording procedures. System evaluation was conducted using the ISO 25010 quality standard covering six characteristics: functional suitability, performance efficiency, usability, reliability, security, and maintainability. Testing results show an overall system quality score of 83.7% (Very Good category). The system successfully reduces medical record analysis time by 67.4% compared to manual methods and increases the completeness rate of medical record documentation from 71.3% to 94.8%. The novelty of this research lies in the integration of an automated completeness checklist module with a real-time incomplete medical record (IMR) tracking dashboard, which has not previously been developed specifically for the primary healthcare (Puskesmas) context in Indonesia.
Implementation of a Finite State Machine for Character Animation Transitions in Unity-Based 3D Games Muhammad Fairul Filza; Ahmad Zaid Rahman; Nadea Cipta Laksmita; Haryoko; Jedidta Adoni Saputra
SMART : Jurnal Teknologi Informasi dan Komputer Vol. 4 No. 2 (2025): July - December
Publisher : Gayaku Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58222/sj.v4i2.1808

Abstract

A responsive character animation system with smooth transitions is a crucial factor in creating a high-quality and immersive gameplay experience. A common issue that frequently arises is animation that appears rigid or unnatural when a character switches from one action to another. This study aims to implement a Finite State Machine (FSM) to manage player character animation transitions in the game Legacy of the Sunstone. The method employed is a Hierarchical Finite State Machine (HFSM) with Moore Machine characteristics, in which the output in the form of animation is determined by the currently active state at a given time. The implementation was carried out using the Unity Engine and applied the State Pattern to establish a structured, modular, and maintainable code architecture. The CrossFadeInFixedTime technique was utilized to achieve smooth animation blending between states with configurable transition durations. The developed FSM system consists of two main categories: Locomotion states, including Idle, Movement, Jump, Falling, and Crouch, and Combat states, including Aim, Melee, and Takedown. System testing can be conducted using Black Box Testing through an iterative approach across 13 test scenarios that cover all functional requirements of the system.
Pemanfaatan ChatGPT AI pada Proses Pembelajaran Siswa di SMA X Kota Y Agus Wagito
SMART : Jurnal Teknologi Informasi dan Komputer Vol. 4 No. 2 (2025): July - December
Publisher : Gayaku Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58222/rcg8pq32

Abstract

The rapid advancement of artificial intelligence (AI) technology, particularly ChatGPT developed by OpenAI, has opened new opportunities in the education sector. However, studies specifically examining how senior high school students in Indonesia use ChatGPT in their learning processes remain limited. This study aims to: (1) analyze patterns of ChatGPT use among students of SMA X, City Y; (2) evaluate the impact of ChatGPT use on learning outcomes from the student perspective; (3) identify the dimensions of use (Accessibility, Usefulness, Ease of Use, Academic Integrity, and Learning Motivation) that receive the highest and lowest assessments; and (4) formulate targeted recommendations for the integration of ChatGPT in high school learning. The research employed a descriptive quantitative approach with a cross-sectional design. Respondents consisted of 120 students actively enrolled in SMA X selected through proportional stratified random sampling. Data were collected via a structured questionnaire covering five dimensions. The User Satisfaction Index (USI) showed an overall score of 74.2% (Good category). The Usefulness dimension obtained the highest score (77.5%), while Academic Integrity received the lowest (64.8%). Gap analysis revealed the largest negative gap in Academic Integrity (gap score: −0.89), indicating this dimension as the most critical area requiring intervention. The novelty of this study lies in its application of five-dimensional gap analysis specifically adapted for AI-based technology use in the secondary school educational context, providing a more actionable diagnostic framework compared to single-score satisfaction surveys previously used in similar studies.
Implementation of Machine Learning-Based Artificial Intelligence for Performance Prediction and Analysis of Information Systems in Modern Computing Environments Adi Ikbal Rahman; Sobarrokah; Erri hardiana
SMART : Jurnal Teknologi Informasi dan Komputer Vol. 4 No. 2 (2025): July - December
Publisher : Gayaku Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58222/6fw9nw49

Abstract

The rapid proliferation of digital information systems in modern organizations has created an urgent need for proactive performance monitoring and predictive analytics capabilities. Traditional rule-based monitoring approaches are increasingly inadequate in addressing the dynamic, high-dimensional nature of modern computing environments comprising cloud infrastructure, microservices architectures, and distributed databases. This study proposes and evaluates a machine learning (ML)-based framework for predicting and analyzing information system performance metrics in modern computing environments. The framework integrates five supervised and unsupervised ML algorithms — Random Forest (RF), Extreme Gradient Boosting (XGBoost), Long Short-Term Memory (LSTM), Support Vector Machine (SVM), and Isolation Forest — applied to a multi-dimensional dataset of system performance telemetry collected from a heterogeneous IT infrastructure over a 12-month period. The dataset encompasses 14 performance indicators including CPU utilization, memory usage, network throughput, query response time, and application error rates. Experimental results demonstrated that the XGBoost model achieved the highest predictive accuracy (R² = 0.942, RMSE = 2.31%) for CPU load forecasting, while the LSTM network outperformed other models for sequential anomaly detection with F1-score of 0.961. The ensemble approach combining RF and XGBoost reduced false positive rates in performance degradation alerts by 34.7% compared to single-model baselines. The novelty of this research lies in the integration of a hybrid ensemble architecture with SHAP (SHapley Additive exPlanations)-based interpretability analysis, enabling actionable root-cause identification beyond binary anomaly detection — addressing a critical gap in existing AI-based IT performance management solutions.

Page 5 of 5 | Total Record : 47

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