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Jurnal Teknologi Informasi dan Multimedia
Published by Puslitbang Sekawan Institute Nusa Tenggara
ISSN : 27152529     EISSN : 26849151     DOI : https://doi.org/10.35746/jtim.v2i1
Core Subject : Science,
Computer Science & IT
Cakupan dan ruang lingkup JTIM terdiri dari Databases System, Data Mining/Web Mining, Datawarehouse, Artificial Integelence, Business Integelence, Cloud & Grid Computing, Decision Support System, Human Computer & Interaction, Mobile Computing & Application, E-System, Machine Learning, Deep Learning, Information Retrievel (IR), Computer Network & Security, Multimedia System, Sistem Informasi, Sistem Informasi Geografis (GIS), Sistem Informasi Akuntansi, Database Security, Network Security, Fuzzy Logic, Expert System, Image Processing, Computer Graphic, Computer Vision, Semantic Web, Animation dan lainnya yang serumpun dengan Teknologi Informasi dan Multimedia.
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Articles 296 Documents
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Wavelet-Based MFCC and CNN Framework for Automatic Detection of Cleft Speech Disorders Muhammad Hilmy Herdiansyah; Syahroni Hidayat; Nur Iksan
Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 3 (2025): August
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i3.780

Abstract

Cleft Lip and Palate (CLP) is a congenital condition that often results in atypical speech articulation, making automatic recognition of CLP speech a challenging task. This study proposes a deep learning-based classification system using Convolutional Neural Networks (CNN) and Wavelet-MFCC features to distinguish speech patterns produced by CLP individuals. Specifically, we investigate the use of two wavelet families Reverse Biorthogonal (rbio1.1) and Biorthogonal (bior1.1)—with three decomposition strategies: single-level (L1), two-level (L2), and a combined level (L1+2). Speech data were collected from 10 CLP patients, each pronouncing nine selected Indonesian words ten times, resulting in 900 utterances. The audio signals were processed using wavelet-based decomposition followed by Mel-Frequency Cepstral Coefficients (MFCC) extraction to generate time-frequency representations of speech. The resulting features were input into a CNN model and evaluated using 5-fold cross-validation. Experimental results show that the combined L1+2 decomposition yields the highest classification accuracy (92.73%), sensitivity (92.97%), and specificity (99.04%). Additionally, certain words such as “selam”, “kapak”, “baju”, “muka”, and “abu” consistently achieved recall scores above 0.94, while “lampu” and “lembab” proved more difficult to classify. The findings demonstrate that integrating multi-level wavelet decomposition with CNN significantly improves the recognition of pathological speech and offers promising potential for clinical diagnostic support.
Rancang Bangun Sistem Satu Data sebagai Strategi Peningkatan Mutu Pendidikan Tinggi di Universitas Mataram Mohammad Zaenuddin Hamidi; Ahmad Zafrullah Mardiansyah; I Wayan Sudiarta; Halil Akhyar
Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 3 (2025): August
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i3.781

Abstract

The quality of higher education greatly depends on the accuracy and consistency of data used in decision making and accreditation processes. At the University of Mataram, various information systems have been developed separately, such as the Academic Information System (SIA), the New Student Admission System (PMB), the Research and Community Service Information System (SIMLITABMAS), and the Lecturer Performance Information System (BKD). However, the lack of integration among these systems has resulted in fragmented data, which is often unsynchronized and complicated the quality reporting process. This study aims to design and develop an integrated information system based on the One Data approach, which consolidates various primary data sources into a centralized platform within the University of Mataram. The advantages of the developed system lie in its direct integration with PDDIKTI, enabling automated data retrieval and submission through the national central system. This research adopts a Research and Development (R&D) approach with a Waterfall based software development method, consisting of the stages of requirement analysis, system design, implementation, testing, and evaluation. The results show that the developed system is able to integrate data from various existing systems and presenting it in a consistent format that is easily accessible by relevant units, with testing results achieving a 100% success rate. The system has been proven to support efficiency in reporting and monitoring processes for higher education quality in a more accurate manner. In conclusion, the One Data system contributes significantly to improve the quality of data governance and quality assurance processes in higher education and can serve as a foundation for the development of a more holistic and sustainable academic data ecosystem.
Optimizing Inter-Site Traffic Comparative Performance Analy-sis of IPSec with IKEv2 RSA-ESP and IKEv2 with PSK Surya Pratama; Mohammad Ramaddan Julianti; Detin Sofia
Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 3 (2025): August
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i3.788

Abstract

This study compares the performance of IPsec VPNs using Internet Key Exchange version 2 (IKEv2) with RSA and Pre-Shared Key (PSK) authentication. The research is driven by the rising need for secure and efficient communication in distributed systems, particularly in environments with limited resources and sensitivity to latency. Guided by the PPDIOO framework, this study assesses system performance across two distinct scenarios: standard operational conditions and impaired (stressed) network environments. Key metrics include latency, jitter, throughput, packet loss, and IKE negotiation time, measured using iperf3, ping, and tc netem. The testbed uses virtual Ubuntu environments with strongSwan 5.9.13 on VMware® Workstation, simulating inter-site traffic VPNs. Under normal conditions, PSK outperforms RSA by showing lower latency (0.82 ms vs. 0.88 ms), faster IKE setup (10.05 ms vs. 20.80 ms), and higher UDP throughput. Under stressed conditions—100 ms latency, 20 ms jitter, and 1% packet loss—PSK remains more resilient, especially for real-time UDP traffic. RSA offers steady performance for TCP downloads. Statistical significance is confirmed using paired t-tests. The results suggest PSK suits lightweight deployments with minimal cryptographic demands, while RSA is better for environments requiring certificate-based security. This study provides valuable insights for network architects in selecting appropriate IPsec configurations based on specific operational requirements. Future research may explore scalability considerations, multi-user environments, and the integration with Software-Defined Wide Area Networking (SD-WAN) technologies.
Analisis Prediksi Penjualan Isi Ulang Air Galon menggunakan Metode LSTM dan SARIMA Ulfarida Miftakhul Jannah; Nurmalitasari Nurmalitasari; Ridwan Dwi Irawan
Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 3 (2025): August
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i3.802

Abstract

Refillable drinking water depots often face challenges in dealing with unpredictable customer demand on a daily basis. This uncertainty complicates the process of stock management, production planning, and overall operations. Without accurate sales forecasts, depots risk losing potential sales and experiencing a decline in service quality to customers. Therefore, a solution is needed that can accurately predict daily sales. The first step in this research is to collect relevant data. Once the data is available, pre-processing is conducted to prepare the data before entering the modeling process. The Long Short-Term Memory (LSTM) model has the advantage of remembering historical patterns in time series data. Meanwhile, the Seasonal Autoregressive Integrated Moving Average (SARIMA) model is an extension of ARIMA that can handle data with seasonal characteristics. In this study, the LSTM model demonstrated better performance than SARIMA. This is evidenced by the performance evaluation values: MAPE of 9.54%, RMSE of 0.17, and MAE of 0.14 for the LSTM model, which are lower than MAPE of 10.51%, RMSE of 0.19, and MAE of 0.16 for SARIMA. These values indicate that LSTM is capable of providing more accurate prediction results. Based on these results, it can be concluded that the LSTM model is more effective and recommended for use in predicting daily sales of refillable water at the Manshurin Water depot
Implementasi Augmented Reality Sebagai Media Pembelajaran Untuk Pengenalan Buah-Buahan Rahman Nur Syam; Sigit Sugiyanto; Tito Pinandita; Feri Wibowo
Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 3 (2025): August
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i3.805

Abstract

Innovative and interactive teaching strategies have emerged as a result of the development of communication and information technology. One of the most promising and rapidly expanding educational technologies is augmented reality. By displaying virtual things in three dimensions in a real-world setting in real time, Augmented Reality can make studying more engaging and joyful for students Augmented reality can display virtual objects in three dimensions in real time, creating a more engaging and enjoyable learning experience for students. This research aims to develop and implement Augmented Reality-based fruit recognition learning media as an alternative to conventional, static and unengaging media for elementary school students, helping them visualize the concepts being learned. The Multimedia Development Life Cycle (MDLC), which has six stages concept, design, gathering materials, assembly, testing, and distribution the development methodology. This application is designed to display various types of fruit as 3D objects that can be scanned through markers using the camera on an android device. Each fruit is equipped with its own name and information to improve student knowledge. Testing is carried out through black box testing to evaluate system functions, and user feasibility testing using a Likert scale questionnaire given to 15 grade students. According to the results of black-box testing, there were no system or functional issues and the application operated as planned. It received an 84.86% feasibility score, placing it in the "very feasible" range. Thus, it can be said that this AR-based fruit recognition app works well to boost students' curiosity, involvement, and comprehension of the material.
Penerapan Web Content Accessibility Guidelines dan Design Thinking dalam Perancangan UI/UX Aplikasi Ujian Online Henim, Silvana Rasio; Hidayat, Erzi; Saf, Maksum Ro'is Adin
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 1 (2026): February
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i1.701

Abstract

The most significant change in education due to the pandemic is the implementation of online evaluation methods. Online exams provide students with the flexibility to take tests from any lo-cation. Although online examinations offer flexibility for learners to participate from any loca-tion, their implementation still faces various challenges, such as the potential for cheating, tech-nical disruptions, and limited accessibility for users with diverse physical conditions and digital competencies. These issues highlight the need for designing online examination interfaces that are not only easy to use but also inclusive. This study aims to design the user interface and user expe-rience by employing the design thinking approach and applying the Web Content Accessibility Guidelines (WCAG) to enhance interface accessibility starting from the design phase. The WCAG 2.0 standard, developed by the W3C, is applied as a guideline for meeting accessibility require-ments. The WCAG principles implemented include perceivability, operability, understandability, and robustness. Usability testing on the prototype was conducted using the System Usability Scale (SUS), scoring 69. This score indicates that the designed prototype falls into the "marginal high" category within the acceptability range. Accessibility testing using Axe for Designers indi-cated that, overall, the prototype met accessibility requirements. The results also show that inte-grating WCAG 2.0 principles during the design stage effectively enhances the accessibility of the user interface.
Analisis Kesiapan Pengguna di Indonesia dalam Adopsi Teknologi Blockchain Pada Platform Pertukaran Kripto Menggunakan TRI Nurjanah, Sri Putri; Herliana, Asti
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 1 (2026): February
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i1.803

Abstract

The use of blockchain technology on cryptocurrency exchange platforms in Indonesia has experi-enced notable growth, yet challenges persist concerning user preparedness and preferences be-tween domestic and international platforms. This research seeks to explore the factors influencing users’ selection of crypto platforms and to evaluate the technological readiness of Indonesian us-ers by integrating the Technology Readiness Index (TRI) with an information technology adop-tion framework. The study employed purposive sampling to gather data from 156 active crypto platform users. Quantitative data analysis was performed using PLS-SEM through SmartPLS version 4.0. Findings indicate that the majority of respondents are young adults aged 17 to 25, predominantly male, and show a preference for international platforms due to their innovative capabilities, greater liquidity, and lower transaction fees. Nonetheless, local platforms remain attractive because of easier accessibility and enhanced regulatory backing. Structural model re-sults demonstrate that optimism, innovativeness, and insecurity significantly influence user readiness, whereas discomfort does not have a meaningful impact. Moreover, user readiness stands out as a critical factor strongly facilitating blockchain technology adoption on crypto ex-changes. This study validates the combined application of the TRI and IT adoption models as ef-fective tools for pinpointing key determinants of blockchain adoption readiness, offering strategic insights for developers of local platforms and serving as a foundation for future research on blockchain implementation in Indonesia.
Implementasi Model Machine Learning untuk Deteksi Phishing dengan Pendekatan Ekstraksi Fitur yang Dioptimalkan Pradana, Adam; Susanto, Susanto
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 1 (2026): February
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i1.881

Abstract

Phishing is a common form of cybercrime used by digital criminals to steal sensitive information such as passwords, personal data, and financial details through fake websites designed to re-semble legitimate pages. However, conventional detection methods such as blacklists and manual inspection are currently considered ineffective due to their static nature, often failing to recognize new, evolving and increasingly sophisticated attack patterns. To address this issue, this study developed a machine learning-based phishing detection model focused on improving the accura-cy and efficiency of identifying malicious sites. This model applies an optimized feature extrac-tion technique to enable the system to analyze URL characteristic patterns more comprehensively and targeted. The research dataset was taken from the Kaggle platform, which provides a dataset of phishing and benign URLs with a high reputation. The data was then processed through nor-malization, cleaning, and extraction of important features such as URL structure and domain at-tributes. The classification process was carried out using an ensemble learning approach that combines four popular algorithms: Random Forest, Gradient Boosting, Logistic Regression, and AdaBoost through a soft voting mechanism. The evaluation results show that the proposed model has excellent performance with an accuracy of 98.10%, a precision of 97.81%, a recall of 93.90%, an F1-Score of 95.82%, and a ROC-AUC of 98.62%. These findings confirm that the ensemble ap-proach with optimized features has great potential for application in artificial intelligence-based cybersecurity systems capable of adaptive and real-time phishing detection.
Perancangan Enterprise Architecture Aplikasi Manage Personal Finance dengan Framework TOGAF dan PEAF Siahaan, Mangapul; Yulsen, Yulsen; Firmansyah, Muhammad Dody
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 1 (2026): February
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i1.889

Abstract

The development of information technology encourages the use of the Manage Personal Finance application as a more systematic and data-driven financial management tool. However, in prac-tice, the application still faces various problems, such as an unintegrated financial recording pro-cess, limited system architecture documentation, and the absence of an enterprise architecture framework that best suits business needs and long-term development. These problems have the potential to cause the system to be out of alignment with the organization's strategic objectives and difficult to develop sustainably. This study aims to: (1) design an enterprise architecture for the Manage Personal Finance application using the TOGAF ADM 9.2 framework; (2) produce an integrated business, data, application, and technology architecture blueprint; and (3) compare the effectiveness of the TOGAF and PEAF frameworks quantitatively based on five indicators, namely alignment with business needs, completeness of documentation, implementation speed, scalability, and resource requirements. The research method used is the design of an enterprise architecture based on TOGAF ADM, followed by a comparative analysis of the PEAF framework as an alternative, more pragmatic approach. The results of the study indicate that TOGAF excels in 3 out of 5 indicators (60%), namely business needs alignment, completeness of documentation, and system scalability, while PEAF excels in 2 indicators (40%), namely speed of implementation and resource efficiency. These findings indicate that TOGAF is more suitable for the development of Manage Personal Finance applications that have high complexity and long-term orientation. Thus, this study provides an empirical contribution in selecting the optimal enterprise architec-ture framework for the development of integrated and sustainable financial systems.
Perancangan dan Implementasi Sistem Pengelolaan Order Barang Berbasis Web dengan Laravel Anggraini, Nabela Yulian; Susanto, Susanto
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 1 (2026): February
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i1.890

Abstract

CV. Surya Sarana Dinamika currently faces significant operational inefficiencies due to its man-ual, paper-based order management process. These challenges lead to frequent data recording errors, substantial delays in information flow, and a critical lack of real-time visibility regarding order status, which ultimately hinders effective administrative decision-making. This study aims to address these systemic issues by designing and implementing a web-based order management system utilizing the Laravel Framework. The system was developed using the Agile Development methodology, employing iterative cycles to ensure that the final product remains aligned with dynamic business requirements. The architecture is built upon the Model-View-Controller (MVC) pattern to ensure code scalability and long-term maintenance ease. Functional validation via Black-Box testing confirms that all core features, including order submission and purchasing validation, operate according to specifications. Quantitatively, the implementation resulted in a drastic efficiency increase; the average time for order submission decreased from 20-25 minutes to just 3-5 minutes (an efficiency gain of over 75%), while purchasing validation time was re-duced from 30-60 minutes to 5-10 minutes. These findings demonstrate that digital automation effectively eliminates manual bottlenecks and reduces the risk of human error. By providing cen-tralized data and real-time tracking, the system significantly enhances accountability and trans-parency within the company’s supply chain, providing a replicable model for digital transfor-mation in similar organizational contexts..

Page 28 of 30 | Total Record : 296

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