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JUTIK : Jurnal Teknologi Informasi dan Komputer
Published by Universitas Dhyana Pura
ISSN : 2442241X     EISSN : 25285211     DOI : -
Core Subject : Economy, Science, Education, Social, Engineering,
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Engineering Social Sciences
Jurnal Teknologi Informasi dan Komputer berisi tulisan yang diangkat dari hasil penelitian di bidang teknologi informasi dan komputer. Jurnal ini merupakan sarana bagi peneliti di bidang ilmu teknologi informasi dan komputer untuk mempublikasikan karya-karya penelitiannya. Redaksi penyunting jurnal Teknologi Informasi dan Komputer terdiri dari dosen-dosen yang terkait bidang ilmu teknologi informasi dan komputer dalam konsentrasi antara lain : Rekayasa Perangkat Lunak, Sistem Informasi, Jaringan dan Keamanan Komputer, Pengolahan Citra, Multimedia dan Kecerdasan Buatan, dan konsentrasi lainnya terkait bidang ilmu teknologi informasi dan komputer.
Arjuna Subject : -
Articles 458 Documents
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ANALISIS ADOPTION RATE PENGGUNAAN MICROSOFT COPILOT DALAM KEGIATAN AKADEMIK MAHASISWA SURABAYA MENGGUNAKAN METODE EXTENDED TAM Achmad Naufal Ferdiansyah; Taqiyuddin Ahmad Al Aufa; Ahmad Faiq Shalahuddin Wafa
Jurnal Teknologi Informasi dan Komputer Vol. 12 No. 1 (2026): JUTIK : Jurnal Teknologi Informasi dan Komputer, Edisi April 2026
Publisher : LPPM Universitas Dhyana Pura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36002/jutik.v12i1.3968

Abstract

The advancement of artificial intelligence (AI) technology has introduced Microsoft Copilot as a supportive tool for students' academic activities. This study aims to analyze the factors influencing the adoption rate of Microsoft Copilot Bing among university students in Surabaya using the Extended Technology Acceptance Model (Extended TAM). A quantitative approach was employed through a Likert-scale questionnaire distributed to 100 purposively selected respondents. Data analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS software. The findings reveal that Attitude Toward Use Copilot serves as a central mediator that significantly affects Intention to Use Copilot. Key predictors influencing this attitude include Perceived AI Enjoyment, Usefulness, and Intelligence. However, Perceived AI Trust and Personal Competence did not show a direct significant effect on users’ attitudes. To address discriminant validity issues, a model refinement process was conducted by simplifying overlapping indicators. The results highlight the importance of enjoyable user experiences, perceived usefulness, and AI intelligence in shaping students’ intention to adopt the technology. This research provides practical implications for technology developers and educational institutions in designing strategies to integrate AI-based tools effectively in academic environments.
IMPLEMENTASI FIREWALL FILTERING PADA SITUS WEB DAN GAME ONLINE MENGGUNAKAN LAYER 7 PROTOCOLS DAN MANAJEMEN BANDWIDTH DENGAN METODE HIERARCHICAL TOKEN BUCKET Muhlis Tahir; Abdullah Bachtiar Rifai
Jurnal Teknologi Informasi dan Komputer Vol. 12 No. 1 (2026): JUTIK : Jurnal Teknologi Informasi dan Komputer, Edisi April 2026
Publisher : LPPM Universitas Dhyana Pura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36002/jutik.v12i1.3972

Abstract

The development of computer network technology has a significant impact in supporting the learning process. However, without good network management, the use of the internet can cause problems such as accessing irrelevant sites and uneven bandwidth distribution. This research aims to implement firewall filtering using Layer 7 protocols and bandwidth management using the Hierarchical token bucket (HTB) method on Mikrotik devices in the computer laboratory of SMK Negeri 3 Bangkalan. This research is included in the type of development research using the NDLC (Network Development Life Cycle) network development model. The implementation results show that the firewall successfully blocks access to inappropriate websites and online games. Based on the Quality of service (Qos) test results, there was an increase in throughput from 189 bps to 2534 bps, packet loss was successfully maintained at 0%, delay from 49.85 ms to 3.94 ms, and jitter from 47.8 ms to 6.75 ms. These results show that the implementation of HTB has a significant impact on improving network efficiency and stability.
PERANCANGAN APLIKASI ABSENSI KELAS PRESENTENSE.COMSCI BERBASIS GLIDE SEBAGAI PLATFORM NO-CODE Evelyn Keisha Silalahi; Aurela Khoiri Nasution; Josua Anugrah Deo Tampubolon; Rut Kezia Imburi; Adidtya Perdana
Jurnal Teknologi Informasi dan Komputer Vol. 12 No. 1 (2026): JUTIK : Jurnal Teknologi Informasi dan Komputer, Edisi April 2026
Publisher : LPPM Universitas Dhyana Pura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36002/jutik.v12i1.3977

Abstract

The development of information technology has encouraged the birth of digital solutions in various fields, including education. One of the problems often faced in the academic environment is a manual attendance system that is prone to manipulation, inefficient, and makes it difficult to record data. This research aims to design and implement a mobile-based digital attendance application called Presentense.ComSci, using Glide as a no-code platform. The research method used is Research and Development (R&D), with stages ranging from needs analysis, system design, implementation, to evaluation. This application is designed to be able to record student attendance in real-time through the institution's email verification feature, automatic time recording (timestamp), GPS location tracking, and selfie upload as proof of attendance. Attendance data is automatically saved into a Google Spreadsheet, so it can be accessed by the admin practically and safely. Tests were conducted on two classes at Medan State University with the results showing that the application was able to function properly, although there were some problems with GPS location accuracy. With this application, the attendance recording process becomes more transparent, efficient, and practical, and can be an innovative solution for attendance management in higher education.
ANALISIS PENERIMAAN PENGGUNA TERHADAP ALGORITMA REKOMENDASI ARTIFICIAL INTELLIGENCE PADA SPOTIFY MENGGUNAKAN TAM Dealy Alti; Valens Florencia; Kevin Fernando Cahyadi; Dicky Pratama
Jurnal Teknologi Informasi dan Komputer Vol. 12 No. 1 (2026): JUTIK : Jurnal Teknologi Informasi dan Komputer, Edisi April 2026
Publisher : LPPM Universitas Dhyana Pura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36002/jutik.v12i1.3978

Abstract

Artificial Intelligence (AI) has been transforming various sectors, and the music streaming industry is no exception. Spotify stands out for employing AI to deliver tailored music suggestions to its users. This research explores user responses to such AI-driven features by utilizing the Technology Acceptance Model as an analytical framework. The study evaluates four dimensions: perceived ease of use, perceived usefulness, behavioral intention, dan actual system use. A survey method was implemented, gathering responses from 100 Spotify users. The results were examined with the help of statistical tools, namely SPSS and SmartPLS. Findings reveal that users’ continued engagement is more strongly linked to the perceived advantages of AI recommendations than to how easy the system is to use.
PENGARUH TEKNOLOGI ARTIFICIAL INTELLIGENCE APLIKASI DUOLINGO TERHADAP KEPUASAN PELANGGAN MENGGUNAKAN METODE TECHNOLOGY ACCEPTANCE MODEL (TAM) Cesya Catherine; Albert Wijaya; Dicky Pratama
Jurnal Teknologi Informasi dan Komputer Vol. 12 No. 1 (2026): JUTIK : Jurnal Teknologi Informasi dan Komputer, Edisi April 2026
Publisher : LPPM Universitas Dhyana Pura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36002/jutik.v12i1.3984

Abstract

The advancement of technology, particularly Artificial Intelligence (AI), has brought significant changes to the education sector, especially in the use of digital learning applications such as Duolingo. This application integrates AI to provide an adaptive and personalized learning experience, enabling content customization and automatic feedback based on user performance. This research endeavors to understand the impact of AI technology in the Duolingo application on user satisfaction by applying the Technology Acceptance Model (TAM) framework. A quantitative approach was used, with data gathered through questionnaires distributed to 100 active Duolingo users. The research variables include perceived ease of use (PEOU), perceived usefulness(PU), attitude toward use(AT), behavioral intention(BI), and actual usage(AU). The outcomes of the validity and reliability tests show that all instruments utilized in this research fulfill the requirements for validity and reliability.Structural model analysis shows that all hypotheses in the TAM model are statistically significant, where the ease of use of AI positively influences perceived usefulness, user attitude, behavioral intention, and actual usage. The conclusion of this study reveals that the integration of AI in Duolingo has a positive impact on user satisfaction. This study helps to further the understanding of learning technology that is more engaging, interactive, effective, and adaptable to future needs.
ANALISIS KEPUASAN PENGGUNA TERHADAP ALGORITMA AI DALAM PERSONALISASI KONTEN PADA APLIKASI INSTAGRAM MENGGUNAKAN METODE EUCS Callista Felisya; Felinsia Pung Handoko; Shella Marcelia; Dicky Pratama
Jurnal Teknologi Informasi dan Komputer Vol. 12 No. 1 (2026): JUTIK : Jurnal Teknologi Informasi dan Komputer, Edisi April 2026
Publisher : LPPM Universitas Dhyana Pura

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

Abstract

As one of the popular platforms and often used by the general public, Instagram is a social media that is widely used by the public that allows us to post content, exchange content, and get information from the Artificial Intelligence (AI) algorithm. Based on the number of users who use the Instagram application, this study was conducted to provide a level of user satisfaction with the AI ​​algorithm in personalizing content presented by the Instagram application. The approach applied to assess the level of user satisfaction with the AI ​​algorithm is the End-User Computing Satisfaction (EUCS) Method. The data collection method appliedis the use of a questionnaire with a total of 18 questions distributed to 100 respondents who are active users of the Instagram a pplication. Based on the data collection obtained using EUCS, from a total of 5 hypotheses, there are 2 hypotheses that have a significant influence on the scale of user satisfaction and these variables are accuracy & timeliness variables. From the results of this hypothesis, it can be stated that the AI ​​algorithm in the Instagram application provides satisfaction to users in the context of content personalization accuracy and timeliness in presenting content, but the AI ​​algorithm has not made a significant contribution to other aspects such as Content, Format and Ease of Use. The percentage obtained based on 5 hypothesis tests, 40% shows that the AI ​​algorithm has influenced user satisfaction, but the other 60% are content suitability, explore page accuracy, lack of application display, and user convenience in using the application that still needs to be returned by the application manager to provide a satisfying user experience. This study can be a basis for the Instagram application itself to improve the AI ​​algorithm in developing their application in order to provide comprehensive satisfaction to users.
RANCANG BANGUN SISTEM PEMESANAN MAKANAN DAN MINUMAN DI RESTORAN ZHAFHA’S HOME BERBASIS WEBSITE Ike Agusti Hardinata; Wulan Andang Purnomo; Fauzi Tri Yuniko
Jurnal Teknologi Informasi dan Komputer Vol. 12 No. 1 (2026): JUTIK : Jurnal Teknologi Informasi dan Komputer, Edisi April 2026
Publisher : LPPM Universitas Dhyana Pura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36002/jutik.v12i1.4350

Abstract

The manual food ordering process at Zhafha's Home Restaurant often results in long lines and long wait times, disrupting customer convenience, especially for office workers with limited rest time. To address this issue, a website-based food ordering system was developed. This system allows customers to order directly through their devices by scanning a QR code provided at the table. Key features include menu display, special promotion information, and digital order data storage. Despite potential challenges such as lack of internet access, the restaurant provides free Wi-Fi and continues to accept manual orders. Implementing this system is expected to improve operational efficiency, service quality, and customer satisfaction, as well as attract new customers.
IMPLEMENTASI LSTM UNTUK ANALISIS SENTIMEN PERSEPSI MASYARAKAT TERHADAP BANJIR SUMATERA 2025 DI YOUTUBE Kunti Najma Jalia; Adi Suwondo
Jurnal Teknologi Informasi dan Komputer Vol. 12 No. 1 (2026): JUTIK : Jurnal Teknologi Informasi dan Komputer, Edisi April 2026
Publisher : LPPM Universitas Dhyana Pura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36002/jutik.v12i1.5212

Abstract

Sumatra Flash Flood triggered extensive public discussion on social media regarding the causes of the disaster, particularly between natural factors and human factors. Understanding public perception is important for evaluating disaster literacy and mitigation communication strategies. This study analyzes public perceptions of the disaster’s causes using sentiment analysis based on the Long Short-Term Memory (LSTM) algorithm applied to YouTube comments. A total of 15,259 comments were collected using the YouTube Data API and processed through data cleaning and lexicon-based automatic labeling. After data selection, 11,043 comments were used for model training and testing. The experimental results show that the LSTM model achieved an accuracy of 96.29% and a ROC-AUC value of 0.99. Sentiment distribution analysis indicates that 57% of comments emphasize human factors, while 43% highlight natural factors or religious interpretations. These findings suggest an increasing public awareness of the human role in disaster risk and demonstrate the effectiveness of LSTM for Indonesian-language disaster sentiment analysis.

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