cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Oris Krianto Sulaiman
Contact Email
oris.ks@ft.uisu.ac.id
Phone
-
Journal Mail Official
oris.ks@ft.uisu.ac.id
Editorial Address
-
Location
Kota medan,
Sumatera utara
INDONESIA
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan
Published by Universitas Islam Sumatera Utara
ISSN : 25407597     EISSN : 25407600     DOI : -
Core Subject : Science,
Computer Science & IT
Merupakan jurnal yang dikelola oleh program studi teknik informatika Universitas Islam Sumatera Utara (UISU), jurnal ini membahas ilmu dibidang Informatika dan Teknologi jaringan, sebagai wadah untuk menuangkan hasil penelitian baik secara konseptual maupun teknis yang berkaitan dengan ilmu informatika. InfoTekjar terbit 2 kali dalam setahun yaitu pada bulan maret dan september, terbitan pertama bulan september 2016. Artikel yang masuk akan diterima oleh editor untuk kemudian diteruskan ke editor bagian dan diteruskan lagi ke reviewer untuk di review artikel nya. Waktu review maksimal dilakukan selama 4 minggu.
Arjuna Subject : -
Articles 354 Documents
 32   33   34   35   36 
Pengembangan Media Virtual Tour 360 Derajat Menggunakan Platform Lapentor Untuk Promosi Ekowisata Gampong Nusa Aceh Besar Farizaki Kahvi; Raihan Islamadina
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Vol 10, No 2 (2026): InfoTekjar Maret
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/infotekjar.v10i2.13106

Abstract

Penelitian ini bertujuan mengembangkan media Virtual Tour 360 derajat menggunakan platform Lapentor sebagai sarana promosi ekowisata di Gampong Nusa, Aceh Besar. Media promosi konvensional dinilai belum mampu memberikan gambaran kondisi destinasi wisata secara realistis. Metode penelitian yang digunakan adalah Research and Development (RD) dengan model ADDIE, meliputi tahap analisis, desain, pengembangan, implementasi, dan evaluasi. Media Virtual Tour dikembangkan dengan menampilkan beberapa titik lokasi utama ekowisata Gampong Nusa dalam bentuk panorama 360 derajat. Tahap implementasi dilakukan melalui uji coba kepada 15 responden menggunakan instrumen kuesioner. Hasil penelitian menunjukkan bahwa media Virtual Tour 360 derajat memperoleh persentase sebesar 80% pada aspek tampilan media dan kemudahan penggunaan, serta persentase sebesar 73% pada aspek kemampuan media dalam menyajikan gambaran kondisi ekowisata secara lebih nyata. Media ini berpotensi menjadi alternatif promosi ekowisata yang efektif dan informatif.
Implementasi YOLO V8 Dengan Pemanfaatan Apple M2 Untuk Deteksi Perilaku Merokok syarifah syifa hamidah; Nixon Erzed
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Vol 9, No 1 (2024): InfoTekJar September
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/infotekjar.v9i1.9713

Abstract

Indonesia is one of the countries facing serious problems related to the high number of smokers. Active smokers have a high risk of contracting various serious diseases, such as heart disease, cancer, respiratory diseases, and others. Additionally, exposure to tobacco smoke also has adverse effects on passive smokers, who are often individuals around them who do not smoke but are affected by it. Conventional methods for detecting smokers are often inefficient and require significant manual intervention, thus necessitating a technological solution for automatic and real-time detection to support the enforcement of anti-smoking regulations. Therefore, this research aims to detect smoking behavior using the You Only Look Once (YOLO) version 8 method on Apple M2. YOLO V8 was chosen for its capability in fast and accurate object detection, while the Apple M2 supports real-time processing. The training results showed an accuracy rate of 91.6%, precision of 96.4%, recall of 90.4%, and an F1-Score of 93.2%. During the inference stage, the Apple Neural Engine (ANE) was able to process 21-25 frames per second (fps), demonstrating good capability for real-time object detection. The combination of YOLO V8 and Apple M2 proved effective for detecting smokers in public areas, offering an efficient and effective innovative solution, supporting the creation of a smoke-free environment in Indonesia, and showing great potential for the application of edge computing in similar applications in the future.
Prediksi Viralitas Hoaks Menggunakan Explainable Machine Learning Doughlas Pardede; Muhamad Sayid Amir Ali Lubis; Agus Fahmi Limas Ptr
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Vol 10, No 1 (2025): InfoTekJar September
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/infotekjar.v10i1.13089

Abstract

The spread of hoaxes on social media has become a systemic threat, potentially triggering opinion polarization, mass panic, and disruption of social stability. Previous research has primarily focused on hoax detection through classification, while predictive efforts to anticipate the extent of their spread remain limited. This study aims to develop a machine learning model to predict the propagation level of hoax content on social media (low, medium, high) and identify the most influential factors contributing to its virality. The dataset was collected from TurnBackHoaks and MAFINDO repositories, comprising 2,500 Indonesian-language hoax contents published throughout 2022-2023. Feature extraction included TF-IDF-based text features and sentiment analysis, temporal features (upload time), and early engagement features (number of likes, shares, comments within the first hour). Three algorithms were compared: Logistic Regression, Random Forest, and XGBoost, with class imbalance handled using SMOTE. The results showed that XGBoost achieved the best performance with a macro average F1-score of 0.82, outperforming Random Forest (0.79) and Logistic Regression (0.70). SHAP analysis revealed that early engagement (shares and likes within the first hour) was the most dominant predictor, followed by content emotionality and nighttime uploads. The model demonstrated high sensitivity to the high-spread class (recall 0.85), indicating its potential for integration into early warning systems by social media platforms and fact-checking organizations. This research contributes to the development of predictive approaches in disinformation mitigation and the strengthening of digital literacy in Indonesia.
Fuzzy Mamdani DSS for STIKOM Student Boarding House Selection Ela Roza Batubara; Poningsih Poningsih; Nina Helnida Siadari; Nadia Sidauruk
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Vol 10, No 2 (2026): InfoTekjar Maret
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/infotekjar.v10i2.13243

Abstract

A Decision Support System (DSS) is a system designed to assist users in decision-making based on valid data, involving multiple criteria within a short timeframe. This study employs the Fuzzy Mamdani method as the data processing formula for selecting boarding houses for STIKOM Tunas Bangsa Pematangsiantar students. Selecting a boarding house is a crucial decision faced by migrant students, involving subjective criteria such as price, distance, facilities, room size, and security. Without a systematic tool, students may struggle to choose boarding houses that best suit their preferences, potentially leading to dissatisfaction. This research aims to design and implement a DSS using the Fuzzy Mamdani method to assist students in boarding house selection. The method was chosen for its ability to accommodate linguistic and ambiguous criteria, transforming them into objective and measurable decisions. Five input variables were used: price (Rp 500,000-2,000,000), distance (0-5 km), facilities (0-100), room size (4-30 m²), and security (0-100), with feasibility (0-100) as output. Fuzzy sets and membership functions were defined for each variable, and 45 IF-THEN rules were constructed. Manual calculation for Kost Bio (price Rp 250,000, distance 2.2 km, facilities 88, room size 20.16 m², security 0) produced a feasibility score of 85 (Very Feasible), close to the expert assessment of 93. The system successfully provides objective recommendations, helping students make informed boarding house choices efficiently.

Page 36 of 36 | Total Record : 354

 32   33   34   35   36 

Filter by Year

2016 2026


Reset
Filter By Issues
All Issue Vol 10, No 2 (2026): InfoTekjar Maret Vol 10, No 1 (2025): InfoTekJar September Vol 9, No 2 (2025): INFOTEKJAR MARET Vol 9, No 1 (2024): InfoTekJar September Vol 8, No 2 (2024): InfoTekJar Maret Vol 8, No 1 (2023): InfoTekJar September Vol 7, No 2 (2023): Infotekjar Maret Vol 7, No 1 (2022): InfoTekJar September Vol 6, No 2 (2022): InfoTekJar Maret Vol 6, No 1 (2021): InfoTekJar September Vol 5, No 2 (2021): InfoTekJar Maret Vol 5, No 1 (2020): InfoTekJar September Vol 4, No 2 (2020): InfoTekJar Maret Vol 4, No 1 (2019): InfoTekJar September Vol 3, No 2 (2019): InfoTekJar Maret Vol 3, No 1 (2018): InfoTekJar September Vol 2, No 2 (2018): InfoTekJar Maret Vol 2, No 1 (2017): InfoTekJar September Vol 1, No 2 (2017): InfoTekJar Maret Vol 1, No 1 (2016): InfoTekJar Vol 1, No 1 (2016): InfoTekJar September More Issue