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Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika
Published by Universitas Palangka Raya
ISSN : 1907896X     EISSN : 26560321     DOI : https://doi.org/10.47111/JTI
Core Subject : Science, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Library & Information Science
Jurnal Teknologi Informasi (JTI) diterbitkan adalah Jurnal Jurusan Teknik Informatika Universitas Palangka Raya dengan ISSN 1907-896X, E-ISSN 2656-0321. Jurnal Teknologi Informasi (JTI) merupakan Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika yang menyajikan hasil penelitian yang fokus pada bidang informatika. Jurnal Teknologi Informasi (JTI) terbit dua kali dalam satu tahun (Januari dan Agustus). JTI ini fokus mempublikasi hasil penelitian orisinal yang belum diterbitkan di mana pun, isu yang dipublikasi oleh JTI meliputi pengembangan ilmu pengetahuan komputer dan informatika, fokus pada sains ilmu komputer, teknologi komputer tepat guna, dan rancang bangun sistem informasi.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 465 Documents
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PENERAPAN METODE HYBRID-BASED RECOMMENDATION PADA SISTEM REKOMENDASI LAPTOP: Implementation of Hybrid-Based Recommendation Method in a Laptop Recommendation System Sari, Nova Noor Kamala; Christian , Efrans; Alparez Rati , Rizky
Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 19 No. 1 (2025): Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Inform
Publisher : Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47111/jti.v19i1.22585

Abstract

Recommendation systems play a crucial role in helping users choose complex and diverse products, such as laptops, which have numerous and varied technical attributes. This research aims to implement a Hybrid-Based Recommendation method that combines Content-Based Filtering (CBF) and Collaborative Filtering (CF). CBF is implemented using TF-IDF Vectorization and cosine similarity to recommend laptops based on technical attribute similarity. Concurrently, CF uses Singular Value Decomposition (SVD) to predict user preferences based on rating history. A Cascade Hybrid strategy is applied by filtering initial candidates from CBF and then re-ranking them using rating predictions from CF. The dataset comprises laptop data and user ratings obtained from Kaggle. Evaluation is performed using the NDCG metric to measure the relevance order of recommendations and MAPE to assess prediction accuracy. The research results indicate that this hybrid system is capable of generating relevant and personalized recommendations, with an NDCG value of 0.9838 and a MAPE value of 27.94%. The study concludes that the integration of CBF and CF through a hybrid approach effectively produces relevant and effective recommendations. For future development, exploring other hybrid methods, parameter optimization, and direct user testing are suggested.
PEMANFAATAN AUGMENTED REALITY SEBAGAI MEDIA PROMOSI KAMPUS POLITEKNIK MANUFAKTUR NEGERI BANGKA BELITUNG Nugraha, Estu; Septiandi, Recky; Josi, Ahmat; Andriyanto, Sidhiq
Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 19 No. 2 (2025): Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Inform
Publisher : Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47111/jti.v19i2.22604

Abstract

The development of technology today is advancing at a rapid pace, particularly in the field of information technology. One of the latest advanced and modern information technologies, such as Augmented Reality (AR), has been widely used as a medium for creating 3D objects, such as objects and buildings. This study aims to explore the use of AR for creating promotional and campus introduction media that can accurately represent the physical forms of buildings and facilities at the Bangka Belitung State Polytechnic of Manufacturing, a vocational higher education institution in Indonesia specializing in manufacturing. This media is developed as an Android-based application and can be accessed via Virtual Reality. The method used in this study is the Multimedia Development Life Cycle (MDLC) method. The research results show that the feasibility test score obtained was 82.5%, categorized as highly feasible. Based on these results, it can be concluded that the application was successfully implemented using AR technology and functions effectively.
MINIMALISASI ATTACK SURFACE PADA SERVER WEB MELALUI PENDEKATAN KEAMANAN BERLAPIS Amin, Musa
Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 19 No. 2 (2025): Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Inform
Publisher : Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47111/jti.v19i2.22756

Abstract

Servers used to run WordPress-based web applications face serious challenges due to a wide attack surface, especially when backend and SSH access are exposed to the public. This study designs and implements an access protection architecture for servers and websites by combining Cloudflare proxy, Virtual Private Network (VPN), and Web Application Firewall (WAF) to mitigate these risks. An experimental method is employed by building a simulated LAMP and WordPress-based infrastructure on two Virtual Private Servers (VPS), where all public traffic is routed through Cloudflare and administrative access is strictly limited to VPN tunnels. The test results show that the proposed architecture effectively eliminates unauthorized access to backend pages and SSH services without disrupting public access to the website. This approach demonstrates that a simple layered defense strategy can be practically applied to enhance server security while providing a protection model that can be replicated for similar infrastructures.
SPAM EMAIL CLASSIFICATION USING SUPPORT VECTOR MACHINE (SVM) AND TF-IDF: A CASE STUDY WITH THE TREC 2007 AND ENRON-SPAM DATASETS Paramartha, I Gusti Ngurah Darma; Sudestra, I Made Ardi; Gama, Adie Wahyudi Oktavia; Prathama, Gede Humaswara
Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 19 No. 2 (2025): Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Inform
Publisher : Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47111/jti.v19i2.22770

Abstract

Spam emails represent a substantial concern within the digital landscape, impeding users with unsolicited communications. This study elucidates the utilization of a Support Vector Machine (SVM) coupled with a TF-IDF Vectorizer for categorizing emails into spam and non-spam classifications. The model was developed utilizing two publicly accessible pre-processed datasets: the TREC 2007 Public Spam Corpus and the Enron-Spam Dataset. By employing the TF-IDF algorithm, which allocates heightened importance to infrequent yet pertinent terms, alongside SVM, renowned for its efficacy in textual classification, the model exhibits remarkable efficacy, achieving an accuracy of 99.04%, a precision of 98.57% and a recall of 99.62%. These findings underscore the model's formidable capacity to discern spam emails while concurrently minimizing false positives accurately. This is critical for real-world applications where authentic emails must not be erroneously categorized as spam. Furthermore, this study elaborates on the justification for the selection of TF-IDF and SVM in the context of spam email classification, in addition to the evaluation outcomes of the model, which align with existing literature, wherein the integration of SVM with TF-IDF has demonstrated substantial performance in spam detection endeavours.
IMPLEMENTASI DATA MINING DALAM MENENTUKAN TATA LETAK PRODUK MENGGUNAKAN ALGORITMA FP-GROWTH Prathama, Gede Humaswara; Devi Anggreni, Ni Komang Ayu; Oktavia Gama, Adie Wahyudi; Darma Paramartha, I Gusti Ngurah
Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 19 No. 2 (2025): Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Inform
Publisher : Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47111/jti.v19i2.22855

Abstract

This study analyzes purchasing patterns in minimarkets using the FP-Growth algorithm to optimize product layouts. One year of sales transaction data (103,181 transactions) from UNDIKNAS Mart were analyzed through data cleaning, transformation, and aggregation. The FP-Growth algorithm was applied with minimum support 5%, confidence 80%, and lift >1 thresholds. Results identified strong product associations, particularly between "Aqua 600 ml (Tanggung)" and various snacks, with confidence values of 81-93% and lift >5. Implementing these findings in product arrangement increased sales by 15-20% despite store accessibility limitations. Cross-validation using a decision tree model showed 81.67% accuracy. The findings demonstrate FP-Growth's effectiveness in small-scale transaction data analysis. The research provides practical contributions for retailers to boost sales through data-driven product layout optimization. A limitation is the single-location data scope, suggesting the need for broader subsequent studies. This study offers a data-based approach adoptable by small and medium retail businesses to enhance operational efficiency and profits. The research confirms that data mining techniques can significantly impact retail performance even in constrained environments, providing empirical evidence of FP-Growth's practical utility in real-world minimarket settings. The methodology and findings contribute to the growing literature on data mining applications in small-scale retail operations, offering replicable frameworks for similar business contexts.

Page 47 of 47 | Total Record : 465

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