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E-Commerce Product Recommendation System Using Case-Based Reasoning (CBR) and K-Means Clustering Legito; Wattimena, Fegie Yoanti; Yulianto Umar Rofi'i; Munawir
International Journal Software Engineering and Computer Science (IJSECS) Vol. 3 No. 2 (2023): AUGUST 2023
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v3i2.1527

Abstract

This research proposes and implements an e-commerce product recommendation system that combines Case-Based Reasoning (CBR) and K-Means Clustering algorithms. The main aim of this research is to provide more personalized and relevant product recommendations to e-commerce users. The CBR approach leverages users' transaction history to provide customized recommendations, whereas K-Means Clustering groups users with similar preferences increase the relevance of recommendations. This study assesses the effectiveness of the system by conducting a comprehensive evaluation by comparing system recommendations with actual user preferences. The results of this study reveal that the combined approach of CBR and K-Means Clustering can improve the performance of e-commerce product recommendations, ensure the accuracy of recommendations, and produce a more satisfying shopping experience for users. Although there are limitations in terms of the dataset used and the choice of algorithm parameters, this research makes an important contribution in developing a more adaptive and personalized recommendation system for e-commerce platforms.
The Application of Convolutional Neural Networks in Floristic Recognition Legito; Nuraini, Rini; Judijanto, Loso; Lubis, Ahmadi Irmansyah
International Journal Software Engineering and Computer Science (IJSECS) Vol. 3 No. 3 (2023): DECEMBER 2023
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v3i3.1827

Abstract

In the dynamic field of computer vision, this research explores the application of Convolutional Neural Networks (CNNs) for the complex task of floristic recognition, a critical aspect of botanical and ecological studies. Addressing the challenges posed by the vast diversity and subtle morphological differences among plants, our study leverages CNNs for an efficient and accurate plant identification method. Distinguished by a comprehensive dataset encompassing a wide range of plant species and employing a state-of-the-art CNN model, our research significantly advances the methodology of flower recognition. This paper highlights the CNN model's sophisticated feature extraction and image analysis capabilities, demonstrating its superior performance in classifying a diverse range of flora compared to traditional methods and other machine learning techniques like Support Vector Machines (SVM) and decision trees. Our approach emphasizes practical applications in areas such as agriculture, ecology, and conservation, and offers a powerful tool for rapid and efficient plant identification, crucial in biodiversity studies. The research contributes to the fields of botany, ecology, and environmental conservation, underscoring the transformative potential of CNNs in floristic recognition. It also outlines the future direction for enhancing the model's efficiency, including developing more computationally efficient architectures and expanding training datasets.
The Effect of Using End-to-End Encryption in Improving Data Security in Cloud Computing Satya Arisena Hendrawan; Legito; Muhammad Bitrayoga; Jatmiko Wahyu Nugroho; Arnes Yuli Vandika
International Journal of Health, Economics, and Social Sciences (IJHESS) Vol. 7 No. 1: January 2025
Publisher : Universitas Muhammadiyah Palu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56338/ijhess.v7i1.6941

Abstract

Cloud Computing offers various advantages, but also presents major challenges related to data security. End-to-end encryption (E2EE) is considered as a solution to mitigate threats to the security of data stored and processed in the cloud. This research aims to examine the effect of implementing E2EE encryption in improving data security in Cloud Computing. Using a qualitative approach with literature study and secondary data analysis, this research focuses on three main threat categories: data leakage, unauthorized access, and cyberattacks. The results show that E2EE encryption can reduce the incidence of data leakage by 80%, unauthorized access by 83.3%, and cyberattacks by 78.6%. Despite its effectiveness, E2EE encryption implementation faces challenges in encryption key management and potential degradation in system performance. Therefore, good key management and multifactor authentication are essential to ensure data security. This study concludes that although end-to-end encryption improves security, a thorough policy, including key management and access control, is needed to maximize data protection in Cloud Computing.
Augmented Reality and Virtual Reality: Transforming Digital Experiences Atmodjo WP, Dwi; Syamsudin, Ahmad; Legito; Suban, Agustinus Lambertus
Technologia Journal Vol. 2 No. 1 (2025): Technologia Journal - February
Publisher : Pt. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/c9wb0f81

Abstract

This article discusses the development of Augmented Reality (AR) and Virtual Reality (VR) technologies and their role in the transformation of digital experiences. Using a literature study approach, this study examines various written sources, including scientific journals, technology articles, and recent industry reports, to understand how AR and VR have developed, are applied in various fields, and the challenges faced in their development. The analysis is carried out by comparing the main characteristics of AR and VR, especially in terms of immersion, interactivity, and hardware requirements. The results of the study show that AR is increasingly used in mobile applications, education, manufacturing, and marketing by combining digital elements into the real world. Meanwhile, VR offers a more immersive virtual environment and is widely applied in the entertainment industry, simulation training, and health. Advances in hardware, graphics, and artificial intelligence (AI) have increased the realism and interactivity of these two technologies, expanding their application in various sectors. Although promising, AR and VR still face challenges such as hardware limitations, high production costs, and ergonomic and privacy issues. With continued innovation, AR and VR are expected to be increasingly integrated into various aspects of life, making them key elements in future digital transformation.
Pengembangan Aplikasi Chatbot untuk Layanan Informasi Akademik Berbasis AIML di Universitas Tjut Nyak Dhien Medan Permata Bunda, Yola; Chairu Sabila, Puji; Legito
Riau Jurnal Teknik Informatika Vol. 3 No. 3 (2024): November 2024
Publisher : Prodi Teknik Informatika Universitas Pasir Pengaraian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30606/rjti.v3i3.3540

Abstract

Perkembangan teknologi informasi telah mendorong berbagai institusi pendidikan tinggi untuk menghadirkan layanan informasi yang lebih responsif dan efisien. Universitas Tjut Nyak Dhien Medan memerlukan inovasi sistem informasi yang mampu menjawab kebutuhan mahasiswa dan calon mahasiswa secara cepat dan akurat. Penelitian ini bertujuan untuk mengembangkan aplikasi chatbot berbasis Artificial Intelligence Markup Language (AIML) sebagai media layanan informasi akademik. Metode pengembangan sistem meliputi analisis kebutuhan, desain, implementasi, dan pengujian menggunakan pendekatan blackbox, whitebox, serta User Acceptance Test (UAT). Aplikasi chatbot ini dirancang untuk memberikan jawaban otomatis terhadap pertanyaan umum seputar pendaftaran, program studi, biaya pendidikan, dan informasi kampus lainnya. Hasil pengujian menunjukkan bahwa sistem berhasil menjawab 100% pertanyaan valid berdasarkan knowledge base, dan tingkat kepuasan pengguna berdasarkan UAT mencapai 83,67%. Dengan demikian, aplikasi chatbot ini dapat meningkatkan efisiensi layanan informasi akademik di lingkungan Universitas Tjut Nyak Dhien Medan.
Pelatihan Pengembangan Media Pembelajaran Berbasis Teknologi Informasi sebagai Upaya Peningkatan Kompetensi Profesional Guru Permata Bunda, Yola; Afni, Nurul; Chairu Sabila, Puji; Legito; Harahap, Baginda
JURNAL ABDIMAS MADUMA Vol. 3 No. 2 (2024): Oktober, 2024
Publisher : English Lecturers and Teachers Association (ELTA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52622/jam.v3i2.481

Abstract

Transformasi digital dalam pendidikan menuntut guru untuk mampu mengintegrasikan teknologi secara efektif dalam proses pembelajaran. Namun, masih banyak guru di sekolah menengah atas yang menghadapi kendala dalam hal literasi digital dan kemampuan teknis dalam menyusun media pembelajaran yang menarik dan kontekstual. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan kompetensi profesional guru SMA Kemala Bhayangkari melalui pelatihan pengembangan media pembelajaran berbasis teknologi informasi menggunakan Canva. Metode pelaksanaan meliputi ceramah interaktif, demonstrasi, dan praktik langsung dengan pendekatan individual dan klasikal. Evaluasi dilakukan melalui pre-test dan post-test yang mencakup tiga aspek kompetensi, yaitu: pengetahuan media digital, keterampilan penggunaan Canva, dan kreativitas desain. Hasil menunjukkan adanya peningkatan signifikan pada seluruh aspek, khususnya pada kemampuan teknis menggunakan Canva dengan peningkatan rata-rata sebesar 30 poin. Selain itu, ditemukan pula perubahan positif pada motivasi, kreativitas, dan pemahaman pedagogis peserta dalam menyusun media pembelajaran yang sesuai dengan Kurikulum Merdeka. Kegiatan ini tidak hanya meningkatkan keterampilan guru secara langsung, tetapi juga mendorong terciptanya ekosistem pembelajaran yang lebih adaptif terhadap perkembangan teknologi dan kebutuhan peserta didik.
Application of Artificial Intelligence in Medical Diagnostics: Applications and Implications in the Healthcare Sector Arnes Yuli Vandika; Dadang Muhammad Hasyim; Devi Rahmah Sope; Legito; Novycha Auliafendri
Jurnal Informasi dan Teknologi 2025, Vol. 7, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.vi0.674

Abstract

Artificial Intelligence (AI) has emerged as a transformative innovation in the medical diagnostic sector. This study explores the application and implications of AI in healthcare services at RSUD Dr. H. Abdul Moeloek, Bandar Lampung. Using a qualitative case study method, data were obtained through in-depth interviews and participatory observation. The results show that AI contributes significantly to improving diagnostic accuracy and speed, particularly in radiological imaging. However, limitations in technological infrastructure and system integration were found to hinder its optimal use. Furthermore, the readiness of human resources remains a critical factor. Although there is optimism among medical staff, a lack of technical training has led to gaps in understanding and utilization. Ethical and legal concerns also emerged, especially regarding responsibility in case of misdiagnosis and the protection of patient data. The absence of specific regulations and digital ethics protocols presents a major barrier to AI adoption. This research concludes that while the implementation of AI in medical diagnostics shows promising outcomes, it still faces institutional and regulatory challenges. Strengthening digital literacy among healthcare workers, developing standard operating procedures, and building a secure infrastructure are essential. Collaboration between hospitals, academic institutions, and government bodies is needed to create an inclusive and ethical AI-based healthcare ecosystem.