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SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan
Published by RAM PUBLISHER
ISSN : 30901626     EISSN : 30323991     DOI : -
Core Subject : Humanities, Science, Engineering,
Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan or in English the publication title Information Systems, Engineering and Applied Technology is an open access journal committed to publishing high quality research articles in the fields of Information Systems, Informatics, Digital Communication Information Technology, Tourism Technology, Transportation Technology, Agricultural Technology, Plantations, Fisheries, Marine, Environmental Technology, Artificial Intelligence, Mechanical Engineering, Electrical Engineering, Industrial Engineering and Civil Engineering. Published 4 X (Times) a year in January, April, July, and October. SITEKNIK accepts and selects quality articles and focuses on providing the best service for writers. SITEKNIK is committed to being a leading platform for researchers to share their innovative findings. We also provide a fast and transparent review process to ensure the quality and originality of each published article.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 107 Documents
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Performance Study of 13.56 Mhz Full-Bridge Inverter on Wireless Power Transfer System for Electric Vehicle Charging Meky Taba Orlando MT; Hery Sudaryanto; Iqbal Ahmad Dahlan; Aam Muharam
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 2 No. 4 (2025): October
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.17448266

Abstract

This research developed a series of GaN MOSFET-based full bridge inverters (TP90H050) with UCC27524 drivers for Wireless Power Transfer (WPT) applications of military vehicles, which are targeted to operate at the ISM frequency of 13.56 MHz. The LTspice simulation showed a potential for near-sinusoidal waves (THD<1%) and a power efficiency of ≈2.13 kW at 50Ω. However, the PCB prototype was only capable of stable operation up to 666.66 kHz with a clean box wave output, and separate tests on fourth-order LC–Butterworth filters achieved a sinusoidal signal with an efficiency of ≈75%. Failure analysis attributed MOSFET damage to switching path length, parasitic effects, and protection limitations. Significant differences were found between the simulation and the implementation at 666.66 kHz, where the hardware RMS voltage was only ≈33% of the simulation. Improvements going forward include the use of precision oscillators/DDSs, drivers with protective features (UVLO and active Miller-clamp),  calibrated snubber, and closed controls
A Systematic Literature Review on AI Architecture Frameworkfor Product Analysis & Recommendation System in Electronic Service Irfan Fahmi Ahmadi
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 3 No. 1 (2026): January
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Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.18431166

Abstract

The rapid growth of electronic services has created significant opportunities for personalized product recommendations through artificial intelligence (AI) systems. However, existing recommendation algorithms face critical challenges, including scalability, cold-start issues, and performance degradation in big data environments. This research performs a systematic review of 73 studies published from 2022 until 2024 to examine AI architecture frameworks applied to product analysis and recommendation systems in electronic service. The review identifies dominant frameworks such as CNN, RNN/LSTM, TensorFlow, Spark, and emerging technologies like GNN, alongside distributed infrastructures such as Hadoop for large-scale data processing. Research methods observed include experiments, benchmarks, simulations, surveys, and case studies. Key findings emphasize performance and efficiency improvements, accuracy, and scalability concerns. Based on these insights, this paper proposes a multi-layered AI architecture framework integrating data ingestion, distributed storage, model development, MLOps orchestration, privacy-preserving learning, and adaptive feedback loops. The proposed framework addresses scalability and sustainability challenges while ensuring high-performance recommendation capabilities. This study contributes a comprehensive blueprint for organizations seeking to deploy robust, scalable, and privacy-aware AI systems in dynamic e-service environments.
Rancangan Arsitektur Sistem Analisis Sentimen Kinerja POLRI Berbasis Cloud PaaS dan IndoBERT Novantri Prasetya Putra
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 3 No. 1 (2026): January
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Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.18366548

Abstract

Pada era ini, kepercayaan publik terhadap institusi penegak hukum seperti POLRI sangat dipengaruhi oleh opini yang berkembang di media sosial. Namun, analisis terhadap data masif (Big Data) ini menghadapi dua tantangan utama yaitu keterbatasan metode klasik dalam memahami konteks bahasa Indonesia (seperti sarkasme dan bahasa gaul) serta tingginya kebutuhan sumber daya komputasi untuk menjalankan model Deep Learning. Penelitian ini bertujuan untuk merancang sebuah kerangka kerja sistem analisis sentimen terintegrasi yang tidak hanya akurat, tetapi juga efisien secara infrastruktur dan strategis dalam pengambilan keputusan. Metodologi penelitian ini menggabungkan model IndoBERT untuk klasifikasi teks kontekstual, metode Analytic Hierarchy Process (AHP) untuk pembobotan prioritas kinerja, dan arsitektur Cloud Platform as a Service (PaaS) sebagai lingkungan implementasi. Hasil penelitian ini berupa rancangan arsitektur sistem yang memanfaatkan layanan serverless dan GPU berbasis cloud untuk efisiensi biaya dan skalabilitas otomatis. Simulasi sistem menunjukkan bahwa integrasi IndoBERT mampu mendeteksi sentimen negatif terselubung, sementara AHP berhasil mentransformasi data sentimen menjadi daftar prioritas perbaikan yang dapat ditindaklanjuti (actionable insights). Penelitian ini menyimpulkan bahwa adopsi arsitektur berbasis Cloud PaaS adalah solusi paling layak (feasible) untuk mengimplementasikan model NLP mutakhir di lingkungan pemerintahan tanpa investasi perangkat keras yang masif.
Perancangan Enterprise Architecture Pada UPT Perpustakaan Pondok Pesantren Salafiyah Syafi’iyah Sukorejo Situbondo Berbasis TOGAF ADM Akhlis Munazilin; Arif Ferdiansyah; Bagus Maulana Zulkarnain
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 3 No. 1 (2026): January
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.18334065

Abstract

UPT Perpustakaan Pondok Pesantren Salafiyah Syafi’iyah Sukorejo merupakan pusat literasi yang berperan penting dalam mendukung kegiatan pendidikan santri dan masyarakat. Namun, proses pelayanan, integrasi data, dan pengelolaan sistem informasi masih menghadapi beberapa kendala, seperti pencatatan manual yang tersisa, hilangnya kartu santri, keterbatasan waktu layanan, serta persoalan teknis jaringan. Penelitian ini bertujuan merancang Enterprise Architecture menggunakan kerangka kerja TOGAF ADM sebagai panduan pengembangan sistem informasi perpustakaan. Hasil penelitian berupa model arsitektur bisnis, data, aplikasi, dan teknologi yang dapat dijadikan blueprint pengembangan sistem informasi terpadu guna meningkatkan efisiensi layanan dan mendukung proses digitalisasi perpustakaan.
Artificial Intelligence Adoption and Implementation In Indonesia: Policy Frameworks, Sectoral Applications, and Future Prospects Saskiya Farannisa
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 3 No. 1 (2026): January
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.18431719

Abstract

Indonesia stands at a pivotal moment in its digital transformation journey, with Artificial Intelligence (AI) emerging as a strategic catalyst for economic growth and social development. This paper presents a comprehensive analysis of AI adoption and implementation in Indonesia, examining the national policy framework, sectoral applications, technological infrastructure, and institutional mechanisms established to accelerate AI development. The research reveals that Indonesia's National AI Strategy (Stranas KA) 2020-2045, complemented by institutional structures such as the AI Innovation Center (PIKA) and the Artificial Intelligence Industry Research and Innovation Collaboration (KORIKA), has created a comprehensive ecosystem for AI advancement. Current implementations span critical sectors including healthcare, agriculture, finance, manufacturing, and government services. However, significant challenges persist, particularly in digital infrastructure development, cybersecurity readiness, talent acquisition and retention, and ethical AI governance. Analysis of 43 recent studies from accredited journals indicates that quantitative research methodologies dominate AI investigations in Indonesia, with healthcare and education emerging as primary research foci. This paper concludes that while Indonesia possesses considerable potential to leverage AI for competitive advantage—with projected economic contributions reaching USD 366 billion over the next decade—successful realization requires sustained investment in infrastructure, comprehensive talent development programs, robust ethical frameworks, and enhanced cross-sector collaboration. The findings underscore the necessity of bridging the gap between policy formulation and operational implementation to ensure Indonesia emerges as a regional AI leader in Southeast Asia.
Analisis Strategis Dampak Transformasi Digital Indonesia: Studi Literatur pada Sektor Publik, Ekonomi, dan Pendidikan Dewi Setiowati; Diah Indriani; Inayah Wisartika; Selvi Alvinda Fitriyani
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 3 No. 1 (2026): January
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.18395894

Abstract

Transformasi digital merupakan instrumen strategis untuk meningkatkan efisiensi operasional dan kualitas pelayanan di berbagai sektor. Namun, implementasinya di Indonesia masih menunjukkan hasil yang beragam dan ketimpangan dampak antar wilayah. Penelitian ini menggunakan metode Systematic Literature Review (SLR) terhadap 20 jurnal ilmiah bertema transformasi digital di Indonesia pada sektor publik, UMKM, dan pendidikan dalam rentang tahun 2020–2025. Data dianalisis secara kualitatif melalui teknik analisis tematik untuk memetakan pola keberhasilan dan hambatan sistemik. Hasil penelitian menunjukkan bahwa transformasi digital di Indonesia masih didominasi oleh perubahan administratif (digitization) dan belum sepenuhnya mencapai transformasi substansial. Keberhasilan transformasi bergantung pada variabel multiplikatif antara kepemimpinan digital dan kesiapan operasional SDM. Adanya kesenjangan digital (digital divide) yang signifikan, di mana wilayah metropolitan (Jabodetabek) mendapatkan dampak ekonomi positif yang nyata, sementara wilayah daerah (Pariaman dan Bima) masih menghadapi hambatan literasi dan infrastruktur. Hambatan utama yang teridentifikasi fragmentasi data (silo data), rendahnya kompetensi digital, dan isu keamanan siber. 
Prediksi Kelulusan Mahasiswa Pada Program Studi Akuntansi Fakultas Ekonomi Dan Bisnis Universitas Khairun Dengan Algoritma C4.5 Usman Sadik; Santosa; Salim Albaar
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 3 No. 2 (2026): April
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.18825451

Abstract

Tingkat kelulusan tepat waktu mahasiswa pada Program Studi Akuntansi Fakultas Ekonomi dan Bisnis Universitas Khairun masih relatif rendah. Berdasarkan data lima tahun terakhir, rerata kelulusan tepat waktu tercatat mencapai 17,61%. Kondisi tersebut mendorong perlunya upaya untuk mengidentifikasi dan memprediksi faktor-faktor yang memengaruhi kelulusan mahasiswa sebagai dasar intervensi akademik yang lebih dini. Penelitian ini mengembangkan aplikasi prediksi kelulusan mahasiswa menggunakan metode decision tree dengan algoritma C4.5. Variabel yang digunakan meliputi asal sekolah, penghasilan orang tua, jalur masuk, IPK, indeks prestasi semester 1 hingga semester 6, serta status beasiswa. Dataset penelitian terdiri dari 83 mahasiswa angkatan 2020 sebagai data pelatihan dan 137 mahasiswa angkatan 2021 sebagai data pengujian. Kinerja model dievaluasi menggunakan teknik K-Fold Cross Validation dengan nilai K=5. Hasil pengukuran dan pengujian menunjukkan bahwa model C4.5 menghasilkan akurasi 69,67%, presisi 24,49%, recall 70,59%, dan F1-score 36,36%. Faktor yang paling dominan dalam menentukan kelulusan adalah indeks prestasi semester 6 pada kategori A. Model yang dihasilkan berpotensi dimanfaatkan sebagai alat pendukung evaluasi akademik dan pengambilan keputusan pada institusi pendidikan.
Analisis Tata Kelola Sistem Informasi Dengan Framework COBIT 5 : Studi Kasus Pada PT. Bintang Mutiara Cemerlang Naufal Fathoni Putra; Adnan Buyung Nasution; Maulidya Putri Kinanti Ritonga
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 3 No. 2 (2026): April
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.19924543

Abstract

Perkembangan teknologi informasi saat ini memberikan dampak yang begitu besar bagi sebuah perusahaan untuk mencapai tujuannya. PT. Bintang Mutiara Cemerlang adalah perusahaan yang bergerak di bidang distribusi makanan dan minuman yang dipasok ke setiap kota di Indonesia. Melalui wawancara yang kami lakukan, diketahui beberapa hal yang menjadi sumber permasalahan saat ini yang perlu mendapat perhatian antara lain pengiriman yang lambat, kualitas produk yang tidak sesuai dengan kesepakatan/buruk, tidak memberikan solusi ketika terjadi masalah. terjadi, untuk memberikan harga yang tidak masuk akal. Karena sesuai dengan fungsi teknologi informasi yang memiliki peran penting, maka diperlukan evaluasi tata kelola untuk mengetahui kapabilitas yang dimiliki oleh suatu teknologi informasi. Pada penelitian ini framework yang digunakan adalah framework COBIT 5 dengan tahapan Assessment Process Activities. Domain yang digunakan dalam penelitian ini adalah EDM02 (Ensure Benefits Delivery), BAI06 (Manage Changes), DSS01 (Manage Operations). Agar PT. Bintang Mutiara Cemerlang disarankan untuk melengkapi kekurangan yang dibutuhkan dan mengoptimalkan kekuatan perusahaan agar tidak terjadi kesalahan yang fatal. Hal ini juga bertujuan untuk memaksimalkan dan meningkatkan tata kelola teknologi informasi di dalam perusahaan.
A Bibliometric Analysis of Research Trends in AI Integration within Cloud Computing Mega Fitri Yani; Istifa Shania Putri; Cindy Muhdiantini; Farid Munadhil
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 3 No. 2 (2026): April
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.19927559

Abstract

The integration of Artificial Intelligence (AI) and cloud computing has emerged as a rapidly expanding research area, driven by the need for scalable, elastic, and cost-efficient intelligent systems. Cloud infrastructures enable dynamic resource allocation and pay-as-you-go models, making them ideal environments for AI model training and deployment. Despite the growing volume of publications, a structured mapping of the intellectual landscape of AI–cloud integration remains necessary. This study aims to analyze the research landscape of AI integration in cloud computing using a bibliometric approach. Data were collected from the Scopus database for the period 2021-2026 using the query “Artificial Intelligence” AND “Cloud Computing”, focusing on English-language articles. The analysis was conducted using the Bibliometrix package in R to examine Annual Scientific Production, Countries Collaboration World Map, Most Relevant Affiliations, Co-occurrence Network, Thematic Map, Most Relevant Words, Trend Topics. The findings reveal a significant increase in publications after 2021, indicating accelerating academic interest in AI–cloud convergence. International collaboration is dominated by countries such as India, China, Saudi Arabia, the United States, and the United Kingdom. Thematic analysis shows that artificial intelligence and cloud computing function as foundational themes, with machine learning acting as a key driving force. Emerging topics such as edge computing and real-time systems suggest a shift toward intelligent, distributed, and data-intensive cloud environments.
From Technical Security to Human Awareness: A Bibliometric Review of Cybersecurity Education Research Cindy Muhdiantini; Mega Fitri Yani; Istifa Shania Putri
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 3 No. 2 (2026): April
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.19897820

Abstract

The rapid advancement of information technology has increased cybersecurity threats, emphasizing the importance of education in building security awareness and human-centered defense capabilities. As research on cybersecurity education continues to grow, a systematic understanding of its research trends and thematic evolution is required. This study analyzes global research trends in cybersecurity education using a bibliometric approach. A total of 189 Scopus-indexed publications from 2020 to 2026 were analyzed using the bibliometrix R package and the Biblioshiny interface. The analysis examines annual publication growth, dominant keywords, evolving research topics, and geographical research contributions. The results indicate a steady increase in scientific production, confirming cybersecurity education as an expanding research domain. While technical topics such as network and data security remain prominent, recent research shows a clear shift toward education, training, and security awareness, highlighting the growing importance of human factors in cybersecurity. In addition, the findings reveal an imbalance in global research contributions and relatively limited international collaboration. This study provides a concise overview of the development and structure of cybersecurity education research and offers insights to support future studies, curriculum development, and policy formulation.

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