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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) IJCCS (Indonesian Journal of Computing and Cybernetics Systems) JURNAL SISTEM INFORMASI BISNIS Jurnal Peternakan Integratif Elkom: Jurnal Elektronika dan Komputer Journal of Education and Learning (EduLearn) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Prosiding SNATIF Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Transformatika JUITA : Jurnal Informatika Scientific Journal of Informatics Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan JOIN (Jurnal Online Informatika) JOIV : International Journal on Informatics Visualization AdBispreneur Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JIKO (Jurnal Informatika dan Komputer) JURNAL MEDIA INFORMATIKA BUDIDARMA Information System for Educators and Professionals : Journal of Information System SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Jurnal Informatika Aptisi Transactions on Management JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Aptisi Transactions on Technopreneurship (ATT) EDUMATIC: Jurnal Pendidikan Informatika Building of Informatics, Technology and Science Jurnal Mnemonic Journal Sensi: Strategic of Education in Information System Indonesian Journal of Electrical Engineering and Computer Science Abdimasku : Jurnal Pengabdian Masyarakat Computer Science and Information Technologies Jurnal Bumigora Information Technology (BITe) Aiti: Jurnal Teknologi Informasi Infotech: Journal of Technology Information Jurnal Teknologi Informasi dan Komunikasi Jurnal Teknik Informatika (JUTIF) Indonesian Journal of Applied Research (IJAR) Journal of Applied Data Sciences JOINTER : Journal of Informatics Engineering Jurnal Indonesia : Manajemen Informatika dan Komunikasi Journal of Information Technology (JIfoTech) Edutik : Jurnal Pendidikan Teknologi Informasi dan Komunikasi Nusantara of Engineering (NOE) Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat Jurnal Rekayasa elektrika Jurnal INFOTEL SmartComp Jurnal Indonesia : Manajemen Informatika dan Komunikasi Blockchain Frontier Technology (BFRONT) Scientific Journal of Informatics JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
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Security Level Significance in DApps Blockchain-Based Document Authentication Aini, Qurotul; Manongga, Danny; Rahardja, Untung; Sembiring, Irwan; Elmanda, Vonda; Faturahman, Adam; Santoso, Nuke Puji Lestari
Aptisi Transactions On Technopreneurship (ATT) Vol 4 No 3 (2022): November
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v4i3.277

Abstract

In the development of the Industrial revolution 4.0 to improve and modify the world's industry by integrating production lines, and extraordinary results in the field of technology and information marked its emergence. It can be used to enhance document security systems using Blockchain technology. Blockchain Innovation Authentication has attracted great attention in the world of science and capital markets. The persistent problems of the many available digital currencies and the various tricks of early coin offerings also welcome the well-known discussion of emerging innovations in the field of education. The importance of this paper follows the improvement of the blockchain framework to reveal the importance of decentralized applications (dApps) and blockchain on the future value in education. This study uses a descriptive method, which is a research method used to describe problems that occur in the present or ongoing, aiming to describe what happened as it should when the research was conducted. the novelty of cutting-edge dApps and talk about the title of blockchain progress to meet the positive attributes of future dApps. Readers will come to the conclusion of dApp research and know the continuous improvement in blockchain .
Transformation of Payment in Education Use Bitcoin with Reduced Confirmation Times Henderi; Aini, Qurotul; Manongga, Danny; Sembiring, Irwan; Apriliasari, Dwi
Aptisi Transactions On Technopreneurship (ATT) Vol 5 No 1 (2023): March
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v5i1.285

Abstract

Significant changes in the financial system are prompted by the growth of the national economy, particularly as a form of payment. The means evolved from barter to things or commodities to metal and paper as the base materials for money before arriving at barter. With such significant changes, there is also a need for a transformation in the world of education in order to welcome technological advancements and one way to survive the changes in the increasingly rapid digital era. As the economic need increases, trade transaction methods shift from traditional to internet-based. One of the necessary international online payment options is bitcoin. For many applications where payments are modest and instantaneous approval is required, Bitcoin is inappropriate because of the high transaction fees and long confirmation periods. As a result, despite the introduction of numerous rival cryptocurrencies to address these problems, the Bitcoin network continues to be the most extensively used payment method. Unquestionably, new finding of this research that effectively address the problems of high transaction costs and transaction verification times are needed if the company is to benefit from its user network. The Lightning Network (LN), which makes use of off-chain bidirectional payment channels between participants, is one of the most recent payment network concepts to be proposed.
Improving performance of air quality monitoring: a qualitative data analysis Manongga, Danny; Rahardja, Untung; Sembiring, Irwan; Aini, Qurotul; Abas Sunarya, Po
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i4.pp3793-3807

Abstract

This research aims to improve performance of air quality monitoring and understand the latest relevant technological developments. Employing the Kitchenham systematic literature review (SLR) method, the study examines 436 journal articles and conference proceedings published from 2019 to 2023, sourced from the Web of Science (WoS) and Scopus databases. The analysis was carried out using Leximancer 5.0 and identified research five themes; i) air quality, ii) artificial intelligence (AI), iii) pollution, iv) middleware, and v) smart environment. The results showed that only 48 journals had strict inclusion and exclusion criteria include relevance to the research theme, methodological quality, and contribution to the research field. In addition, this research integrates AI and middleware, which has significantly contributed to improving air quality. These findings can become the basis for the development of air quality monitoring technology that is more sophisticated and responsive to environmental needs. This research contributes to further understanding air quality monitoring technology trends and designing solutions to improve overall air quality.
Network Intrusion Detection Using Transformer Models and Natural Language Processing for Enhanced Web Application Attack Detection Priatna, Wowon; Sembiring, Irwan; Setiawan, Adi; Setyawan, Iwan
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 3 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i3.82462

Abstract

The increasing frequency and complexity of web application attacks necessitate more advanced detection methods. This research explores integrating Transformer models and Natural Language Processing (NLP) techniques to enhance network intrusion detection systems (NIDS). Traditional NIDS often rely on predefined signatures and rules, limiting their effectiveness against new attacks. By leveraging the Transformer's ability to capture long-term dependencies and the contextual richness of NLP, this study aims to develop a more adaptive and intelligent intrusion detection framework. Utilizing the CSIC 2010 dataset, comprehensive preprocessing steps such as tokenization, stemming, lemmatization, and normalization were applied. Techniques like Word2Vec, BERT, and TF-IDF were used for text representation, followed by the application of the Transformer architecture. Performance evaluation using accuracy, precision, recall, F1 score, and AUC demonstrated the superiority of the Transformer-NLP model over traditional machine learning methods. Statistical validation through Friedman and T-tests confirmed the model's robustness and practical significance. Despite promising results, limitations include the dataset's scope, computational complexity, and the need for further research to generalize the model to other types of network attacks. This study indicates significant improvements in detecting complex web application attacks, reducing false positives, and enhancing overall security, making it a viable solution for addressing increasingly sophisticated cybersecurity threats
WEBSITE VULNERABILITY TESTING USING THE PENETRATION TESTING METHOD REFERRING TO NIST SP 800 – 155 (CASE STUDY (Astonprinter.com Domain)) Agustinus, Ari; Sembiring, Irwan
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 6 (2024): JUTIF Volume 5, Number 6, Desember 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.6.3859

Abstract

Information security is a very important aspect in maintaining the confidentiality, integrity and availability of data on a system, especially on websites that are vulnerable to various cyber threats. This research aims to test website vulnerabilities using the penetration testing method by referring to the NIST SP 800-115 standard. The case study used in this research is the astonprinter.com website. The penetration testing method applied in this research follows the NIST SP 800-115 guidelines which include the Planning, Discovery, Attacking and Reporting stages. The results of the research show that the astonprinter.com website has 20 vulnerabilities that can be exploited, with details of 2 vulnerabilities which are in the high threat level, namely DNS Server Spoofed Request Amplification Ddos and Path Traversal, then it has 7 vulnerabilities which are in the medium threat level, including DNS Server Chace Snooping Remote Information Disclosure and Vulnerable Js Library and 11 vulnerabilities that are in the low threat level including ICMP Timestamp Request Remote Date Disclosure, SSH Server CBC Mode Ciphers Enabled, , Cookie No HttpOnly Flag and Cookie without SameSite Attribute. These findings can provide valuable insight for website managers in strengthening security systems and reducing the risk of cyber attacks in the future.
The object detection model uses combined extraction with KNN and RF classification Kurniati, Florentina Tatrin; Manongga, Daniel HF; Sembiring, Irwan; Wijono, Sutarto; Huizen, Roy Rudolf
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 1: July 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i1.pp436-445

Abstract

Object detection plays an important role in various fields. Developing detection models for 2D objects that experience rotation and texture variations is a challenge. In this research, the initial stage of the proposed model integrates the gray-level co-occurrence matrix (GLCM) and local binary patterns (LBP) texture feature extraction to obtain feature vectors. The next stage is classifying features using k-nearest neighbors (KNN) and random forest (RF), as well as voting ensemble (VE). System testing used a dataset of 4,437 2D images, the results for KNN accuracy were 92.7% and F1-score 92.5%, while RF performance was lower. Although GLCM features improve performance on both algorithms, KNN is more consistent. The VE approach provides the best performance with an accuracy of 93.9% and an F1-score of 93.8%, this shows the effectiveness of the ensemble technique in increasing object detection accuracy. This study contributes to the field of object detection with a new approach combining GLCM and LBP as feature vectors as well as VE for classification.
IMPLEMENTASI KEAMANAN JARINGAN KOMPUTER DENGAN IPTABLES SEBAGAI FIREWALL MENGGUNAKAN PORT KNOCKING METODE DINAMIS Budi, Reza Setya; Sembiring, Irwan
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 1 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i1.5750

Abstract

Keamanan jaringan adalah aspek penting dalam perlindungan data dan layanan dari ancaman siber. Salah satu metode inovatif yang digunakan untuk meningkatkan keamanan adalah dinamis port knocking (dynamic port knocking). Metode ini menggabungkan konsep dasar port knocking dengan elemen dinamis untuk memberikan lapisan perlindungan yang lebih kuat terhadap akses tidak sah. Port knocking tradisional melibatkan pengiriman serangkaian koneksi ke port tertutup dalam urutan tertentu untuk membuka akses ke layanan yang dilindungi. Namun, pendekatan ini dapat rentan terhadap serangan brute force dan replay. Dinamis port knocking memperbaiki kelemahan ini dengan mengubah urutan dan port yang harus diketuk berdasarkan parameter dinamis, seperti waktu atau informasi sesi yang dienkripsi. Dalam dinamis port knocking, pola knocking dapat berubah secara periodik atau berdasarkan algoritma tertentu, sehingga lebih sulit bagi penyerang untuk menebak urutan yang benar. Parameter dinamis dapat disesuaikan untuk menambah lapisan keamanan tambahan, seperti menggunakan token berbasis waktu atau informasi unik lainnya yang hanya diketahui oleh pengguna sah. Keuntungan utama dari dinamis port knocking meliputi peningkatan keamanan melalui perubahan urutan port secara berkala, mengurangi risiko deteksi oleh penyerang, dan meningkatkan kompleksitas serangan brute force dan replay. Selain itu, metode ini dapat diintegrasikan dengan protokol keamanan lain untuk membangun sistem pertahanan yang lebih komprehensif. Namun, implementasi dinamis port knocking juga memiliki tantangan, termasuk kebutuhan akan sinkronisasi waktu yang presisi antara klien dan server, serta kompleksitas dalam pengaturan dan pemeliharaan sistem. Dengan desain yang hati-hati dan pemanfaatan teknologi enkripsi yang kuat, dinamis port knocking dapat menjadi elemen penting dalam strategi keamanan jaringan modern, memastikan bahwa hanya pengguna yang berwenang dapat mengakses sumber daya yang dilindungi.
Exploring the Relationship between Artificial Intelligence and Business Performance Lutfiani, Ninda; Sembiring, Irwan; Setyawan, Iwan; Setiawan, Adi; Rahardja, Untung; Sulistio, Sulistio
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 19, No 1 (2025): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.86697

Abstract

The integration of Artificial Intelligence (AI) into business operations has garnered significant attention due to its potential impact on business performance. However, the relationship between AI adoption and business performance remains not fully understood. This article comprehensively analyzes this relationship through three key aspects: the acceptance and implementation of AI within organizations, the impact of AI on various dimensions of business performance, and the potential challenges associated with AI adoption. In this study, we employ SmartPLS as an analytical tool to evaluate the relationships between identified factors and the impact of AI adoption on business performance. Our findings reveal that several factors influence the adoption and implementation of AI, including data availability, organizational culture, leadership support, technical expertise, and ethical considerations. Moreover, AI adoption significantly influences business performance metrics such as productivity, efficiency, revenue, and customer satisfaction. Nonetheless, challenges arising from AI adoption, including shifts in job roles, data privacy, and security concerns, also require substantial attention. In conclusion, successful AI adoption and implementation necessitate careful consideration of organizational, technical, and ethical factors. This research provides valuable insights for business leaders and researchers seeking a deeper understanding of the relationship between Artificial Intelligence and business performance.
Aesthetic Photography Analysis on Instagram: A Visual Study of Social Media using ATLAS.ti Wibowo, Mars Caroline; Purnomo, Hindriyanto Dwi; Hartomo, Kristoko Dwi; Sembiring, Irwan
Scientific Journal of Informatics Vol. 11 No. 4: November 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i4.13985

Abstract

Purpose: This study aims to analyze the dominant trends in color and composition within aesthetic photography on Instagram and explore their influence on user interaction, specifically likes and comments. Given the growing role of visual aesthetics in digital marketing, understanding these elements is crucial for content creators, brands, and businesses aiming to maximize engagement. Unlike previous studies that focus on general social media engagement, this research integrates technology-driven qualitative analysis using ATLAS.ti, enabling structured coding and thematic identification of visual elements. Methods: A qualitative content analysis was conducted on 591 Instagram posts tagged with #AestheticPhotography and #VisualAesthetic. Data was collected using Instagram scraping (PhantomBuster), extracting both visual (color palettes, composition techniques) and textual (captions, metadata) elements. The ATLAS.ti software was used to analyze recurring visual patterns and color extraction was performed via Google Colab and Python for accuracy. Result: The results show that natural colors (48.18%) and pastel tones (30.90%) are dominant in aesthetic photography, contributing to higher engagement due to their harmonious and calming effect. Composition techniques such as center alignment (40.51%) and the Rule of Thirds (23.27%) significantly correlate with user interaction, as they align with cognitive load theory and visual perception principles. Additionally, short captions (≤10 words) were more effective in enhancing engagement, receiving 8,876 likes and 4,432 comments on average, compared to longer captions. Novelty: This study bridges the gap between visual aesthetics and computational analysis, using ATLAS.ti to systematically examine social media trends. Unlike previous studies that focus solely on quantitative metrics, this research provides qualitative insights into how color and composition influence engagement. The findings offer practical guidance for content creators, designers, and marketers, suggesting that strong visual composition and color harmony can enhance audience engagement.
CRYPTO NARRATIVES SENTIMENT ANALYSIS ON BITCOIN PRICE PREDICTION USING THE NAIVE BAYES METHOD Nuryadi, Didik; Manongga, Daniel H.F.; Sembiring, Irwan
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 2 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i2.6116

Abstract

Globalization affects many aspects of human life with consequences that may be positive or negative. Advances in information technology, which significantly assist many human activities, are one of the ele-ments affected. As a new product of financial technology, cryptocur-rency has revolutionized the global payment system. Bitcoin has expe-rienced significant price increases in recent years, often caused by eco-nomic and psychological market factors. Sentiment analysis of the bitcoin crypto narrative is essential for understanding market behavior and predicting price trends because market sentiment has been proven to influence bitcoin price movements. Therefore, this research aims to investigate the crypto sentiment narrative regarding Bitcoin price movements using a sentiment analysis approach with the Naïve Bayes classification method. The dataset used in this research comes from crypto narratives that are considered to influence bitcoin price move-ments, which were collected from October 2022 to April 2024. This re-search succeeded in classifying the data tested using 10-fold cross-validation testing, with an average of 76.13%. The precision score for the positive opinion class was 63.92%, and the precision score for the negative opinion class reached 81.77%. The average recall value for the positive class was 61.69%, and for the negative class, it reached 83.12%. This data shows that Naïve Bayes is quite good at analyzing crypto sentiment narratives regarding bitcoin price movements.
Co-Authors Abas Sunarya, Po Ade Iriani Adi Setiawan Adriyanto Juliastomo Gundo Agus Sugiarto Agustinus, Ari Alamsyah, Ferry Andriana, Myra April Lia Hananto Apriliasari, Dwi Ardaneswari, Awanda Arthur, Christian Astawa, I Wayan Aswin Dew Ayu Sanjaya, Yulia Putri Bayu Setyanto Pamungkas Budhi Kristianto Budi Santoso Budi, Reza Setya Cahyaningtyas, Christian Daniawan, Benny Danny Manongga Danny Sebastian Dedy Prasetya Kristiadi Dwi Hosanna Bangkalang Dwi Setiawan Edi Suharyadi Efendy, Rifan Eko Sediono Eko Sediyono Eleazer Gottlieb Julio Sumampouw Elmanda, Vonda Erick Alfons Lisangan Esti Zakia Darojat Evangs Mailoa Evi Maria Faturahman, Adam Fauzi Ahmad Muda Fian Yulio Santoso Florentina Tatrin Kurniati Gallen cakra adhi wibowo Gerry Santos Lasatira Ginting, Jusia Amanda Girinzio, Iqbal Desam Gudiato, Candra Hamdan . Hany Makaruku, Yulian Hasnudi . Henderi Henderi . Hendry Hendry, - Henuk, Yusuf Leonard Hindriyanto Dwi Purnomo Huda, Baenil Ignatius Agus Supriyono Ilham Hizbuloh Indrastanti Ratna Widiasari Iwan Setiawan Iwan Setiawan Iwan Setyawan Joko Listiawan Sukowati Joko Siswanto Joko Siswanto Jonas, Dendy Julians, Adhe Ronny Juneth Manuputty Krismiyati Kristoko D Hartomo Kristoko Dwi Hartomo Kusumajaya, Robby Andika Limbong, Josua Josen Alexander Madawara, Herdin Yohnes Manongga, Daniel H.F Manongga, Daniel H.F. Manongga, Daniel HF Marsyel Sampe Asang Marvelino, Matthew Mau, Stevanus Dwi Istiavan Maya Sari Merryana Lestari Migunani Migunani Mira Mira Mira Mohammad Ridwan Muhamad Yusup Nanle, Zeze Nazmun Nahar Khanom Nina Setiyawati Ninda Lutfiani Nining Fitriani Nugroho, Samuel Danny Nurtino, Tio Nuryadi, Didik Nurzainah Ginting Pamungkas, Bayu Setyanto Phillnov Yohanes Pinontoan Pinontoan, Phillnov Yohanes Priatna , Wowon Purbaratri, Winny Purnama Harahap, Eka Purnomo, Hidriyanto Dwi Putra, Yonathan Rahadi Qurotul Aini Qurotul Aini Rahardja.,M.T.I.,MM, Dr. Ir. Untung Raymond Elias Mauboy Rimes Jopmorestho Malioy Roy Rudolf Huizen Saian, Septovan Dwi Suputra Sandry Lanovela Pasaribu Santoso, Nuke Puji Lestari Sediyono, Eko - Setiawan Hakim Sri Ngudi Wahyuni Sri Ngudi Wahyuni, Sri Ngudi Sri Yulianto Joko Prasetyo Suharyadi Sulistio Sulistio Sumampouw, Eleazer Gottlieb Julio Supriadi, Candra Suryantara, I Gusti Ngurah Susanti, Novita Dewi Sutarto Wijono Suwijo Danu Prasetyo Teady Matius Surya Mulyana, Teady Matius Teguh Wahyono Theopillus J. H. Wellem Tintien Koerniawati Tirsa Ninia Lina Tomasoa, Lyonly Tri Wahyuningsih Tri Wahyuningsih Tukino, Tukino Untung Rahardja Untung Rahardja Wibowo, Mars Caroline Wijaya, Angga Zakharia Wiwien Hadikurniawati Yerik Afrianto Singgalen Yessica Nataliani Yohan Maurits Indey Yohnes Madawara, Herdin Yulian Hany Makaruku