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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 Sisforma: Journal of Information Systems 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 Jurnal Algoritma 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)
Irwan Sembiring
Universitas Kristen Satya Wacana
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Consortium Blockchain Framework for Secure Digital Medical Record Innovation Sembiring, Irwan; Aji, Bintang Kristianto; Bayu, Teguh Indra
Aptisi Transactions On Technopreneurship (ATT) Vol 8 No 1 (2026): March
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v8i1.777

Abstract

Healthcare systems face growing challenges in protecting patient information, with more than 276 million healthcare records breached in 2024 alone. This study presents a proof-of-concept consortium blockchain framework that integrates Near Field Communication (NFC) based authentication with smart contract driven consensus to securely verify and synchronize Electronic Medical Records (EMRs) across multiple healthcare facilities. The system was tested in a simulated network of three Virtual Private Servers, achieving an average NFC verification time of 2.9 seconds and a consensus propagation time of 0.4 seconds, demonstrating stable performance suitable for near-real-time operations.Although these results are promising, the evaluation was limited to synthetic datasets, small-scale network conditions,and basic database security configurations. Future work will focus on scaling the system to larger and more diverse networks, strengthening cybersecurity measures, and ensuring full compliance with HIPAA and GDPR standards. By supporting the United Nations’3rd Sustainable Development Goal on Health and the 9th Sustainable Development Goal on Infrastructure and Innovation, this research contributes to the development of secure, interoperable, and sustainable healthcare information systems.
Tsunami Vulnerability and Risk Assessment in Banyuwangi District using machine learning and Landsat 8 image data Gallen cakra adhi wibowo; Sri Yulianto Joko Prasetyo; Irwan Sembiring
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 22 No. 2 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i2.2677

Abstract

The tsunami is a disaster that often occurs in Indonesia, there are no valid indicators to assess and monitor coastal areas based on functional land use and based on land cover which refers to the biophysical characteristics of the earth's surface. One of the recommended methods is the vegetation index. Vegetation index is a method from LULC that can be used to provide information on how severe the impact of the tsunami was on the area.In this study, an increase in the vegetation index was carried out using machine learning. The purpose of this study was to develop a tsunami vulnerability assessment model using the Vegetation Index extracted from Landsat 8 satellite imagery optimized with KNN, Random Forest and SVM. The stages of study, are: 1)extraction Landsat 8 images using algorithms NDVI, NDBI, NDWI, MSAVI, and MNDWI; 2) prediction of vegetation indices using KNN, Random Forest, and SVM algorithms. 3) accuracy testing using the MSE, RMSE, and MAE,4) spatial prediction using the Kriging function and 5) tsunami modelling vulnerability indicators. The results of this study indicate that the NDVI interpolation value is 0 - 0.1 which is defined as vegetation density, biomass growth, and moderate to low vegetation health. the NDWI value is 0.02 - 0.08 and the MNDWI value is 0.02 - 0.09 which is interpreted as the presence of surface water along the coast. MSAVI is a value of 0.1 – 0 which is defined as the absence of vegetation. The NDBI interpolation value is -0.05 - (-0.08) which is interpreted as the existence of built-up land with social and economic activities. From the results of research on the 10 areas studied, there are 3 areas with conditions that have a high level of tsunami vulnerability. 2 areas with medium vulnerability and 5 areas with low vulnerability to tsunami.
Analisis dan Desain Model UI/UX untuk Pengguna Manusia Lanjut Usia dalam Transformasi Bisnis Pertanian Digital Herdin Yohnes Madawara; Irwan Sembiring; Budhi Kristianto
JURNAL INFOTEL Vol 16 No 3 (2024): August 2024
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v16i3.1199

Abstract

Digital agriculture faces challenges, namely in integrating Elderly People (SENIORS) in digital transformation. The purpose of the study is to analyze and design UI/UX models according to user needs, expectations, and challenges. The method used is the Design Thinking approach which begins with literature study, then interviews are conducted to identify problems faced by users, and analyze the need to determine problem priorities. UI/UX prototypes are carried out to design solutions that suit user needs, and evaluations are carried out to collect user feedback. The data is assessed through the System Usability Scale (SUS) approach to appraise the designed user interface (UI). The evaluation results showed a "good" rating based on the SUS category, with a final average score of 74,391, so that the solutions designed meet usability standards for SENIORS users in the context of digital agriculture. Thus, the research carried out contributes to increasing the effectiveness and adoption of SENIORS in digital agriculture, as well as by designing user-friendly UI/UX models, making an important step towards inclusive and sustainable digital agriculture.
ANALISIS KESIAPAN TATA KELOLA DAN INVESTASISISTEM INFORMASI Kusumajaya, Robby Andika; Sembiring, Irwan; Iriani, Ade
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 8, No 2 (2019): Smart Comp :Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v8i2.1486

Abstract

Teknologi informasi menjadi salah satu bagian penting dalam perusahaan yang memberikan manfaat untuk meningkatkan efisiensi dan efektifitas proses bisnis, terutama di sektor pendidikan. Tujuan penelitian ini adalah menghasilkan rekomendasi mengenai kesiapan tata kelola teknologi informasi tepat gunadan investasi yang layak diimplementasikan pada Perguruan Tinggi XYZ. Permasalahan yang muncul disebabkan karena belum ada proses pemeriksaan mengenai kesesuaian standart sistem dan kesulitan dalam menghitung costbenefit yang diperoleh dari investasi sistem informasi. Penelitian ini menggunakan framework COBIT 5.0 domain DSS01, bertujuan memberikanrekomendasi tata kelola teknologi informasi pada bagian manage operation dan metode Information Economics untuk melakukan analisis manfaat investasi. Pengumpulan data dilakukan wawancara denganHead IT Operation dan beberapa staff. Hasil penelitian menggunakan COBIT5.0 domain DSS01, menunjukkan bahwa prosesmonitoring operasional yang diimplementasikan belum sepenuhnya dijalankan, yaitu sebesar 81%. Hasil analisis metode Information Economic, dampak ekonomis Enchanced ROImenyatakan bahwa nilai persentase simpleReturn on Investment sebesar 145,66% atau dengan skor 1, menunjukkan bahwa investasi ini memberikan keuntungan bagi perusahaan walaupun tidak besar.Kata Kunci: SistemInformasi, Tata Kelola, COBIT 5.0, Information Economics.
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.
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.
Number of Cyber Attacks Predicted With Deep Learning Based LSTM Model Joko Siswanto; Irwan Sembiring; Adi Setiawan; Iwan Setyawan
JUITA: Jurnal Informatika JUITA Vol. 12 No. 1, May 2024
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v12i1.20210

Abstract

The increasing number of cyber attacks will result in various damages to the functioning of technological infrastructure. A prediction model for the number of cyber attacks based on the type of attack, handling actions and severity using time-series data has never been done. A deep learning-based LSTM prediction model is proposed to predict the number of cyberattacks in a time series on 3 evaluated data sets MSLE, MSE, MAE, RMSE, and MAPE, and displays the predicted relationships between prediction variables. Cyber attack dataset obtained from kaggle.com. The best prediction model is epoch 20, batch size 16, and neuron 32 with the lowest evaluation value on MSLE of 0.094, MSE of 9.067, MAE of 2.440, RMSE of 3.010, and MAPE of 10.507 (very good model because the value is less than 15) compared other variations. There is a negative correlation for INTRUSION-MALWARE, BLOCKED-IGNORED, IGNORED-LOGGED, and LOW-MEDIUM. The predicted results for the next 12 months will increase starting from the second month at the same time. The resulting predictions can be used as a basis for policy and strategy decisions by stakeholders in dealing with fluctuations in cyber attacks that occur.
Optimizing Attendance System: Integrating Liveness Detection and Deep Learning for Reliable Face Recognition Joseph Teguh Santoso; Eko Sediyono; Kristoko Dwi Hartomo; Irwan Sembiring
JUITA: Jurnal Informatika JUITA Vol. 12 No. 2, November 2024
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v12i2.21738

Abstract

The study focuses on using vitality detection and deep learning technologies in the context of facial recognition in an IT presence management project. The combination of deep learning with vitality detection provides a considerable advancement in security and effectiveness. This work integrated vitality-detecting technology with in-depth learning in facial recognition systems. Vitality detection technologies are used to verify the authenticity of persons by examining live indicators such as movements or facial expressions before face recognition. Meanwhile, deep learning is used to analyze and process facial photos correctly by learning from large amounts of data and recognizing facial features in depth. The study data set consists of 1300 photographs of professional school instructors taken with official authority. Model testing and training are carried out in the Google Colab environment, using Python and the Hardy package. The test findings showed an 87% accuracy in face recognition, proving the system's capacity to consistently identify persons and distinguish real from false ones. Furthermore, the performance of Liveness Detection achieves 92% accuracy, as does the integration of Live Detection technology with Deep Learning at 78%.
PENGEMBANGAN APLIKASI PEMBELAJARAN IMERSIF BERBASIS VIRTUAL REALITY MENGGUNAKAN METODE MDLC DAN EVALUASI EUQ Jusia Amanda Ginting; Irwan Sembiring; I Gusti Ngurah Suryantara; Teady Matius Surya Mulyana; Ferry Alamsyah
Infotech: Journal of Technology Information Vol 11, No 2 (2025): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i2.426

Abstract

The advancement of technology in the field of Virtual Reality (VR) offers new opportunities for developing more interactive and immersive learning media. One of the main challenges in online learning is the low level of student engagement in the learning process, as well as the tendency for instructional methods to remain passive. Recognizing this gap and the need for a new technological approach that can encourage active participation, this study aims to develop a VR-based learning application called “FirstMetaClass”. This application is designed to simulate a virtual classroom environment to enhance students’ learning experiences. The application development process follows the Multimedia Development Life Cycle (MDLC) method. The quality of the user experience was evaluated using the Extended User Experience Questionnaire (EUQ). The respondents consisted of 42 university students who participated in the application trial and completed the evaluation questionnaire. The results of the study show that all EUQ dimensions achieved an average score above 4.0 on a 1–5 scale. These findings confirm that the “FirstMetaClass” application successfully provides a positive, engaging, and user-friendly learning experience, while creating a classroom atmosphere that closely resembles the real world and fosters a sense of presence for users.
Peningkatan Knowledge Capture dan Knowledge Sharing dalam KMS Tools dengan Kaizen Form Faisal Hakim Amrullah; Hendry; Irwan Sembiring
Jurnal Algoritma Vol 23 No 1 (2026): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.23-1.3409

Abstract

This study discusses the improvement of knowledge capture and knowledge sharing through the strengthening of a Kaizen-based Knowledge Management System (KMS) in the footwear manufacturing industry. The main problems include the suboptimal management of tacit knowledge and the limitations of document search based on simple keywords. This study applies an information retrieval method using TF-IDF and Cosine Similarity on 800 validated Kaizen documents through preprocessing, weighting, and document similarity measurement stages. The test results show that the proposed method performs better than conventional keyword-based search, with a precision value of 0.60, recall of 0.75, and F1-score of 0.67. The contribution of this study lies in the application of information retrieval methods to improve the effectiveness of knowledge retrieval in a Kaizen-based KMS, thereby supporting continuous improvement and organizational learning.
Co-Authors Abas Sunarya, Po Ade Iriani Adi Setiawan Adriyanto Juliastomo Gundo Agus Sugiarto Agustinus, Ari Aji, Bintang Kristianto 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 Candra Supriadi Daniawan, Benny Danny Manongga Danny Sebastian Dedy Prasetya Kristiadi Dwi Hosanna Bangkalang Dwi Setiawan Edi Suharyadi Efendy, Rifan Eka Purnama Harahap Eko Sediono Eko Sediyono Eleazer Gottlieb Julio Sumampouw Elmanda, Vonda Erick Alfons Lisangan Esti Zakia Darojat Evangs Mailoa Evi Maria Faisal Hakim Amrullah Faturahman, Adam Fauzi Ahmad Muda Ferry Alamsyah Fian Yulio Santoso Florentina Tatrin Kurniati Gallen cakra adhi wibowo Gerry Santos Lasatira Girinzio, Iqbal Desam Gudiato, Candra Hamdan . Hasnudi . Henderi Henderi . Hendry Hendry, - Henuk, Yusuf Leonard Herdin Yohnes Madawara Hidriyanto Dwi Purnomo Hindriyanto Dwi Purnomo Huda, Baenil I Gusti Ngurah Suryantara Ignatius Agus Supriyono Ilham Hizbuloh Indrastanti Ratna Widiasari Iwan Setiawan Iwan Setiawan Iwan Setyawan Iwan Setyawan Joko Listiawan Sukowati Joko Siswanto Jonas, Dendy Joseph Teguh Santoso Julians, Adhe Ronny Juneth Manuputty Jusia Amanda Ginting Krismiyati Kristoko Dwi Hartomo Kusumajaya, Robby Andika Limbong, Josua Josen Alexander Marsyel Sampe Asang Marvelino, Matthew Mau, Stevanus Dwi Istiavan Maya Sari Merryana Lestari Migunani Migunani Mira Mira Mira Mohammad Ridwan Muhamad Yusup Myra Andriana Nanle, Zeze Nazmun Nahar Khanom Nina Setiyawati Ninda Lutfiani Nining Fitriani Nugroho, Samuel Danny Nuryadi, Didik Nurzainah Ginting Pamungkas, Bayu Setyanto Phillnov Yohanes Pinontoan Pinontoan, Phillnov Yohanes Priatna , Wowon Purbaratri, Winny 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 Setiawan Hakim Sri Ngudi Wahyuni, Sri Ngudi Sri Yulianto Joko Prasetyo Suharyadi Sulistio Sulistio Sumampouw, Eleazer Gottlieb Julio Susanti, Novita Dewi Sutarto Wijono Suwijo Danu Prasetyo Teady Matius Surya Mulyana Teguh Indra Bayu Teguh Wahyono Theopillus J. H. Wellem Tintien Koerniawati Tio Nurtino Tirsa Ninia Lina Tomasoa, Lyonly Tri Wahyuningsih Tri Wahyuningsih Tukino, Tukino Untung Rahardja Untung Rahardja Wibowo, Mars Caroline Wijaya, Angga Zakharia Wiwien Hadikurniawati Wiwin Sulistyo Yerik Afrianto Singgalen Yessica Nataliani Yohan Maurits Indey Yohnes Madawara, Herdin Yolan Dita Dewi Pramudita Yulian Hany Makaruku