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All Journal Bulletin of Electrical Engineering and Informatics PROSIDING CSGTEIS 2013 EMITTER International Journal of Engineering Technology JOIV : International Journal on Informatics Visualization INOVTEK Polbeng - Seri Informatika J-Dinamika: Jurnal Pengabdian Kepada Masyarakat GUYUB: Journal of Community Engagement The Indonesian Journal of Computer Science
Idris Winarno
Politeknik Elektronika Negeri Surabaya
Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences Other

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QR Code-Based Smart Document Implementation Using Distributed Database And Digital Signature Ayub, Waqas; Winarno, Idris; Sudarsono , Amang
The Indonesian Journal of Computer Science Vol. 13 No. 1 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i1.3673

Abstract

In digitized world, digital documents are essential for information sharing. However, some organizations continue to place their reliance in traditional hard-copy formats concerning about the legitimacy of documents. This study presents an innovative approach to document verification with digital signatures, distributed databases, and QR codes. Using a two-step process for data integrity and document authentication, the study approach entails developing a Smart Document with a QR code and digital signature. For increased security and scalability, the system design distributes hash fragments among several databases using the hash split approach. The system's excellent performance, resistance to sluggish HTTP-based attacks, and effectiveness in document verification are highlighted by the results and debates. The report ends with recommendations for future improvements to strengthen the system's resilience, like implementing more secure database engines and enhancing fault tolerance. In conclusion, this method offers a viable way to verify documents in hardcopy and electronic formats in a secure and scalable manner.
Event-driven integration of electronic medical records with blockchain and InterPlanetary file system Arissabarno, Cahyo; Sukaridhoto, Sritrusta; Winarno, Idris; Putri Nourma Budiarti, Rizqi
Bulletin of Electrical Engineering and Informatics Vol 14, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i3.9355

Abstract

The integrity, security, and accessibility of electronic medical record (EMR) are often compromised by traditional systems, which struggle to ensure data integrity, transparent audit trails, and secure long-term storage. This research addresses these challenges by integrating EMR with a private blockchain and InterPlanetary file system (IPFS) cluster, using change data capture (CDC) for real-time updates and integrate with existing EMR systems, avoiding the need for building new EMR software. Implemented in the OpenEMR framework, the system's performance is evaluated across various processes, including document uploading, sharing, access, deletion, and integrity verification. Testing with anonymized medical records in PDF formats ranging from 1 MB to 100 MB shows that uploading to IPFS takes 0.7 seconds per MB, blockchain transaction processing averages 4.2 seconds, CDC time is 1.1 seconds per MB, and OpenEMR uploads average 0.98 seconds per MB. These results demonstrate significant improvements in data security, integrity, and availability, following the CIA triad principles. The system provides a traceable and secure solution for EMR management.
Cloud Computing-based Shrimp Pond Water Quality Prediction Intelligent Service System Suasono, Zaikhul Sulthon; Setiawardhana, Setiawardhana; Winarno, Idris; Gunawan, Agus Indra
JOIV : International Journal on Informatics Visualization Vol 9, No 4 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.4.2862

Abstract

Maintaining water quality is an essential factor in the success of shrimp farming, particularly in conventional and semi-intensive methods in Indonesian. Poor water quality will affect shrimp's survival, reproduction, development, and harvest yield. In order to furnish data regarding future water quality conditions, This research aims to create an intelligent cloud-based water quality prediction system for shrimp ponds that can provide accurate predictions regarding future water quality conditions. The system utilizes the WQI dataset gathered from four different shrimp farming sites, totaling 408 samples, each location exhibiting a different set of values. The model will be trained using four parameters: pH, DO, salinity, and temperature. The WQI dataset will be pre-processed to address missing data, outliers, and standardization. The water quality prediction model uses three machine learning algorithms: SVM, ANN, and MLR. The model's performance results are evaluated using MAE, RMSE, and R². The results indicate that the ANN model is the most effective, achieving an MAE: 0.4023, RMSE: 0.5336, and R²: 0.7178 for temperature predictions, and an MAE: 0.4080, RMSE: 0.5942, and R²: 0.5997 for salinity. The SVM model had mixed results for temperature, with an MAE: 0.3645 and RMSE: 0.4823, but it performed poorly for DO, as evidenced by a negative R² of -0.2428. The MLR model provided reasonable temperature predictions MAE: 0.4953, RMSE: 0.6370, R²: 0.5602. Subsequent research endeavors should prioritize the augmentation of the dataset size and the incorporation of temporal dimensions in order to enhance the precision of predictive outcomes.
A Heterogeneous Hybrid Cloud Storage Service Using Storage Gateway with Transfer Acceleration and Diff Algorithm Jamal Abdul Nasyir; Idris Winarno; Udin Harun Al-Rasyid
The Indonesian Journal of Computer Science Vol. 11 No. 2 (2022): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v11i2.3071

Abstract

Recently, the cloud service has the potential to replace conventional cluster and grid systems. The objective of migrating apps to the cloud is to minimize maintenance and procurement expenses while simultaneously boosting scalability and availability. However, embra=cing cloud technology created some challenges, such as the complexity of cloud storage. In addition, many clients underestimate if it is not plug-and-play. Each vendor has its access methods, and nonstandard application programming interfaces (APIs) make integrated applications, such as archiving or sharing data with cloud storage, complicated, costly, and require high throughput. Furthermore, organizations did not have many alternatives for implementing high-performance object storage systems in the cloud and on-premises data centers until now. In this paper, we would like to suggest a storage gateway as a solution to this issue and will optimize it using Transfer Acceleration and Diff algorithms to improve the performance, Intelligent Tiering to reduce costs, and Server-Side encryption for extra protection. Moreover, utilizing Storage Gateway has proven can provide more efficient integration between the on-premises data center environment and the AWS Cloud Storage ecosystem that is safer and more reliable. This technology can work in a common data center environment regardless of the vendor used by the company it can communicate seamlessly with the AWS Environment.
Distributed Aerial Image Stitching on Multiple Processors using Message Passing Interface Ramadhan, Alif Wicaksana; Aulia, Fira; Dewi, Ni Made Lintang Asvini; Winarno, Idris; Sukaridhoto, Sritrusta
JOIV : International Journal on Informatics Visualization Vol 8, No 1 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.1.1890

Abstract

This study investigates the potential of using Message Passing Interface (MPI) parallelization to enhance the speed of the image stitching process. The image stitching process involves combining multiple images to create a seamless panoramic view. This research explores the potential benefits of segmenting photos into distributed tasks among several identical processor nodes to expedite the stitching process. However, it is crucial to consider that increasing the number of nodes may introduce a trade-off between the speed and quality of the stitching process. The initial experiments were conducted without MPI, resulting in a stitching time of 1506.63 seconds. Subsequently, the researchers employed MPI parallelization on two computer nodes, which reduced the stitching time to 624 seconds. Further improvement was observed when four computer nodes were used, resulting in a stitching time of 346.8 seconds. These findings highlight the potential benefits of MPI parallelization for image stitching tasks. The reduced stitching time achieved through parallelization demonstrates the ability to accelerate the overall stitching process. However, it is essential to carefully consider the trade-off between speed and quality when determining the optimal number of nodes to employ. By effectively distributing the workload across multiple nodes, researchers and practitioners can take advantage of the parallel processing capabilities offered by MPI to expedite image stitching tasks. Future studies could explore additional optimization techniques and evaluate the impact on speed and quality to achieve an optimal balance in real-world applications.
High-Performance Computing on Agriculture: Analysis of Corn Leaf Disease Fajrianti, Evianita Dewi; Pratama, Afis Asryullah; Nasyir, Jamal Abdul; Rasyid, Alfandino; Winarno, Idris; Sukaridhoto, Sritrusta
JOIV : International Journal on Informatics Visualization Vol 6, No 2 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.2.793

Abstract

In some cases, image processing relies on a lot of training data to produce good and accurate models. It can be done to get an accurate model by augmenting the data, adjusting the darkness level of the image, and providing interference to the image. However, the more data that is trained, of course, requires high computational costs. One way that can be done is to add acceleration and parallel communication. This study discusses several scenarios of applying CUDA and MPI to train the 14.04 GB corn leaf disease dataset. The use of CUDA and MPI in the image pre-processing process. The results of the pre-processing image accuracy are 83.37%, while the precision value is 86.18%. In pre-processing using MPI, the load distribution process occurs on each slave, from loading the image to cutting the image to get the features carried out in parallel. The resulting features are combined with the master for linear regression. In the use of CPU and Hybrid without the addition of MPI there is a difference of 2 minutes. Meanwhile, in the usage between CPU MPI and GPU MPI there is a difference of 1 minute. This demonstrates that implementing accelerated and parallel communications can streamline the processing of data sets and save computational costs. In this case, the use of MPI and GPU positively influences the proposed system.
Automatic Representative News Generation using On-Line Clustering Sigita, Marlisa; Barakbah, Ali Ridho; Kusumaningtyas, Entin Martiana; Winarno, Idris
EMITTER International Journal of Engineering Technology Vol 1 No 1 (2013)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (8313.353 KB) | DOI: 10.24003/emitter.v1i1.11

Abstract

The increasing number of online news provider has produced large volume of news every day. The large volume can bring drawback in consuming information efficiently because some news contain similar contents but they have different titles that may appear. This paper presents a new system for automatically generating representative news using on-line clustering. The system allows the clustering to be dynamic with the features of centroid update and new cluster creation. Text mining is implemented to extract the news contents. The representative news is obtained from the closest distance to each centroid that calculated using Euclidean distance. For experimental study, we implement our system to 460 news in Bahasa Indonesia. The experiment performed 70.9% of precision ratio. The error is mainly caused by imprecise results from keyword extraction that generates only one or two keywords for an article. The distribution of centroid’s keywords also affects the clustering results.Keywords: News Representation, On-line Clustering, Keyword Aggregation, Text Mining.
Automatic Backup System for Virtualization Environment Winarno, Idris; Sani, Muzaki Nurus
EMITTER International Journal of Engineering Technology Vol 2 No 1 (2014)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (10037.285 KB) | DOI: 10.24003/emitter.v2i1.20

Abstract

Virtualization is a technology lately much discussed and considered as the proper way to cut costs in the construction of a data center. One example of the implementation of virtualization technologies is to using VMware. Another tools for virtualization are Xen and OpenVZ, but VMware is more flexible than Xen or OpenVZ because VMware can run a variety of operating systems. Although it has the advantage, virtualization technology also has a vital weakness, virtualization technologies could be analogous by putting all the eggs in a basket. This means that if the master server problem, all systems inside the virtual machine can not be used. However, it can be anticipated by provide backup facilities that run continually and automatically. VMware itself has had an application to backup/replicate virtual machines. However, that application is not free yet.This research has been design and creates a web-based software forbacking up virtual machines on VMware. So it made easier for users and admins to perform periodic backups of virtual machines. From the test results has been done, it can be seen that used disk type thin or zeroed thick make process backup faster, system can’t work well when virtual machine has snapshot, scheduling system and restoring system has worked well, physical ability data storage influence system.Keywords: Virtual machine, virtualization, Vmware, Backup, Data Center.
Towards a Resilient Server with an external VMI in the Virtualization Environment Utomo, Agus Priyo; Winarno, Idris; Syarif, Iwan
EMITTER International Journal of Engineering Technology Vol 8 No 1 (2020)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v8i1.468

Abstract

Currently, cloud computing technology is implemented by many industries in the world. This technology is very promising due to many companies only need to provide relatively smaller capital for their IT infrastructure. Virtualization is the core of cloud computing technology. Virtualization allows one physical machine to runs multiple operating systems. As a result, they do not need a lot of physical infrastructures (servers). However, the existence of virtualization could not guarantee that system failures in the guest operating system can be avoided. In this paper, we discuss the monitoring of hangs in the guest operating system in a virtualized environment without installing a monitoring agent in the guest operating system. There are a number of forensic applications that are useful for analyzing memory, CPU, and I/O, and one of it is called as LibVMI. Drakvuf, black-box binary analysis system, utilizes LibVMI to secure the guest OS. We use the LibVMI library through Drakvuf plugins to monitor processes running on the guest operating system. Therefore, we create a new plugin to Drakvuf to detect Hangs on the guest operating system running on the Xen Hypervisor. The experiment reveals that our application is able to monitor the guest operating system in real-time. However, Extended Page Table (EPT) violations occur during the monitoring process. Consequently, we need to activate the altp2m feature on Xen Hypervisor to by minimizing EPT violations.
Student Behavior Analysis to Predict Learning Styles Based Felder Silverman Model Using Ensemble Tree Method Ikawati, Yunia; Al Rasyid, M. Udin Harun; Winarno, Idris
EMITTER International Journal of Engineering Technology Vol 9 No 1 (2021)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v9i1.590

Abstract

Learning styles are very important to know so that students can learn effectively. By understanding the learning style, students will learn about their needs in the learning process. One of the famous learning management systems is called Moodle. Moodle can catch student experiences and behaviors while learning and store all student activities in the Moodle Log. There is a fundamental issue in e-learning where not all students have the same degree of comprehension. Therefore, in some cases of learning in E-Learning, students tend to leave the classroom and lack activeness in the classroom. In order to solve these problems, we have to know students' preferences in the learning process by understanding each student's learning style. To find out the appropriate student learning style, it is necessary to analyze student behavior based on the frequency of visits when accessing Moodle E-learning and fill out the Index Learning Style (ILS) questionnaire. The Felder Silverman model's learning style classifies it into four dimensions: Input, Processing, Perception, and Understanding. We propose a learning style prediction model using the Ensemble Tree method, namely Bagging and Boosting-Gradient Boosted Tree. Afterwards, we evaluate the classification results using Stratified Cross Validation and measure the performance using accuracy. The results showed that the Ensemble Tree method's classification efficiency has higher accuracy than a single tree classification model.
Co-Authors Abd. Rasyid Syamsuri Afifah, Izza Nur Ali Ridho Barakbah Amang Sudarsono, Amang Arissabarno, Cahyo Arna Fariza Ata Amrullah Aulia, Fira Ayub, Waqas Bambang Sumantri Bima Sena Bayu Dewantara Budiarti, Rizqi Putri Nourma Dadet Pramadihanto Dewi, Ni Made Lintang Asvini Entin Martiana Kusumaningtyas Fajrianti, Evianita Dewi Gunawan, Agus Indra Hamida, Silfiana Nur Hary Oktavianto Huda, Achmad Thorikul Ikawati, Yunia iwan Syarif Jamal Abdul Nasyir Jamal Abdul Nasyir M Udin Harun Al Rasyid, M Udin Harun Marlisa Sigita, Marlisa Muhammad Alfian Muzaki Nurus Sani, Muzaki Nurus Nasyir, Jamal Abdul Nurazmi, Talita Iza Pratama, Afis Asryullah Primajaya, Grezio Arifiyan Rachmawati, Oktavia Citra Resmi Ramadhan, Alif Wicaksana Rasyid, Alfandino Rudi Kurniawan Sesulihatien, Wahjoe Tjatur Setiawardhana, Setiawardhana Suasono, Zaikhul Sulthon Sudarsono , Amang Susanti, Puspasari Tessy Badriyah, Tessy Tri Harsono Udin Harun Al-Rasyid Udin Harun Al-Rasyid Utomo, Agus Priyo Wahjoe Tjatur Sesulihatien Wiratmoko Yuwono