Article Per Year (5 Year)
p-Index From 2021 - 2026
6.902
P-Index
This Author published in this journals
All Journal TEKNIK Jurnal Teknologi dan Manajemen Informatika Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL LENTERA : Kajian Keagamaan, Keilmuan dan Teknologi JOURNAL OF APPLIED INFORMATICS AND COMPUTING Dinamisia: Jurnal Pengabdian Kepada Masyarakat Jurnal Sisfokom (Sistem Informasi dan Komputer) Technomedia Journal Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Capture : Jurnal Seni Media Rekam Building of Informatics, Technology and Science Jurnal ABDINUS : Jurnal Pengabdian Nusantara TEPIAN Jurnal Teknik Informatika (JUTIF) Business Economic, Communication, and Social Sciences Journal (BECOSS) Jurnal ABDIMAS (Pengabdian kepada Masyarakat) UBJ Jurnal Pendidikan dan Teknologi Indonesia Jurnal Locus Penelitian dan Pengabdian Eduvest - Journal of Universal Studies Jurnal Indonesia : Manajemen Informatika dan Komunikasi The Indonesian Journal of Computer Science
Santoso, Handri
Unknown Affiliation
Religion Aerospace Engineering Arts Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Neuroscience Social Sciences Other

Published : 53 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 53 Documents
Search

 1   2   3   4   5 
DEVELOPMENT OF INDEPENDENT TAEKWONDO TRAINING MACHINE LEARNING WITH 3D POSE MODEL MEDIAPIPE Santoso, Billy Cahyo; Santoso, Handri; Sandjaya, Julio
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 3 (2023): Article Research Volume 7 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.12571

Abstract

Taekwondo is a martial art that focuses on punching and kicking movements while upholding the values of discipline, ethics, and good behavior. Discipline is built with routine training to make someone proficient in taekwondo martial arts. Training cannot be carried out flexibly because it must be accompanied by a sabouem to know the correct taekwondo movements. Machine learning can be used as a solution for taekwondo movement recognition by building a learning machine model that recognizes the correct taekwondo movement. The MediaPipe framework has the advantage of being able to recognize human posture with 33 points or landmarks. The research was carried out by conducting a literature study, where similar research was found but only based on the values of the x and y axes. So a problem arises where the majority of taekwondo movements require the z axis to know the correct taekwondo movements. The research was conducted to add z-axis values and change calculations, which were adjusted to reconstruct a training data object in the form of an image into a three-dimensional shape. From this study, it was found that machine learning using the x, y, and z axes is much better for its use, especially when detecting taekwondo movements from different viewpoints from the training data. This research can be developed by enlarging the image dataset and packaging the model into a mobile application so that it can be used for taekwondo training up to taekwondo movement assessment.
Performance Comparison between Signature Cryptography: A Case Study on SNAP Indonesia Ramadhoni, Moehammad; Santoso, Handri
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.12819

Abstract

SNAP (Standar Nasional OPEN API Pembayaran) was submitted by several sub-working groups formed jointly by ASPI and the Bank of Indonesia for encouraging digital transformation in the banking industry. In the document Pedoman Tata Kelola (Bank of Indonesia, n.d.), there is the use cryptographic algorithms that are used as validation for third parties to use the Open API. The algorithms used in the document are HMAC and RSA. The third party will send the signature in the API header along with the sent API payload. The signature describes the body payload, the endpoint URL that was called by the third party, and the time when the API call was made, so the signature will change all the time. However, there are other algorithms that can be used as a form of validation, such as ECC and ZK-SNARK. In this journal, the performance of the four cryptographic algorithms is compared. The performance we compare is overall speed when creating the signature and verifying it. The result is that HMAC is the most efficient algorithm, but for financial data, it is better to use ECC which uses asymmetric keys and is faster than RSA contained in the SNAP document, especially when 256 bits security level that ECC could be 10 times faster then RSA.
PyTorch Deep Learning for Food Image Classification with Food Dataset Iswahyudi, Iswahyudi; Hindarto, Djarot; Santoso, Handri
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.12987

Abstract

Classification of food images is crucial in today's increasingly digitally connected world. In the rapidly evolving mobile applications and social media era, the demand for an automated system that can recognize food types from an image is intensifying. This study employs deep learning and the PyTorch framework to develop a dependable and efficient solution for classifying food images. This research is motivated by the growing complexity of food introduction challenges. The primary challenge is improving the accuracy of food type recognition and overcoming variations in the visual presentation of food, such as lighting, shooting angles, and proportional and textural differences. Convolutional Neural Networks (CNN) are effective for image classification and are incorporated into the methods utilized. In addition, we employ ResNet101 transfer learning techniques to capitalize on the knowledge of trained models for large image datasets. The primary objective of this study is to develop a food image classification model that is accurate, training-efficient, and capable of accurately recognizing various types of food. In testing and evaluation, the developed model could realize multiple types of food with satisfactory accuracy. The accuracy of training reached 99.35%, while the accuracy of testing reached 94.65%. This study also reveals how Resnet101 transfer learning is utilized by deep learning technology.
Designing Claim Systems in Health Insurance Companies with Microservices and Event-Driven Architecture Approach Sentosa, Steve; Makmur, Amelia; Santoso, Handri
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 3 (2024): Research Artikel Volume 8 Issue 3, July 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.13677

Abstract

Through digital transformation, insurance companies, especially in the health sector, are increasingly adopting modern technologies to enhance efficiency and service quality. Health insurance allows individuals or families to mitigate the financial risks associated with high and unexpected medical expenses. One crucial area is insurance claim, where a fast and accurate process is key to customer satisfaction. This study proposes the design and architecture of an insurance claim system using a microservices and event-driven approach. This approach enables insurance companies to break down applications into separate components, facilitating scalability, flexibility, and easier maintenance. Additionally, with an event-driven approach, the system can quickly respond to changes and events in the business environment. A comprehensive analysis shows that implementing microservices and event-driven architecture in the insurance claim system can enhance overall system performance, scalability, and resilience. For insurance companies, adopting microservices and event-driven architecture can lead to increased operational efficiency, reduced time to market for new products, and improved customer experiences through faster claim processing. Policyholders will benefit from quicker claim resolutions and a more transparent and responsive claim process. This study provides valuable insights for health insurance companies looking to upgrade their IT infrastructure to meet future challenges. The findings from this research will be documented to support the development of insurance business technology, specifically for health insurance claims in Indonesia.
CLASSIFYING VILLAGE FUND IN WEST JAVA, INDONESIA USING CATBOOST ALGORITHM Harriz, Muhammad Alfathan; Akbariani, Nurhaliza Vania; Setiyowati, Harlis; Santoso, Handri
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 4 No. 2 (2023): Mei
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v4i2.269

Abstract

With over 261 million inhabitants, Indonesia is home to approximately 15,000 villages, according to the Ministry of Villages, Disadvantaged Regions, and Transmigration. Among these, 1,406 are in West Java. Of these, 504 of them are advanced, 464 are developing, 390 are disadvantaged, and 48 are very disadvantaged. The CatBoost machine learning model was used to classify village funds in West Java from 2018 to 2021 and had an accuracy rating of 75%, precision rating of 79%, recall of 79%, and f1 score of 79%, demonstrating its excellent performance. However, missing data points had to be removed from the analysis and it is suggested that a more sophisticated method for handling missing values should be used in future studies. In addition, hyperparameter tuning could be employed to increase the model's performance, and a variety of metrics could be used to accurately assess the results. Overall, CatBoost may be of benefit to the Indonesian Government in order to classify village funds according to their status, channel funds more accurately and efficiently, and observe the situation of a village year-over-year.
Analisis Kombinasi Teknologi Baru Pengembangan Aplikasi Pengantar Makanan Pada Digital IT Service Melalui Workflow Dan Process Automation Ruddin, Isra; Santoso, Handri; Indrajit, Richardus Eko; Dazki, Erick
JURNAL LENTERA : Kajian Keagamaan, Keilmuan dan Teknologi Vol 21 No 1 (2022): Maret 2022
Publisher : LP2M STAI Miftahul 'Ula (STAIM) Nganjuk

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29138/lentera.v21i1.626

Abstract

Penyedia layanan pengiriman makanan dapat dikategorikan sebagai Pengiriman Restoran-ke- Konsumen atau operasi pengiriman Platform-ke-Konsumen. Penyedia Pengiriman Restoran-ke- Konsumen membuat makanan dan mengirimkannya, seperti yang ditunjukkan oleh penyedia, seperti KFC, McDonald's, Pizza Hut dan lainnya. Urutan dapat dibuat langsung melalui platform online. Food Delivery Online membutuhkan layanan pengiriman real-time yang sangat efisien dan dapat diskalakan. Kombinasi dari teknologi baru memberikan kesan yang besar jumlah peluang bisnis bagi para pengusaha. Pada bagian ini menargetkan untuk menunjukkan konvergensi teknologi baru ini dalam dimensi bisnis dan mengeksplorasi titik sayatan untuk perusahaan rintisan di masa depan melalui contoh spesifik mobil self-driving. IoT memecahkan masalah konektivitas, yang berarti perangkat pintar yang berbeda di masa depan bisa mendapatkan terhubung dan bertukar data satu sama lain. AI sangat meningkatkan tingkat otomatisasi mesin sehingga mereka dapat melakukan tugas yang sama seperti manusia. Persimpangan AI dan IoT tidak bisa lagi dipandang sebelah mata dan efek sinergi di antara mereka sangat menjanjikan. Pengusaha dengan latar belakang bisnis yang lebih tradisional memberikan peringkat yang lebih tinggi pada bagian saluran. Di sektor tradisional, saluran dapat dipandang sebagai aset penting dalam operasi bisnis. Perusahaan yang memiliki saluran distribusi premium dapat diberkahi dengan keunggulan luar biasa dalam persaingan pasar, dan pola pikir seperti itu akan diwariskan kurang lebih dalam kegiatan bisnis berikut. Berbeda dengan sektor tradisional, saluran masuk ekonomi baru biasanya transparan. Sama seperti di E-commerce atau industri digital, media internet bagi semua perusahaan untuk menjangkau pelanggan
Building an Automated Guided Vehicle Based on UWB Technology Haryono; Santoso, Handri
The Indonesian Journal of Computer Science Vol. 13 No. 6 (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.v13i6.4487

Abstract

The development of automated guided vehicles (AGVs) for indoor environments necessitates precise positioning technology to enable accurate navigation within confined spaces. Ultra-Wideband (UWB) technology has proven to be a leading solution for this purpose, known for its high accuracy, low latency, and resilience to interference. This study presents a specialized approach to AGV localization within a room, utilizing UWB technology to achieve reliable movement and positioning. We conducted a comparative analysis of two UWB modules, DWM1000 and DWM1001, evaluating their performance and suitability for AGV applications. Although both modules provide high accuracy, the DWM1001 was chosen due to its integrated microcontroller, simplified setup, and enhanced compatibility with indoor navigation. The DWM1001’s efficient integration and power management make it ideal for environments requiring precise and dependable AGV operation. This paper details the methodology for selecting the DWM1001 and demonstrates how it enables robust AGV navigation with minimal drift, achieving a positioning accuracy of approximately 10 cm—an acceptable margin for indoor applications. Through rigorous testing and evaluation, we observed consistent performance, validating the DWM1001 as an effective solution for small-scale AGV systems. This approach not only provides a reliable foundation for deploying UWB technology in compact indoor settings but also addresses a gap in current research on high-precision, small-scale AGV localization.
USER EXPERIENCE IN METAVERSE BUILDING TRAINING USING PHOENIX-FIRESTORM SOFTWARE Magdalena, Maria; Indrajit, Richardus Eko; Santoso, Handri; Sari, Muh Masri
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 1 (2025): JUTIF Volume 6, Number 1, February 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.1.3447

Abstract

This study aims to evaluate the effectiveness of training using Phoenix-Firestorm software in a 3D virtual environment (metaverse) for teachers, lecturers, and students. A total of 49 participants were involved in the online training consisting of seven sessions, facilitated through the Discord platform for voice communication. Each participant was given a virtual area of 35x35 meters for practice, with daily guidance via Discord chat. The training was designed to equip participants with basic skills in building 3D objects, including an understanding of the software and building techniques. After the training, a survey was conducted using a Likert scale of 1-9 to assess participants' understanding of navigation, software customization, virtual communication, and problem-solving. The survey results showed that the majority of participants found Phoenix-Firestorm relatively easy to use, although some challenges were reported regarding the complexity of the interface. These findings will be used as a basis for developing more effective and user-friendly training guidelines in the future, with a focus on improving accessibility and user experience in the context of technology-based learning. This study is in line with previous studies that show the potential of virtual worlds in education, as discussed by Jusuf (2023). Additionally, the use of virtual technology in education is also supported by research on the effectiveness of virtual learning environments, as explained by Wang et al (2022), that digital games contributed to a moderate overall effect size when compared with other instructional methods. These findings are expected to make a significant contribution to the development of innovative training methods in education in the digital era.
Machine Health in a Click: A Website for Real-Time Machine Condition Monitoring Rochadiani, Theresia Herlina; Santoso, Handri; Aprilia, Novia Pramesti; Laurenso, Justin; Suhandi, Vartin
The Indonesian Journal of Computer Science Vol. 12 No. 6 (2023): 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.v12i6.3592

Abstract

Globalization in the current digital era has made it easier to use information technology to obtain fast and accurate information. One source of information is a website that can be used to monitor machine conditions in the industry. A good machine maintenance strategy is needed to maintain and increase machine productivity. Therefore, this research aims to build a website to monitor machine conditions in real-time. The machine condition is monitored using sushi sensors to track parameters such as temperature, acceleration, and velocity. Deep learning analysis is then used to identify anomalies in the machine. Using the SCRUM method, this website was successfully built. From the results of tests carried out using unit testing and integrated testing, every feature on this website can run well and according to user needs.
Boosting Electronics Manufacturing Efficiency with Automated Data Mining and OEE Process Analytic Sumargo, Ruly; Santoso, Handri
Jurnal Teknologi dan Manajemen Informatika Vol. 10 No. 1 (2024): Juni 2024
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v10i1.11377

Abstract

In the last few decades, the industrial sector has experienced rapid growth, driven by increasing demand and intense competition among manufacturers, especially in the electronics sector. This competition focuses on providing superior products with competitive prices, maintained quality, and optimal delivery times. Optimizing manufacturing processes and effectively utilizing company resources have become key to competitiveness in the manufacturing industry. To ensure comprehensive optimization and smooth manufacturing workflows, it is crucial to engage in systematic evaluation and analytical processes. One of the key performance metrics in assessing manufacturing process efficiency is Overall Equipment Efficiency (OEE), which is used to uncover improvement opportunities and inefficient areas. Accurate OEE measurement requires a data mining systems with automated quantitative data collection methods and real-time calculations. These systems visualize process losses in six (pareto) groups, aiding users in analyzing processes and determining process improvements. The implementation of OEE and alert systems for management can bring an 11.82% increase in overall production efficiency. This achievement can serve as a model for other companies embarking on the initial stages of digital transformation processes.
Co-Authors Agus Anwar Agustiana, Puspa Riri Akbar, Achmad Fathurrazi Akbariani, Nurhaliza Vania Amanda, Djaja Andrew Andrew, Andrew Andriani, Febri Anggraini, Astria Febrian Aprilia, Novia Pramesti Dazki, Erick Devanda, Faustin Eko Hadianto, Eko Firmansah, R Arif Fransisca, Viviana Han, Hanif Harlis Setiyowati HARYONO Heni Jusuf Hindarto, Djarot Ho, Patricia Indrajit, Eko ISWAHYUDI ISWAHYUDI Ito Wasito Karjadi, Daniel Avian Karjadi, Markus Laurenso, Justin Lijaya, Hendra Lucia Sri Istiyowati Lupitha, Mariska Mareta, Arvin Maria Magdalena Mayatopani, Hendra Mohammad, Saiful Azhari Muhammad Alfathan Harriz Nana Sutarna Panna, Ariya Perdana, Nanda Praharto, Suwandhy Prawira, Khairul Thamrin Prijantono, Sonny Priswanto, Budi Purwadi Purwadi Purwadi Putri, Gladys Rahman, Ben Ramadhoni, Moehammad Richardus Eko Indrajit Rochadiani, Theresia Herlina Ruddin, Isra Sakti, Irwin Sandjaya, Julio Santoso, Billy Cahyo Saputra, Adi Dwifana Sari, Muh Masri Sentosa, Steve Sucipto, Nadya Rudie Suhandi, Vartin Suherman, Endang Sumargo, Ruly Sze, Edward Tauhid, Tauhid Teddy Mantoro Wedha, Alessandro Enriqco Putra Bayu Wedha, bayu Yasa Widjaja, Herman Wijaya, Oktavianus Hendry