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All Journal Journal of Novel Engineering Science and Technology Jurnal Informatika dan Perancangan Sistem (JIPS)
David Jumpa Malem Sembiring
Institut Teknologi dan Bisnis Indonesia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Environmental Science Mechanical Engineering

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Perancangan Sistem Otomatisasi Peternakan Ayam Broiler Berbasis Internet Of Things Hendra; Maya Indriana; Nurul Tri Artika; Ricca Ismayani; David Jumpa Malem Sembiring; Melvarina Tamba
JURNAL INFORMATIKA DAN PERANCANGAN SISTEM (JIPS) Vol 5 No 1 (2023): Volume 5, No.1 Januari 2023
Publisher : Prodi Teknik Informatika (S1) Institut Teknologi dan Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (382.102 KB)

Abstract

Livestock is an activity to breed and cultivate livestock to get the benefits and results of these activities. Therefore we need a system that is able to help control feeding and drinking and regulate temperature humidity . The technology that can be used is internet of things technology which is a technology that allows physical objects to communicate with each other via the internet. This farm system uses 4 sensors that function to detect temperature, light, feed availability, and drinking availability. and using Arduino 328 as a microcontroller which functions to control an input output from a system designed to process input data from sensors. the test results show that the system is able to provide information through the android application if a vacancy is detected in the feed and drink place as well as temperature humidity control.
Sistem Pengendalian Kamera Jarak Jauh Terintegrasi Internet Of Things Ahzarina Safura; Andri Jabal Nur; Devi Ayu Lestari; Siti Khairiyah; David Jumpa Malem Sembiring; Meiliyani Br. Ginting
JURNAL INFORMATIKA DAN PERANCANGAN SISTEM (JIPS) Vol 5 No 1 (2023): Volume 5, No.1 Januari 2023
Publisher : Prodi Teknik Informatika (S1) Institut Teknologi dan Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (531.211 KB)

Abstract

The camera is a set of tools that aim to help human needs in the field of photo and video, today's photographers and videographers need sophisticated equipment and can help make taking pictures easier One of the benefits of this remote camera motion control system is that it functions to move the camera using a smartphone without having to be controlled manually by holding it. Based on this, an Internet of Things Integrated Remote Camera Control System will be built. This camera control system uses sensors that function to detect proximity to objects, and uses Arduino 328 as a microcontroller which functions to process input data from sensors. The test results show that the system is able to control the camera via Android at the time of retrieval of documentation as we want.
Federated Quantum Machine Learning for Secure Multi-Party Genomic Data Analysis: A Hybrid Architecture with Differential Privacy David Jumpa Malem Sembiring; Sinek Mehuli Br Perangin Angin
Journal of Novel Engineering Science and Technology Vol. 5 No. 01 (2026): Journal of Novel Engineering Science and Technology
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/jnest.v5i01.1087

Abstract

The exponential growth of genomic data has created opportunities for collaborative biomedical research while posing significant privacy and security challenges. Traditional centralized machine learning approaches risk data breaches and regulatory non-compliance. This study proposes a novel hybrid architecture combining Federated Quantum Machine Learning (FQML) with Differential Privacy (DP) for secure multi-party genomic data analysis. Our simulated framework enables institutions to collaboratively train quantum machine learning models on distributed genomic datasets without exposing sensitive data. Using variational quantum circuits within a federated learning framework, we implement privacy-preserving models across three simulated genomic data silos. Gaussian noise injection via DP mechanisms during gradient updates ensures formal privacy guarantees (ε = 0.85). Experimental results on synthetic datasets demonstrate that FQML achieves 93.4% predictive accuracy in genome-wide association studies simulation, outperforming classical federated models in convergence speed by 27% and reducing communication overhead by 19%. These findings suggest FQML with DP provides a promising foundation for future secure genomic collaboration, though real-world validation remains necessary.
Co-Authors Ahzarina Safura Andri Jabal Nur Devi Ayu Lestari Hendra Maya Indriana Meiliyani BR. Ginting Melvarina Tamba Nurul Tri Artika Ricca Ismayani Sinek Mehuli Br Perangin Angin Siti Khairiyah