Article Per Year (5 Year)
p-Index From 2021 - 2026
2.679
P-Index
This Author published in this journals
All Journal Jurnal Pekommas Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer International Journal of New Media Technology Jurnal ULTIMATICS KOMPUTIKA - Jurnal Sistem Komputer Jurnal Sistem Cerdas Jurnal Teknologi Informasi dan Terapan (J-TIT) Jurnal Teknologi Informasi dan Multimedia Jurnal Teknokes Journal of Community Development J-SAKTI (Jurnal Sains Komputer dan Informatika) International Journal of Public Health Excellence (IJPHE) The International Journal of Studies in Social Sciences and Humanities (IJOSSH)
Arvita Agus Kurniasari
Department Of Information Technology, Politeknik Negeri Jember, Jember, Indonesia
Aerospace Engineering Arts Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Public Health Social Sciences

Published : 14 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 14 Documents
Search

 1   2 
Pelatihan Pengemasan Sayur Hidroponik dan Pemasaran Berbasis Multimedia Sebagai Upaya Peningkatan Keterampilan Siswa SLBN Jember Rindha Rentina Darah Pertami; Trismayanti Dwi Puspitasari; Jumiatun Jumiatun; Arvita Agus Kurniasari; Azizah Afni Maulidiyah
Journal of Community Development Vol. 5 No. 3 (2025): April
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/comdev.v5i3.1445

Abstract

Jember State Special School (SLB) through the Pancasila Student Profile Strengthening Project (P5) vocational through the theme "Let's garden". The implementation of the project has several obstacles, namely the limited number of teachers in managing the number of students if they have to do direct practical activities. So that a visual, communicative, and interesting learning method is needed so that students can easily understand it. The purpose of this activity is to improve the skills of SLB N Jember students. The implementation time is from May to August 2024. The methods used include observation, training in practice, monitoring, and evaluation. They are learning with visual or props techniques Based on the results of the activities that have been carried out. That there are 81% of students understand hydroponic vegetable packaging, and 60% of students who can understand the concept of packaging design, and marketing carried out through WhatsApp business so that they can improve their Agro-Entrepreneurship skills. This activity hopes to foster an entrepreneurial spirit in students as a provision after school. The training uses a learning system with visual or props techniques assisted by teachers at school. This activity continues to be accompanied by monitoring and evaluation so that it can be sustainable.
Automatic Pill Counting Using YOLOv8 to Improve Medication Distribution Accuracy Dinial Utami Nurul Qomariah; Ade Irma Elvira; Arvita Agus Kurniasari; Bima Wahyu Maulana
International Journal of Public Health Excellence (IJPHE) Vol. 5 No. 2 (2026): January-May
Publisher : PT Inovasi Pratama Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55299/ijphe.v5i2.1724

Abstract

Object detection is a critical component in various modern applications, including healthcare systems, smart agriculture, and industrial automation. The main challenge in developing detection systems lies in achieving high accuracy and strong generalization capabilities under diverse image conditions. This study aims to implement and evaluate the YOLOv8 model, a detection method known for its speed and efficiency. The model is trained using two scenarios—10 epochs and 50 epochs—to examine the impact of training duration on system performance. Evaluation results show that training for 10 epochs produces very good performance, with a precision of 0.98, recall of 0.94, and mAP of 0.98. Increasing the training to 50 epochs yields even more optimal results, achieving a precision of 0.99, recall of 1.00, and mAP of 0.99. Based on these findings, YOLOv8 demonstrates excellent adaptability to the dataset and is suitable for real-time detection applications that require high accuracy
Hand Gesture Detection Implemented based on Long Short-Term Memory (LSTM) Method I Gede Wiryawan; Taufiq Rizaldi; Pramuditha Shinta Dewi Puspitasari; Arvita Agus Kurniasari
Jurnal Sistem Cerdas Vol. 8 No. 3 (2025)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v8i3.526

Abstract

The Indonesian government encourages accessibility of information that is friendly to people with disabilities, one of which is through the development of information and communication technology. Efforts to increase accessibility of information and encourage independence of people with disabilities need to be supported by the right solutions. According to the Central Statistics Agency, there were 0.68% of the total population of Indonesia in 2019, this data shows that deafness is one of the highest disabilities in Indonesia. Efforts to increase accessibility of information and encourage independence of people with disabilities need to be supported by the right solutions. One potential solution is the development of a self-service system that is friendly to the deaf. This study aims to develop a self-service system that is friendly to the deaf and helps in obtaining information and services independently. The results achieved in this study are in the application of hand signal detection using the Long Short-Term Memory method which can overcome the problem of long-distance dependency and improve performance in recognizing complex hand signal patterns. The hand signal recognition feature can be improved by overcoming the problem of long-distance dependency with a maximum user distance of 1.25 meters, the system can still recognize hand signals well. It is hoped that in the future, more in-depth studies can be carried out on long-distance dependency for variations of other hand signal recognition methods, so that people with disabilities can more easily use the self-service system.
Towards a Sustainable Campus: Designing a Socio-Technical Framework for IoT Energy Management Systems Supporting SDGs Faisal Lutfi Afriansyah; Trismayanti Dwi Puspitasari; Syamsul Arifin; Dwi Putro Sarwo Setyohadi; Arvita Agus Kurniasari
International Journal of Studies in Social Sciences and Humanities Vol. 3 No. 1 (2026): July
Publisher : P3M Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/ijossh.v3i1.6651

Abstract

The increasing energy consumption in educational institutions presents a significant challenge for sustainable development. Smart campus initiatives, leveraging Internet of Things (IoT) technology, offer a promising solution for optimizing energy use, particularly for lighting and air conditioning (AC) systems. This study focuses on the design and development phase of a comprehensive social-technical framework for an IoT-based energy management system. The framework integrates ESP32 microcontrollers, Zigbee communication protocol, and a Digital Twin model to create an efficient and responsive control system. The primary objective is to establish a foundational design that addresses both the technical architecture and the crucial social aspects of user acceptance and integration within the campus environment, thereby supporting the achievement of Sustainable Development Goals (SDGs), specifically SDG 7 (Affordable and Clean Energy) and SDG 11 (Sustainable Cities and Communities). The methodology encompasses a user-centered design approach, involving stakeholder analysis and the development of a system prototype. Initial results include the successful design of the system architecture, the creation of a 3D Digital Twin model for visualization, and the development of a functional backend using Home Assistant. The study concludes that a robust social-technical framework is essential for the successful implementation of smart campus energy solutions and provides a roadmap for future deployment and evaluation, highlighting the importance of aligning technological innovation with user needs and institutional sustainability policies.
Co-Authors Achmad Basuki Ade Irma Elvira Afriansyah, Faisal Lutfi Aji Seto Arifianto Al Fitra Yudha, Vasyilla Kautsar Ali Ridho Barakbah Azizah Afni Maulidiyah Bety Etikasari Bety Etikasari Bety Etikasari, Bety Bima Wahyu Maulana Denny Trias Utomo, Denny Trias Dewi Puspitasari, Pramuditha Shinta Dinial Utami Nurul Qomariah Dwi Putro Sarwo Setyohadi Faisal Lutfi Afriansyah I Gede Wiryawan Isnaini, Misbachur Rohmatul Jumiatun Jumiatun Jumiatun Jumiatun, Jumiatun Kurniasari, Leli Lukie Perdanasari Octavian Yudha Mahendra Perdanasari, Lukie Pramuditha Shinta Dewi Puspitasari Puspitasari, Pramuditha Shinta Dewi Puspitasari, Trismayanti D. Puspitasari, Trismayanti Dwi Puspitasari, Trismayanti Dwi Putra, Dhony Manggala Ratri Cahyaning Winedhar Ria Chandra Kartika Ria Chandra Kartika Rindha Rentina Darah Pertami Syamsul Arifin Taufiq Rizaldi Taufiq Rizaldi Yuana, Dia Bitari Mei Yuwita, Kirana