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All Journal SISFOTENIKA Journal of Information Technology and Computer Science (JOINTECS) Indonesian Journal of Artificial Intelligence and Data Mining Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat Jurnal Pengabdian Masyarakat Jurnal Ilmu Komputer dan Teknologi (IKOMTI) Malcom: Indonesian Journal of Machine Learning and Computer Science International Journal of Health Science and Technology SEMINAR NASIONAL PENELITIAN DAN PENGABDIAN KEPADA MASYARAKAT Jurnal Pengabdian dan Pemberdayaan Masyarakat Indonesia Intelligent Systems and Robotics
Khoirun Nisa
Universitas Harapan Bangsa
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Nursing Public Health Social Sciences Other

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Implementasi Metode Analytic Hierarchy Process untuk Pemilihan Lahan Perkebunan Kelapa Sawit di Riau: Implementation of Analytic Hierarchy Process Method for Riau Oil Palm Plantation Land Selection Moh. Erkamim; Sepriano Sepriano; I Gede Iwan Sudipa; Khoirun Nisa; Ali Zainal Abidin Alaydrus; Legito Legito
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 3 No. 2 (2023): MALCOM October 2023
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v3i2.871

Abstract

Penelitian ini bertujuan untuk memberikan alternatif pada pemilihan lahan perkebunan Kelapa Sawit Riau dengan Metode Analytic Hierarchy Process (AHP). Dengan jumlah kriteria adalah 5 yang terdiri dari curah hujan, ketinggian diatas permukaan laut, kandungan bahan dasar, ketebalan gambut dan keasaman tanah. Alternatif adalah 12 yang terdiri dari 12 kabupaten di Riau. Provinsi Riau merupakan salah satu provinsi yang memiliki perkebunan kelapa sawit yang paling luas di indonesia, pertumbuhan luas area kebun kelapa sawit sangat pesat. Pencarian alternatif menggunakan metode AHP dengan jumlah kriteria adalah 5 terdiri dari curah hujan, ketinggian diatas permukaan laut, kandungan bahan dasar, ketebalan gambut dan keasaman tanah.  Jumlah alternatif adalah 12 yang terdiri dari 12 Kabupaen di Riau. Sehingga didapatkan hasil perankingan bahwa Kuantan merupakan prioritas pertama dan Bengkalis merupakan prioritas ke-12 dengan nilai konsitensi rasio adalah 2,6%
Digital Entrepreneurship Education and Mentoring for PGRI Gumelar High School Students to Enhance Entrepreneurial Skills in International Markets Using Digital Media Purwono Purwono; Khoirun Nisa; Jatmiko Indriyanto; Lutviana; Dimas Febri Kuncoro
Jurnal Pengabdian dan Pemberdayaan Masyarakat Indonesia Vol. 3 No. 6 (2023)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jppmi.v3i6.212

Abstract

The development of information technology continues to increase and has reached all levels of society, including the younger generation. This generation is present as a cohort with superior personalities and the ability to comprehend knowledge and technology, enabling them to compete locally and globally. Technological advancements also catalyze innovations, fostering creativity in the economic and business fields. SMA PGRI Gumelar is a private school in Gumelar District, Banyumas Regency, which offers various life skill activities such as graphic design, foreign languages, photography, videography, and more. However, the existing activities have not yet yielded works that can be marketed internationally. This service aims to optimize graphic design life skills training for students so that they can produce work that is marketable on overseas platforms, namely Envato. This marketplace has specific standards for works that will be sold; therefore, education and assistance are provided to enhance motivation for digital media-based entrepreneurship in the international market. This beginner community service activity will be conducted from July to October 2023 at SMA PGRI Gumelar. The outcome of this activity will be graphic design work ready to be uploaded to the Envato marketplace. Based on the results of the questionnaire distributed to participants, there was an increase in motivation as a designpreneur, increasing by 35%, Figma skills increasing by 45% and Photoshop skills increasing by 35%. Another output of this project is a graphic design tutorial book with an ISBN number
Pengembangan Aplikasi Peminjaman Ruang Berbasis Web dengan Metode Agile Feature Driven Development pada Universitas Harapan Bangsa Amanah Tri Wulandari; Anggit Wirasto; Khoirun Nisa
Seminar Nasional Penelitian dan Pengabdian Kepada Masyarakat Vol 3 No 1 (2023): Prosiding Seminar Nasional Penelitian dan Pengabdian Kepada Masyarakat (SNPPKM 20
Publisher : Universitas Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35960/snppkm.v3i1.1228

Abstract

Mekanisme peminjaman ruang di Universitas Harapan Bangsa saat ini masih dalam tahap manual. Peminjaman dilakukan dengan cara meminjam ruang melalui grup Whatsapp. Selama proses ini berlangsung, beberapa peminjam tidak mengetahui ruangan mana yang sedang ditempati atau yang dipinjam karena kemungkinan besar pesan WhatsApp akan tertutup oleh pesan lain.Tujuan dari penelitian ini adalah membangun suatu aplikasi peminjaman ruang berbasis web yang bertujuan untuk memudahkan proses peminjaman ruang bagi pegawai dan Administrasi Akademik Umum dan Keuangan (BAAK) dalam proses pengelolaan data ruangan yang akan tersimpan secara digital. Data peminjaman ruangan akan lebih akurat sehingga meminimalisir terjadinya kesalahan seperti peminjaman ganda pada suatu ruangan agar lebih efektif dan efisien.Aplikasi peminjaman ruang ini dibangun menggunakan bahasa pemrograman PHP dan database MySQL dengan framework Laravel 9 dan menggunakan metode Feature Driven Development yang memiliki keunggulan dalam hal waktu, metode yang sederhana dan mudah dipahami serta perangkat lunak yang dikembangkan sesuai dengan kebutuhan stakeholder.
Real Time Computer Vision System Based on Convolutional Neural Networks for Precision Object Detection and Tracking in Collaborative Industrial Robot Applications Anggit Wirasto; Khoirun Nisa; Titi Christiana
Intelligent Systems and Robotics Vol. 1 No. 1 (2026): February: Intelligent Systems and Robotics
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/isr.v1i1.38

Abstract

The increasing adoption of collaborative robots in modern manufacturing environments requires reliable perception systems that can ensure both safety and operational efficiency during human–robot collaboration. This study proposes a CNN-based real-time computer vision system for object and human detection in shared robotic workspaces. The research focuses on developing and evaluating a single-stage deep learning detection model optimized for real-time performance while maintaining high detection accuracy. The proposed methodology includes dataset preparation, model training using transfer learning, real-time system implementation, and comprehensive performance evaluation. Experimental results demonstrate that the developed system achieves high detection accuracy, as reflected by strong precision, recall, and mean Average Precision (mAP) values, while maintaining low inference latency suitable for real-time operation. The system consistently operates above real-time frame-rate thresholds, ensuring timely perception updates required for safety-related decision-making in collaborative robotic environments. Graphical and quantitative analyses further confirm the stability of inference performance under dynamic interaction scenarios involving human movement and multiple objects. Compared with existing approaches, the proposed system provides a balanced trade-off between accuracy and computational efficiency, making it practical for deployment in safety-aware human–robot collaboration scenarios. Overall, the findings indicate that CNN-based real-time object detection systems can effectively support perception and situational awareness in collaborative robotics, contributing to safer and more efficient industrial automation.
Co-Authors Ali Zainal Abidin Alaydrus Amanah Tri Wulandari Amanah Wulandari Anggit Wirasto Bala Putra Dewa Bambang Sumantri, R Bagus Benny Krisbiantoro Dede Yusuf Dimas Febri Kuncoro Endang Setyawati Hadi Jayusman I Gede Iwan Sudipa Imam Ahmad Ashari, Imam Ahmad Jatmiko Indriyanto Kusrini Kusrini Legito . Lutviana Moh. Erkamim Muhammad Soali Muntiari, Novita Ranti Purwono, Purwono Retno Agus Setiawan Said Thaufik Rizaldi Sepriano Sepriano Sony Kartika Wibisono Sudarmawan Sudarmawan Sulhatun Sulhatun Titi Christiana Tri Pujiani Winalia Agwil Zilrahmi, Zilrahmi