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All Journal InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Journal of Applied Engineering and Technological Science (JAETS) Jurnal Sistem Komputer dan Informatika (JSON) Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) ABDI SABHA (Jurnal Pengabdian kepada Masyarakat) Journal of Social Responsibility Projects by Higher Education Forum Jurnal ABDIMAS Budi Darma TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Fatma Sari Hutagalung
Program Studi Magister Teknik Informatika Fakultas Ilmu Komputer Dan Teknologi Informasi Universitas Sumatera Utara
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Visual Detection of Oil Palm Maturity Leveraging Simple Evolving Connectionist System Al-Khowarizmi Al-Khowarizmi; Fatma Sari Hutagalung; Halim Maulana
Journal of Applied Engineering and Technological Science (JAETS) Vol. 7 No. 2 (2026): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/kvqm6450

Abstract

Detecting the ripeness of oil palm fruit bunches is a crucial process in the palm oil industry to ensure the quality and quantity of oil extracted. Conventional methods still rely on subjective and inefficient manual observation. This study proposes a visual detection system using the Simple Evolving Connectionist System (SECoS) algorithm to identify the ripeness of oil palm bunches based on visual images. This model utilizes color, texture, and shape characteristics extracted from images and processed through an adaptive and evolving neural network structure. The results demonstrate that SECoS is capable of high detection accuracy and adapts to new data patterns. This system has the potential to be applied in precision agriculture practices. The model achieved an average accuracy of 91.3%, with the highest accuracy of 94% in the "Ripe" category in the final test based on 300 dataset. This demonstrates that parameter optimization is crucial in improving the model's ability to adapt to variations in oil palm bunch image data. Accuracy improvements were evident in both training and validation data. However, not all categories achieved optimal results, with accuracy for the "empty bunch" labels (89%) and "unripe" labels (88%) being relatively lower than for the other categories.
Intervensi Terfase Model IN-ON-IN untuk Mengatasi Gap Implementasi Literasi Koding dan AI Guru SD di Sumatera Utara Akhyar Lubis; Fatma Sari Hutagalung; Riah Ukur Ginting; Mesran Mesran; Juanda Hakim Lubis; Fajrul Malik Aminullah Napitupulu
Journal of Social Responsibility Projects by Higher Education Forum Vol 6 No 3 (2026): March 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jrespro.v6i3.9752

Abstract

This community service program aimed to address the gap between conceptual knowledge and practical implementation ability of elementary school (SD) teachers in coding and artificial intelligence (AI) instruction in Medan City and Deli Serdang Regency. Initial needs analysis revealed that while many teachers possessed basic familiarity with coding and AI terminology, the majority had not independently designed lesson plans incorporating coding activities nor systematically used coding platforms in classroom settings. Partner schools also faced uneven device availability and internet connectivity, alongside weak post-training support structures that hindered the transfer of learning to classroom practice. The intervention applied the IN-ON-IN model with contextual coaching: In Service Training 1 (conceptual and practical workshops using Scratch 3.0, Code.org, and Teachable Machine), On-the-Job Training (classroom implementation with field coaching and telementoring), and In Service Training 2 (reflection and consolidation). The program involved 175 elementary school teachers from both regions, implemented October 2025 through February 2026. Evaluation used an explanatory sequential mixed-methods design: pretest–posttest, classroom observation rubrics, learning artifact analysis, and in-depth interviews and focus groups. Results showed knowledge score improvement from 81% to 95% with reduced standard deviation (3.11 to 1.09), alongside qualitative findings confirming gains in lesson plan design competency and project-based coding instruction for the majority of participants. Persistent barriers included limited devices, intermittent internet access, and time constraints for lesson planning. Recommendations emphasize low-resource module development, expansion of telementoring, and cross-stakeholder collaboration to strengthen school infrastructure.
Implementasi Sistem Pendukung Keputusan Berbasis Internet of Things (IoT) Untuk Menentukan Kesehatan Tanaman Bunga Kertas Menggunakan Metode Simple Additive Weighting (SAW) Asmaul Husna; Fatma Sari Hutagalung
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2(SEMNASTIK) (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akunt
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2(SEMNASTIK).pp31-39

Abstract

Ornamental plants are plants that are in great demand these days because of their beauty and attractiveness. Ornamental plants are an important aspect because they are able to maintain environmental health, the more ornamental plants the better it is also to beautify the environment. In this research, a determination process is carried out to determine the health of ornamental plants, one of which is Bougenville Flower or commonly referred to as paper flower, which is an ornamental plant whose existence is quite popular among the public and is widely spread in various regions in Indonesia. The method used in this research is the Simple Additive Weighting (SAW) method to rank alternatives. The criteria used are 3 namely air temperature, air humidity, and soil pH, while the alternatives used are 10 paper flower ornamental plants with the aim of ranking the best or healthy paper flower plants from the samples tested. Implementation with the SAW method produces recommendations for paper flower ornamental plants, namely A3 or paper flower 3 accompanied by the results of ranking values with a value of 0.992 which is the highest value compared to other alternatives. This research has also been calculated using Confusion Matrix with an accuracy test result of 60%.
Co-Authors Akhyar Lubis Al Khowarizmi Asmaul Husna Budi Kurniawan Hutasuhut Efendi, Syahril Fajrul Malik Aminullah Napitupulu Farhan Al-iksan Al-iksan Farid Akbar Siregar Ferdy Riza Halim Maulana Herman Mawengkang Indah Purnama Sari Indah Purnama Sari Juanda Hakim Lubis Martiano, Martiano Mesran Mesran Mhd. Basri Ramadhani, Fanny Riah Ukur Ginting Yoshida Sary