Article Per Year (5 Year)
p-Index From 2021 - 2026
2.407
P-Index
This Author published in this journals
All Journal JUSIFO : Jurnal Sistem Informasi Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat J-Dinamika: Jurnal Pengabdian Kepada Masyarakat EPI International Journal of Engineering Jurnal Teknologi Elekterika Abdimas Toddopuli: Jurnal Pengabdian Pada Masyarakat Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Pengabdian UNDIKMA Jurnal Teknik Informatika (JUTIF) Journal of System and Computer Engineering
Maratuttahirah
Institut Teknologi Bacharuddin Jusuf Habibie
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Nursing Public Health Social Sciences Other

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

Found 2 Documents
Search
Journal : journal of system and computer engineering

 1 
Klasifikasi Omset ATK menggunakan Algoritma Naïve Bayes Ira, Mar'atuttahirah
Journal of System and Computer Engineering Vol 5 No 1 (2024): JSCE: Januari 2024
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v5i1.1100

Abstract

Small businesses play a role in absorbing work energy, as a source of innovation, providing economic services to the community and in the process of equalizing and increasing community profit. One of the factors that influences the dynamics of modern business is technological progress. Evolving technology has opened the door to rapid innovation. Profit classification is a popular and effective approach for businesses that can tailor marketing strategies to each group more effectively which will impact business profit. The stock condition of an item greatly influences sales revenue. The increasing demand for goods will result in large profit. Product availability to meet consumer needs is a problem that must be overcome. The stock condition of an item greatly influences sales profit. This research is related to the classification of profit for each item sold in a shop, whether it is sold a lot or not enough to maximize the stock of goods per time using the Naive Bayes algorithm. From data research, attribute grouping, preprocessing, data transformation and modeling were carried out using the Naïve Bayes algorithm in the Python programming language. Testing the Naïve Bayes algorithm obtained 90% accuracy results for the classification of stationery profit. The system can determine the classes of goods that are sold a lot and goods that are not sold enough, becoming a solution for shop leaders to more easily take business strategies quickly and optimally which of course will affect profit.
Deteksi dan Estimasi Berat Sampah Plastik Berbasis Visi Komputer Andri Dwi Utomo; Mar’atuttahirah Mar’atuttahirah; A. Inayah Auliyah; Muhammad Nur
Journal of System and Computer Engineering Vol 7 No 3 (2026): JSCE: July 2026
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v7i3.2755

Abstract

Plastic waste management is an increasingly critical environmental challenge due to the growing volume of waste and the limitations of conventional manual weighing methods, which are inefficient and prone to human error. This study proposes a computer vision-based system for automatic detection, classification, and weight estimation of plastic waste using the YOLOv8n model for object detection and Random Forest Regression for weight estimation. The YOLOv8n model is used to detect and classify seven types of plastic waste based on the Resin Identification Code (RIC), namely PET, HDPE, PVC, LDPE, PP, PS, and OTHER. Subsequently, weight estimation is performed using a Random Forest Regression model based on bounding box features, including width, height, area, aspect ratio, and perimeter. The proposed system is evaluated using an unseen test set to ensure unbiased performance measurement. Experimental results show that the YOLOv8n model achieves a mean Average Precision (mAP@0.5) of 91.93% and mAP@0.5:0.95 of 73.27%, while the Random Forest Regression model achieves an R² score of 95.5% with a Mean Absolute Error (MAE) of 4.28 grams. These results demonstrate that the integration of object detection and regression enables accurate and automatic estimation of plastic waste weight, thereby improving the efficiency and objectivity of waste management systems.
Co-Authors A. Inayah Auliyah Abdullah Abdullah Abdullah B Abdullah B Ahmad Fajri Akmal Baharuddin Syam Al-Amin, Muh. Alfito, Ramadan Barik Alvian Tri Putra Darti Akhsa Alya Wulan Apriliyani Amaliah Chintami Darti Akhsa Andi Febyana Aziz Andri Dwi Utomo Arifin, Nurhikma Barik Alfito, Ramadan Danang Fatkhur Razak Eka Qadri Nuranti Eka Qadri Nuranti Fahrisal, Januar Fajri S, Ahmad Fathuresqi, Fathuresqi Januar Fahrisal Juprianus Rusman Khaera Tunnisa Khaera Tunnisa, Khaera Lukman Hakim Lukman Hakim Lukman Hakim Mahdaniar Mahdaniar Mardhiyyah Rafrin Miftahulkhairah Miftahulkhairah, Miftahulkhairah Muhammad Aldi Alfatih Muhammad Aldi Alfatih Muhammad Alfian Muhammad Alfian Muhammad Anugrah Muhammad Anugrah Muhammad Furqan Rasyid Muhammad Nur Muhammad Rivaldi Jefri Muhammad Rivaldi Jefri Naili Suri Intizhami Naili Suri Intizhami Najwa, Hafizah Najwa, Hafizhah Noel Ivander Pusung Nur Fadillah Hakim Nur Rahmi Putri Ayu Maharani Putri, Anggita Ra, Danang Fatkhur Razak Raden Mohamad Herdian Bhakti Rahmat Eka Putra R Palaloi Rahmat Eka Putra R. Palaloi Rakhmadi Rahman Ramadhan, Syam Syahru Rosmiati Rosmiati Rosmiati Rosmiati Rosmiati Rosmiati Sarmila, Sarmila Siti Hajar Baharuddin Siti Nurhalizah Suryabuana, Andi Sahra Syafira Fatwa Tri Aditya, Muh Wahyuni Ekasasmita