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All Journal Teknika Sistemasi: Jurnal Sistem Informasi RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Inotera Jurnal Vokasi JINAV: Journal of Information and Visualization Rambideun : Jurnal Pengabdian Kepada Masyarakat International Journal of Engineering, Science and Information Technology Jurnal Tika jeti Multidiciplinary Output Research for Actual and International Issue (Morfai Journal) TECHSI - Jurnal Teknik Informatika DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Dharmawangsa: International Journal of the Social Sciences, Education and Humanitis Jurnal Malikussaleh Mengabdi Gameology and Multimedia Expert Nawadeepa: Jurnal Pengabdian Masyarakat Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Nunsina, Nunsina
Universitas Malikussaleh
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K-Means Application to Rice Production with DBI Evaluation Badruttamam Badruttamam; Mukti Qamal; Nunsina Nunsina
SISTEMASI Vol 15, No 7 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Universitas Islam Indragiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i7.6510

Abstract

Rice production is a key indicator of regional food security, making it essential to analyze production patterns and identify differences in productivity across districts. This study aims to apply the K-Means clustering algorithm to classify rice production data in Bireuen Regency and evaluate the quality of the resulting clusters using the Davies–Bouldin Index (DBI). The study employed secondary data from 2020 to 2024 covering 17 districts, with four variables: cultivated area, harvested area, productivity, and total rice production. The K-Means algorithm was used to partition the data into three clusters representing high, medium, and low production levels based on similarities in their characteristics. The results indicate that the clustering process consistently classified the districts across the five-year observation period. Cluster quality evaluation using the Davies–Bouldin Index yielded values of 0.9147 in 2020, 0.8292 in 2021, 0.6119 in 2022, 0.8821 in 2023, and 0.8597 in 2024. The best clustering performance was achieved in 2022, as indicated by the lowest DBI value, reflecting a more compact and well-separated clustering structure. These findings provide valuable insights for supporting agricultural planning, improving rice production strategies, and informing policy decisions related to agricultural development in Bireuen Regency.
Clustering of Food Security Levels in North Aceh Using K-Medoids Tarisha Zhafira; Bustami Bustami; Nunsina Nunsina
Journal of Applied Informatics and Computing Vol. 10 No. 3 (2026): June 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i3.12881

Abstract

Food security is essential for ensuring food availability, accessibility, and utilization. This study applies a multidimensional indicator framework covering social, economic, and infrastructure aspects to cluster regions in North Aceh Regency, addressing limitations of previous studies that primarily focus on agricultural production indicators and lack policy-oriented analysis. The analysis uses 2023 data from 27 sub-districts at the village level, comprising 852 villages. The indicators include: (1) the ratio of agricultural land area to total population, (2) the ratio of food supply facilities and infrastructure to households, (3) the ratio of population with the lowest welfare status to total population, (4) the proportion of villages without adequate transportation access via land, water, or air, (5) the ratio of households without access to clean water, and (6) the ratio of population per health worker relative to population density. Data processing involves preprocessing, normalization, and K-Medoids clustering, evaluated using the Davies–Bouldin Index (DBI) and Silhouette Coefficient (SC). The results identify six clusters: highly food insecure (C1) with 63 villages, food insecure (C2) with 92 villages, moderately food insecure (C3) with 179 villages, moderately food secure (C4) with 42 villages, food secure (C5) with 49 villages, and highly food secure (C6) with 427 villages. Most villages fall within moderately food insecure to highly food secure categories, indicating disparities in food security distribution. The DBI value of 3.085 indicates moderate cluster compactness, while the SC value of 17.75% suggests weak separation between clusters. These findings provide policy recommendations for targeted and equitable food security interventions.
Design of Attendance System for Informatics Engineering Lecturers Using RFID Sensors Based on IoT and Telegram Applications Andry Maulana Akbar; Wahyu Fuadi; Nunsina Nunsina
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.794

Abstract

The attendance system is an essential element in the academic environment to ensure lecturer attendance in the lecture process. However, the manual attendance method still has various weaknesses, such as the potential for data manipulation and inefficiency in recording attendance. To overcome these problems, this research designs and implements an Internet of Things (IoT)-based lecturer attendance system using Radio Frequency Identification (RFID) sensors integrated with the Telegram application. The research method includes hardware design with ESP32 microcontroller, ESP32-CAM, RFID sensor, and HC-SR04 ultrasonic sensor. This system works by detecting lecturer attendance through RFID cards confirmed by ESP32, taking pictures with ESP32-CAM, and sending automatic notifications via the Telegram bot. Lecturer attendance data is then stored in a web-based database to facilitate the monitoring and evaluation. The test results show that the developed system can detect and record lecturer attendance accurately, with the response speed of the RFID sensor in reading cards ranging from 1-5 cm. The ultrasonic sensor also successfully detects objects accurately within a predetermined distance range. Lecturer attendance notifications sent via Telegram allow administrators to conduct real-time monitoring. With this IoT-based attendance system, the attendance recording process becomes more efficient and transparent and can reduce the risk of data manipulation. Further development can be done by adding data encryption and biometric authentication features to improve system security.
Co-Authors Ade Nahya Zahara Andry Maulana Akbar Annisa Fitria Aqiilah Cahya Ningrum Ariyandi, Zulham Badruttamam Badruttamam Bustami Bustami Cut Fadhilah Cut Fadhilah Dahlan Abdullah Epa Yanti Eva Darnila Eva Darnila Eva Darnila Fadhilah, Cut Fadhlilah, Cut Fatimah Zuhra Fatimah Zuhra Haniful Fikri Hasibuan, Fadilah Suryani Ichsan Kulbahri, Kulbahri Mahara, Sabda Maysura Muhammad Muaz Munauwar Mukti Qamal Munawwar Khalil, Munawwar Mustaqim Mutasar Nazimah Nazimah Nilahayati Nurdin Nurdin Putri Raihatul Jannah Rahma Fitria, Rahma Rahmad Rahmad Razi, Ar Rifkial Iqwal Rini Meiyanti Rizal Tjut Adek Rosma Siregar Safrizal Safrizal Tarisha Zhafira Taufiq Taufiq Viki, Zakial Wahyu Fuadi Walad Hidayat Zahidi Pratama Zahratul Fitri Zahratul Fitri, Zahratul Zakial Viki Zara Yunizar Zuliani Zuliani