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All Journal Techno.Com: Jurnal Teknologi Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JITK (Jurnal Ilmu Pengetahuan dan Komputer) ILKOM Jurnal Ilmiah Jurnal Teknik Informatika (JUTIF) Jurnal Pengabdian Masyarakat : Pemberdayaan, Inovasi dan Perubahan Journal of Information Systems and Technology Research Sisfo: Jurnal Ilmiah Sistem Informasi Journal of Computers and Digital Business Wahana Internet of Things and Artificial Intelligence Journal SERVIRE: Jurnal Penelitian dan Pengabdian Jurnal Agro Fabrica Journal of Technology Informatics and Engineering Journal of Deep Learning, Computer Vision and Digital Image Processing The Indonesian Journal of Computer Science Jurnal Edukasi Citra Olahraga Bhakti: Jurnal Pengabdian dan Pemberdayaan Masyarakat Journal of Digital Technology and Computer Science
Ratu Mutiara Siregar
Institut Teknologi Sawit Indonesia
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Classification of Plant Pests Using the Real-Time Detection Transformer (RT-DETR) Algorithm in Oil Palm Plants Bayu Ath Thariq Syams; Ratu Mutiara Siregar; Muhammad Akbar Syahbana Pane
Sisfo: Jurnal Ilmiah Sistem Informasi Vol. 10 No. 1 (2026): Sisfo: Jurnal Ilmiah Sistem Informasi, Mei 2026
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/sisfo.v10i1.27029

Abstract

Plant Pests (PP) are one of the main factors causing a decline in oil palm productivity. This study focuses on the classification of PP, limited to the three main pest species: the rhinoceros beetle (Oryctes rhinoceros), the fireworm (Setora nitens), and the Tioman rat (Rattus tiomanicus). The dataset consists of digital images representing these three pest types. The method used is the Real-Time Detection Transformer (RT-DETR), which is capable of real-time, end-to-end object detection. The research stages include data collection, preprocessing, model training, and evaluation using confusion matrix, precision, recall, and F1-score metrics. The research results are expected to produce an accurate and efficient crop pest classification system to support decision-making in pest management in oil palm plantations.
Design and Development of a Mobile Application for Palm Oil Harvest Recording and Reporting Using a User-Centered Design (UCD) Kisah Tiara Sihombing; Ritna Wahyuni; Ratu Mutiara Siregar
Sisfo: Jurnal Ilmiah Sistem Informasi Vol. 10 No. 1 (2026): Sisfo: Jurnal Ilmiah Sistem Informasi, Mei 2026
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/sisfo.v10i1.27284

Abstract

The digitization of oil palm harvest recording is necessary to improve data accuracy, reporting efficiency, and operational transparency in plantation environments. The manual recording process currently used often leads to reporting delays, data inconsistencies, and errors in harvest data recording. This study aims to design and develop a mobile application for oil palm harvest recording and reporting using a User-Centered Design (UCD) approach to meet user needs and field conditions. The research methods included observation, interviews, user needs analysis, system design, prototype development, and system evaluation. Functional testing was conducted using black-box testing, while usability testing utilized the System Usability Scale (SUS). The developed application provides features for recording fresh fruit bunches (FFB), loose fruit recording, photo documentation, offline data storage, automatic synchronization, foreman validation, and periodic reporting. The test results indicate that all system features functioned properly and achieved an average SUS score of 77.75, which falls into the “Good” category. These results demonstrate that the application is easy to use and accepted by users. Thus, the User-Centered Design approach successfully produced a practical, efficient, and user-friendly application to support oil palm harvest data management.
PEMBERDAYAAN MASYARAKAT MELALUI PELATIHAN PEMBUATAN ECO-ENZYME DARI LIMBAH SAYURAN UNTUK MENDUKUNG PENGELOLAAN SAMPAH RUMAH TANGGA BERKELANJUTAN Sri Wahyuna Saragih; Wardatul Husna Irham; Ratu Mutiara Siregar; Muhammad Ikbal Aritonang; Syerlina Sari; Shaira Fitdina Amelia; Chengly Jaxon Boahlander Siahaan; Hiskia Sitanggang
BHAKTI: JURNAL PENGABDIAN DAN PEMBERDAYAAN MASYARAKAT Vol. 5 No. 01 (2026): Juni
Publisher : Universitas Islam Tribakti (UIT) Lirboyo Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33367/bjppm.v5i01.9189

Abstract

 This community service initiative was designed to empower communities by providing training on converting vegetable waste into eco-enzyme as a solution for sustainable household waste management. The program adopted a participatory method involving awareness sessions, practical workshops, and ongoing assistance. Participants were introduced to material preparation, fermentation techniques, and the utilization of eco-enzyme as an eco-friendly cleaning solution and liquid fertilizer. The outcomes indicated a significant increase in participants’ understanding and practical skills in managing organic waste, along with heightened environmental awareness. Furthermore, the program fostered positive behavioral changes in reducing household organic waste and promoted the adoption of simple and affordable sustainable practices. Hence, eco-enzyme production represents a practical community-based approach to improving sustainable household waste management.
Android-Based Digitalization of Fresh Fruit Bunch Harvest and Supply Chain with Geo-Tagging and Online-Offline Cloud Synchronization Ifan Gultom; Ratu Mutiara Siregar; Andi Prayogi
Sisfo: Jurnal Ilmiah Sistem Informasi Vol. 10 No. 2 (2026): Sisfo: Jurnal Ilmiah Sistem Informasi, Oktober 2026 (In Press)
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/sisfo.v10i2.27375

Abstract

Background: Manual recording of Fresh Fruit Bunch (FFB) harvest activities at Kebun Tanah Putih PTPN IV Regional 3 results in reporting delays of up to 24 hours, a human error rate of approximately 15–20% per entry, inability to verify harvest locations spatially, and absence of real-time monitoring under limited network connectivity. Objective: This study develops HarvestTrack, an Android and web-based mobile information system for FFB harvest recording and supply chain monitoring, aimed at improving data accuracy, operational efficiency, and transparency in oil palm plantation management. Method: A Research and Development (R&D) methodology with a prototyping approach was employed, covering requirements analysis, system design, implementation, and testing. The system was built with Flutter, Firebase Firestore (cloud backend), and SQLite (local storage) using an offline-first architecture. Delta synchronization via WorkManager and geo-tagging via Fused Location Provider API (≤10 m accuracy) were implemented. Testing included functional, performance, and User Acceptance Testing (UAT). Results: Functional testing confirmed 100% success for offline data recording and automatic cloud synchronization (<5 seconds/entry). Geo-tagging achieved ≤10 m accuracy in 95% of 40 field test locations. Last-Write-Wins (LWW) conflict resolution attained an error rate below 2%. Three role-based user modules (KCS, Foreman, Admin) were fully implemented with differentiated access controls. Contribution: HarvestTrack is the first integrated system combining offline-first architecture, real-time geo-tagging, automated conflict handling, and web-based monitoring dashboard for FFB supply chain digitalization in Indonesia's oil palm sector.
IoT Based Monitoring System for Fresh Fruit Bunch (FFB) Quality Indicators Using TCS3200 Color Sensor and LoRa Communication at the Palm Oil Mill Receiving Process Nabil Azzaidan Nasution; Ratu Mutiara Siregar; Muhammad Akbar Syahbana Pane
Sisfo: Jurnal Ilmiah Sistem Informasi Vol. 10 No. 2 (2026): Sisfo: Jurnal Ilmiah Sistem Informasi, Oktober 2026 (In Press)
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/sisfo.v10i2.27518

Abstract

Abstract The quality of Fresh Fruit Bunches (FFB) has a substantial impact on the efficiency of palm oil processing. Nevertheless, traditional assessment techniques remain manual and subjective. This research introduces an Internet of Things (IoT)-based monitoring system designed for the real-time and objective evaluation of FFB maturity. The system employs a TCS3200 color sensor alongside a DHT22 sensor, which are integrated with an ESP32 microcontroller and utilize LoRa communication for long-distance data transmission. The data collected is sent to the ThingSpeak platform for real-time visualization.Field trials conducted at the Cinta Raja plantation indicate that the system is capable of categorizing FFB maturity into ripe, unripe, and undetected based on the predominant color components. However, its performance is affected by environmental variables, especially lighting conditions.In summary, the system offers a practical and cost-effective solution for monitoring FFB quality, although further enhancements in calibration and environmental control are necessary to improve accuracy and reliability.
Design and Development of a Geotagging and QR Code-Based Oil Palm Fertilization Tracking System Using Android Mobile Integration and LoRa SX1278 Mohammad Farodis Azhari; Ratu Mutiara Siregar; Andi Prayogi
Sisfo: Jurnal Ilmiah Sistem Informasi Vol. 10 No. 2 (2026): Sisfo: Jurnal Ilmiah Sistem Informasi, Oktober 2026 (In Press)
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/sisfo.v10i2.27547

Abstract

This research proposes the development of an Internet of Things (IoT) monitoring system for tracking and verifying palm oil fertilization based on Geotagging and QR Code to overcome challenges in manual fertilization supervision, such as location accuracy, dose precision, and transmission vulnerabilities in remote areas. The system ensures compliance with field standard operating procedures (SOP) through a dual-validation mechanism: spatial coordinate recording via geotagging for location audit trails, and QR Code scanning for fertilizer identity verification. The hardware system architecture integrates a ESP32 microcontroller, a NEO-6M GPS module, and a LoRa Ra-02 SX1278 (433 MHz) transceiver mounted directly on the wheelbarrow. Field workers utilize a Flutter-based mobile Android application to scan the fertilizer labels, which wirelessly forwards data via a Bluetooth Low Energy (BLE 4.2) link to the ESP32. Field integration trials conducted at the ITSI Campus estate demonstrated that the wheelbarrow unit successfully captures high-precision coordinates by locking onto 7 active satellites under dense palm oil canopies with a 3-second refresh rate. Out of 20 live fertilization check-ins executed during the field-testing sessions, the system successfully logged 14 valid transactions and flagged 6 operational deviations, achieving a definitive 70.0% geotagging compliance rate. Furthermore, the offline-first local cache layer guaranteed zero data loss inside cellular blank spots by securely holding transaction logs before automatically synchronizing them to the Firebase Realtime Database. This architecture effectively mitigates the telecommunication infrastructure barrier in remote plantation sectors while generating verifiable, tamper-proof digital audit trails.
IMPLEMENTASI YOLOV11 UNTUK SISTEM DETEKSI OTOMATIS SENSUS KELAPA SAWIT : IMPLEMENTATION OF YOLOV11 FOR AUTOMATIC DETECTION SYSTEM OF OIL PALM CENSUS Zia; Raden Aris Sugianto; Ritna Wahyuni; Ratu Mutiara Siregar
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.7915

Abstract

Oil palm tree census plays a crucial role in plantation management, influencing production planning and managerial decision-making. Manual counting using drone imagery in QGIS is time-consuming and prone to human error. This study aims to design and implement an automatic oil palm tree census detection system using the YOLOv11 algorithm integrated with QGIS. A quantitative approach with system development methodology was employed. Drone imagery was processed in Agisoft Metashape to produce orthomosaic GeoTIFF images, then annotated via Roboflow and trained using YOLOv11 for 100 epochs. Detection was performed using SAHI (Sliced Aided Hyper Inference) with 640×640 pixel tiles (25% overlap) and DBSCAN deduplication. The system successfully detected 4,886 oil palm trees in Block P14402 Sei Baleh Estate PT BSP (±24 Ha). Model evaluation yielded Precision 0.96, Recall 0.95, mAP@IoU=0.5 of 0.98, and F1-Score 0.955. Black Box Testing across 9 functional scenarios all passed. The automated system proved significantly more efficient than the manual method, supporting digitalization of oil palm plantation management.
SISTEM INFORMASI MANAJEMEN GUDANG PERKEBUNAN KELAPA SAWIT DENGAN PENDEKATAN HYBRID MENINGKATKAN EFISIENSI DAN AKURASI INVENTORI Ready Perdana; Ratu Mutiara Siregar; Andi Prayogi
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.7966

Abstract

Warehouse management in oil palm plantations still faces challenges including manual recording that is prone to errors, inventory data discrepancies, and limited internet connectivity in remote areas. This study aims to design and develop a Warehouse Management Information System using a hybrid approach that supports offline and online operations, implement a data synchronization mechanism between local storage and the main database, and improve operational efficiency and inventory accuracy in oil palm plantation environments. The Research and Development (R&D) method with a Prototype approach was employed. The system was developed using Flutter as the frontend framework, Laravel as the backend and API, SQLite as the local device database, and MySQL as the main server database. Testing was conducted using the Blackbox Testing method with 46 test scenarios covering eight functional modules. The results show a 100% success rate across all functional test scenarios. The system operates in hybrid mode, automatically synchronizes data via a push-pull mechanism using UUID as an idempotency key, and provides inventory management features including item master data, goods receipt, goods issuance, stock opname, multi-level approval, digital reporting (PDF and Excel), and activity logs. The system has been proven to improve operational efficiency by eliminating redundant recording processes and enabling remote digital approvals, and to enhance inventory accuracy through automatic input validation, duplicate data prevention, and a structured audit trail.  
SISTEM MONITORING IOT BOBOT MUATAN DAN LIVE TRACKING PADA KENDARAAN PENGANGKUT TBS BERBASIS MQTT-NEXTJS Muhammad Hatta Ridho; Andi Prayogi; Ratu Mutiara Siregar
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8264

Abstract

The development of Internet of Things (IoT) technology provides opportunities for to improve the efficiency of Fresh Fruit Bunches (FFB) transportation in oil palm plantations. Common challenges include difficulties in monitoring vehicle locations in real time and recording load weights manually. This study aims to design and develop a load weight monitoring and live tracking system for an FFB transportation vehicle prototype using an ESP32 microcontroller, an HX711 Load Cell sensor, a Neo-6M GPS module, the Message Queuing Telemetry Transport (MQTT) protocol, and a NextJS-based monitoring dashboard. The research methodology included hardware design, software development, system integration, and functional testing. The Load Cell sensor measured the load weight, while the GPS module obtained real-time vehicle coordinates. The ESP32 processed the collected data and transmitted them via MQTT to a broker and database for visualization on the dashboard. The test results showed that the system successfully monitored load weight and tracked the prototype vehicle in real time, achieving a 100% data transmission success rate under normal network conditions. The developed system provides effective, accurate, and integrated transportation monitoring, improving the efficiency of FFB transportation management in oil palm plantations.
Classification of Oil Palm Fresh Fruit Bunch Ripeness Levels Using the YOLOv11n Algorithm Ananda Apri Anata; Ratu Mutiara Siregar; Andi Prayogi
Journal of Digital Technology and Computer Science Vol. 3 No. 2 (2026): April 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/dtcs.v3i2.894

Abstract

Purpose – Manual assessment of oil palm fresh fruit bunch (FFB) ripeness remains subjective and may reduce harvest quality consistency. This study aims to evaluate YOLOv11n for six-class FFB ripeness detection using instance-level object detection metrics. Methods – A Roboflow dataset of 17,437 augmented images was split into training, validation, and held-out test subsets across six classes: Empty Bunch, Less Ripe, Abnormal FFB, Ripe FFB, Unripe FFB, and Overripe. A qualitative consistency check was conducted by one harvest foreman. Findings – Evaluation on 1,756 held-out test images containing 6,372 FFB instances achieved precision of 0.968, recall of 0.980, F1-score of 0.974, mAP50 of 0.988, and mAP50-95 of 0.901. Overripe was the weakest class, with mAP50-95 of 0.846. Research implications – The results indicate that YOLOv11n has strong potential to support automated FFB ripeness grading. However, broader field validation, multi-annotator agreement analysis, and testing under more diverse plantation conditions are still required. Originality – This study contributes a six-class YOLOv11n-based FFB ripeness detection evaluation using held-out test-set instance-level metrics and strict localization assessment through mAP50-95.
Co-Authors Abdussalam Al Akbar Alex Rizky Saputra Ali Ikhwan Alimuddin Yasin Alisarjuni Padang Ananda Apri Anata Andi Prayogi Andi Prayogi Andi Prayogi Annisa Annisa Ardila Aslina Gulo Asnita Yani Awal, Elsa Elvira Balqis Nurmauli Damanik Bayu Ath Thariq Syams Bintang Florentina Aruan Busrizal Faisal Chengly Jaxon Boahlander Siahaan Elfitra Erin Triani Sipayung Fadilah, Sandi Fajar Maulana . Ferdy Hardiansyah Friska Anggraini Barus Guntoro, Guntoro Hiskia Sitanggang Ifan Gultom IzuKhairi Misrawi Rohali Kan, Phak Len Al Eh Khairul Saleh Khoirun Nisa Harahap Kisah Tiara Sihombing Liga Mayola Mahyuddin K. M Nasution Maisarah Maisarah Maisarah, Maisarah Makhrani Sari Ginting Maudy Hellena Harlyn Mohamad Rifa Algifari Mulia Sembiring Mohammad Farodis Azhari Moustafa H. Aly Muhammad Akbar Syahbana Pane Muhammad Akbar Syahbana Pane Muhammad Akbar Syahbana Pane Muhammad Hatta Ridho Muhammad Ikbal Aritonang Muhammad Yusuf Dibisono Mulyara, Budi Nabil Azzaidan Nasution Navea, Roy Francis Niko Firzi Anansyah Nur Hafiqah Rambe Nurliana Phaklen Ehkan Prayogi, Andi Raden Aris Sugianto Rahmad Dian Rahmad Dian Rahmad Dian Rahmamnsyah, Eka Patma Ready Perdana Ritna Wahyuni Rizky Delianngi Saddam Husein Siregar Sari, Yessi Ratna Sepriano Sepriano Septianur Eka Amri Shaira Fitdina Amelia Silky Safira Simbolon, Hasanal Fachri Satia Sri Wahyuna Saragih Sumaryanto Syerlina Sari Tuty Ningsih WARDATUL HUSNA IRHAM Wisnu Ananta Kusuma Yasir, Amru Zia