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All Journal International Journal of Electrical and Computer Engineering Jurnal Teknologi Informasi dan Ilmu Komputer KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Sinkron : Jurnal dan Penelitian Teknik Informatika J-Dinamika: Jurnal Pengabdian Kepada Masyarakat Jurnal Mantik Journal of Applied Engineering and Technological Science (JAETS) Indonesian Journal of Electrical Engineering and Computer Science Jurnal ComunitA Servizio
Rudy Chandra
Institut Teknologi Del
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Nursing Social Sciences

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P PENGEMBANGAN SISTEM INFORMASI YAYASAN PENDIDIKAN ANAK RUMAH DAMAI : Development of The Information System for Yayasan Pendidikan Anak Rumah Damai Henry Agus Panjaitan , Goklas; Simatupang, Frengki; Chandra, Rudy; Arifin Prasetyo, Tegar; Lumban Gaol, Tiurma; Italiano Wowiling, Gerry; Mula Timbul Sigiro, Marojahan; Pangaribuan, Maria; Panca Rahmat Siagian, Iqbal; Partogi Pardede, Immanuel
J-Dinamika : Jurnal Pengabdian Masyarakat Vol 10 No 2 (2025): Agustus
Publisher : Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Yayasan Pendidikan Anak Rumah Damai (YPARD) adalah suatu yayasan pendidikan nonformal untuk anak-anak disabilitas, yatim piatu, anak-anak pinggiran Danau Toba dan anak-anak yang memiliki kemauan untuk belajar pendidikan nonformal dimana proses dan aktifitas yang dilakukan di dalam yayasan masih secara manual dan data-data masih banyak tersimpan dalam bentuk buku atau kertas. Untuk itu diperlukan pengembangan sistem informas yang dapat memberikan informasi yang baik dan komplek terkait bagaimana kondisi atau situasi yang berlangsung di yaysan tersebut. Pengembangan sistem informasi untuk Yayasan Pendidikan Anak Rumah Damai (YPARD) adalah suatu yayasan pendidikan nonformal untuk anak-anak disabilitas, yatim bertujuan untuk memberikan informasi-informasi terkait aktifitas dan data-data yayasan sehingga stakeholder dalam yayasan dapat mengetahui dengan mudah informasi-informasi yang ada di dalam Yayasan dan memudahkan Ketua Yayasan dan staff untuk mendapatkan informasi seperti laporan, rekapitulasi data, dan informasi-informasi tentang Yayasan Pendidikan Anak Rumah Damai. Metode untuk pengembangan sistem informasi Yayasan Pendidikan Anak Rumah Damai adalah mengikuti tahapan-tahapan metodologi Waterfall yaitu Communication, Planning, Modeling, Construction, Deployment. Pengembangan sitem informasi akan menggunakan Framework Laravel, Javascript, CSS, HTML dan MySQL.
Pengembangan Aplikasi Rekomendasi Berbasis Mobile Pada Destinasi Wisata Di Sekitar Danau Toba Menggunakan Metode Moora Dengan Pembobotan ROC Chandra, Rudy; Pasaribu, Monalisa; Arifin Prasetyo, Tegar; Henry Agus Panjaitan, Goklas; Emy Sonia Sinambela; Suandika Napitupulu; Anastasia Marsada Uli Simamora
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 12 No 4: Agustus 2025
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.124

Abstract

Danau Toba merupakan destinasi wisata unggulan di Sumatera Utara yang memiliki potensi wisata alam, wisata buatan, dan budaya Batak. Namun, wisatawan seringkali membutuhkan rekomendasi wisata yang sesuai dengan kriteria keinginan mereka. Untuk mengatasi masalah ini, aplikasi rekomendasi destinasi wisata di sekitar Danau Toba dikembangkan menggunakan metode Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) dengan pembobotan Rank Order Centroid (ROC). Aplikasi rekomendasi wisata dirancang untuk mempermudah para wisatawan untuk mencari destinasi wisata yang menarik sesuai keinginannya. Aplikasi akan memberikan rekomendasi wisata yang optimal berdasarkan kriteria yang telah ditentukan, yaitu jenis wisata, wilayah, rating, harga tiket, hari operasional, dan jam operasional. Jumlah data pada aplikasi rekomendasi wisata menggunakan 123 objek wisata. Hasil aplikasi yang dibangun berupa pengembangan aplikasi rekomendasi wisata berbasis mobile dengan menggunakan API, PHP dan teknologi multi-platform yaitu Flutter. Pengujian aplikasi melibatkan beberapa pengujian, termasuk system testing, user testing, dan pengujian akurasi pengelolaan data. Hasil system testing menunjukkan bahwa aplikasi beroperasi dengan stabil tanpa error dan semua fungsi berjalan sesuai yang diharapkan. User testing dilakukan dengan menyebarkan kuesioner kepada 625 responden yang telah menggunakan aplikasi tersebut, terdiri dari masyarakat domisili Sumatera Utara sebanyak 144 orang (69,2%) dan luar Sumatera Utara sebanyak 65 orang (30,8%). Sebanyak 94,2% responden menyatakan bahwa aplikasi mudah digunakan, 94,1% merasa fungsi rekomendasi sesuai dengan kebutuhan, 83,2% menganggap desain tampilan menarik, 95,5% menyatakan informasi pada setiap destinasi wisata sudah jelas, 94,7% pengguna dari luar dan dalam Sumatera Utara dapat memahami alur aplikasi, dan 94,4% berencana menggunakan aplikasi ini sebagai panduan untuk mengunjungi destinasi wisata di Sumatera Utara. Hasil pengujian akurasi pengelolaan data menunjukkan kecocokan yang tinggi antara hasil perhitungan manual dan implementasi sistem dalam menambah, mengubah, dan menghapus data wisata. Aplikasi rekomendasi ini memiliki keunggulan yang mampu menekankan wisata disekitar Danau Toba sehingga potensi dan kearifan lokalnya dapat terlihat lebih menarik bagi pengunjung baru.   Abstract Lake Toba is a premier tourist destination in North Sumatra, renowned for its natural beauty, artificial attractions, and rich Batak culture. However, tourists often seek recommendations that align with their preferences. To address this need, a tourist destination recommendation application for the Lake Toba area has been developed using the Multi-Objective Optimization based on the Ratio Analysis (MOORA) method, incorporating Rank Order Centroid (ROC) weighting. This application aims to simplify the process for tourists to find appealing destinations based on their criteria. It provides optimal recommendations according to various factors, including type of tourism, region, ratings, ticket prices, operational days, and hours. The application features data on 123 tourist attractions. The resulting application is a mobile-based platform developed using API, PHP, and cross-platform technology, specifically Flutter. Thorough testing has been conducted, including system testing, user testing, and data management accuracy testing. The system testing revealed that the application operates smoothly without errors and that all functionalities perform as intended. User testing involved distributing questionnaires to 625 respondents who had used the application, comprising 144 individuals from North Sumatra (69.2%) and 65 from outside the region (30.8%). The feedback was overwhelmingly positive, with 94.2% of respondents finding the application easy to use, 94.1% satisfied that the recommendations met their needs, 83.2% deeming the design attractive, and 95.5% confirming that the information about each tourist destination was clear. Furthermore, 94.7% of users, both from within and outside North Sumatra, reported understanding the application flow, and 94.4% expressed their intention to use the app as a guide for visiting tourist sites in North Sumatra. The data management accuracy test indicated a strong correlation between manual calculations and the application's data handling capabilities for adding, modifying, and deleting tourism data. This recommendation application highlights tourism around Lake Toba, making its potential and local wisdom more appealing to new visitors.
Optimizing parameter selection in bidirectional encoder portrayal for transformers algorithm using particle swarm optimization for artificial intelligence generate essay detection Prasetyo, Tegar Arifin; Chandra, Rudy; Siagian, Wesly Mailander; Siregar, Horas Marolop Amsal; Siahaan, Samuel Jefri Saputra
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i6.pp5543-5554

Abstract

This research proposes a novel method for detecting artificial intelligence (AI)-generated essays by integrating the bidirectional encoder representations from transformers (BERT) model with particle swarm optimization (PSO). Unlike traditional approaches that rely on manual hyperparameter tuning, this study introduces a systematic optimization technique using PSO to improve BERT’s performance in identifying AI-generated content. The key problem addressed is the lack of effective, real-time detection systems that preserve academic integrity amidst rapid AI advancements. This optimization enhances the model’s detection accuracy and operational efficiency. The research dataset consisted of 46,246 essays, which, after data cleaning, were refined to 44,868. The model was then tested on 9,250 essays. Initial evaluations showed BERT's accuracy ranging from 83% to 94%. After being optimized with PSO, the model achieved an accuracy of 98%, an F1-score of 98.31%, precision of 97.75%, and recall of 98.87%. The model was deployed using a FastAPI-based web interface, enabling real-time detection and providing users with an efficient way to quickly verify text authenticity. This research contributes a scalable, automated solution for AI-generated text detection and offers promising implications for its application in various academic and digital content verification contexts.
Enhancing the Effectiveness of the YOLO Model Through Caladium Leaf Images Generated by Generative Adversarial Networks Chandra, Rudy; Prasetyo, Tegar Arifin; Simamora, Akdes Simon; Simbolon, Amanda Artha Regina; Sinaga, Ester Krismayani; Perdanasari, Lukie
Journal of Applied Engineering and Technological Science (JAETS) Vol. 7 No. 1 (2025): 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/jaets.v7i1.6624

Abstract

The need for ornamental caladium plants is very popular, but there are several obstacles to recognizing its type. Caladium species classification using AI is needed to overcome the problem of misidentification among enthusiasts. This study uses the Generative Adversarial Network (GAN) algorithm to generate new images from the Caladium dataset: Amazon Caladium, Bicolor Caladium, White Queen Caladium, and Skull Caladium. We combine GAN with YOLOv5 to detect Caladium in real time to improve accuracy. The quality of the generated images is evaluated using the Kernel Inception Distance (KID) method, with the highest scores of 0.2320 for Amazon Caladium, 0.1966 for Bicolor, 0.1713 for Skull, and 0.1857 for White Queen, indicating close similarity to the original images. We chose the best model to generate three datasets: Original Dataset, Mixed Dataset (original images plus GAN-generated images), and Dataset consisting mainly of GAN images. The Mixed Dataset achieved the best results, with a mean Average Precision (mAP) of 0.695 for an Intersection over Union (IoU) of 0.50:0.95 outperforming the GAN dataset and the original Dataset. This training used 50 epochs, a learning rate of 0.0003, and a batch size of 16, to obtain the best model and significantly improve Caladium detection. From this experiment, it was found that the GAN, combined with the original data, was able to support the accuracy of YOLOv5 for real-time caladium classification and was also able to create new images that resembled the original leaves. In the mobile application, this model allows real-time identification of Caladium types, making it easier for users to buy Caladium according to the desired type.
Co-Authors Ahmadi Irmansyah Lubis Anastasia Marsada Uli Simamora Asido Saragih Christian Benedict Lumbantoruan Dame Sisri Haryati Katarina Rumapea Dewi Handayani Emy Sonia Sinambela Erna Budhiarti Nababan Ester Saulina Hutabarat Evan Richardo Sianipar Frengki Simatupang Fritz Marpaung Goklas Henry Agus Panjaitan Henry Agus Panjaitan , Goklas Henry Agus Panjaitan, Goklas Herbeth Augustinus Napitupulu Italiano Wowiling, Gerry Joshua Pratama Silitonga Juan Carlos Munthe Lawy Xenna Lumban Gaol, Tiurma Matthew Alfredo Mula Timbul Sigiro, Marojahan Nico Felix Sipahutar Panca Rahmat Siagian, Iqbal Pangaribuan, Maria Partogi Pardede, Immanuel Pasaribu, Monalisa Perdanasari, Lukie Poibe Leny Naomi Risky Saputra Siahaan Roberd Saragih Samuel Sibuea Sarbaini Sarbaini Sawaluddin Nasution SIAGIAN, WESLY MAILANDER Siahaan, Samuel Jefri Saputra Sihombing, Tahan HJ Simamora, Akdes Simon Simbolon, Amanda Artha Regina Sinaga, Ester Krismayani Siregar, Horas Marolop Amsal Suandika Napitupulu Tegar Arifin Prasetyo Tessalonika Siahaan Tiurma Lumban Gaol Trito Exaudi Manik Wesly Mailander Siagian