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Komparatif Studi Model Deep Learning Untuk Deteksi Karies Gigi Tanuwijaya, Yefta; Rochadiani, Theresia Herlina
The Indonesian Journal of Computer Science Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i2.4857

Abstract

Dental caries is a dental disease that is considered a global public health problem and requires detection that is friendly to remote areas. This study presents a comparison of the evaluation results of deep learning models for detecting dental caries from early to extensive levels using YOLOv11, Faster R-CNN and RetinaNet models. The dataset contains 1,036 images divided into 4 classes (healthy teeth, early caries, moderate caries and extensive caries). As a result, YOLOv11 produced the highest mean average precision (mAP) of 79.2%. In addition, balanced precision (70.9%), recall (76.6%) and f1 score (73.6%), high average precision (AP) per class (healthy teeth: 85.5%, early caries: 66.9%, extensive caries: 91.6% and moderate caries: 72.6%), a 5.6 ms inference time and 5 MB model size are featured by YOLOv11 which is suitable to be implemented into various devices to support medical personnel in detecting dental caries in remote areas.
Development of Population Data Management Website for Curug Sangereng Village: Pembangunan Website Pengelolaan Data Kependudukan Desa Curug Sangereng Rochadiani, Theresia Herlina; Tanaka, Steven; Tua, Jonathan Erik Maruli; Thendiwijaya, Alfred Gerald; Muhammad, Muhammad; Purnomo, Bryan Elmer; Chitiawan, Tommy
Dinamisia : Jurnal Pengabdian Kepada Masyarakat Vol. 9 No. 5 (2025): Dinamisia: Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/

Abstract

Pembangunan website untuk pengelolaan data kependudukan Desa Curug Sangereng merupakan langkah penting dalam transformasi digital pemerintahan desa. Sehingga kegiatan pengabdian masyarakat ini bertujuan untuk meningkatkan efisiensi dan efektivitas pengelolaan data penduduk yang sebelumnya dilakukan secara manual. Metode kegiatan ini meliputi identifikasi permasalahan dan kebutuhan, pembangunan sistem, evaluasi, dan sosialisasi. Tahap identifikasi permasalahan dan kebutuhan dilakukan dengan melakukan wawancara dan observasi. Selanjutnya tahap pembangunan website digunakan PHP dan database MySQL, dengan fitur utama seperti penambahan data penduduk, unduh data, dan visualisasi data kependudukan. Evaluasi dilakukan dengan mendemokan website dan meminta feedback dari perangkat desa melalui kuesioner. Tahap terakhir adalah sosialisasi untuk memastikan perangkat desa memahami penggunaan sistem. Hasil evaluasi, berdasarkan hasil kuesioner yang diisi oleh perangkat desa, menunjukkan bahwa 100% responden setuju bahwa sistem ini mempermudah pengelolaan data dan mendukung pengambilan keputusan berbasis data. Website ini meningkatkan efisiensi dan efektivitas pengelolaan data kependudukan Desa Curug.
Digitalisasi UMKM Menuju Masyarakat Maju di Kampung Kalipaten Rochadiani, Theresia Herlina; Mandasari, Rhea; Wulandari , Islamiati; Jaklin, Vanessa
Society : Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol. 4 No. 2 (2024): Vol.4 No.2, April 2024
Publisher : Universitas Dinamika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37802/society.v4i2.486

Abstract

Kegiatan digitalisasi diperlukan bagi pelaku Usaha Mikro Kecil dan Menengah (UMKM) di era industri 4.0. Transformasi dan penguatan teknologi digital telah menjadi hal penting untuk diterapkan di segala bidang, termasuk UMKM yang merupakan tulang punggung ekonomi bangsa. Pembukaan e-wallet dan sosialisasi mengenai e-commerce merupakan upaya yang dilakukan untuk melakukan pengembangan atau transformasi digital pada pelaku UMKM. Tujuan kegiatan pengembangan digitalisasi di Kampung Kalipaten adalah untuk membantu pelaku UMKM mengikuti zaman era digital dan mampu bersaing di pasar online. Metode kegiatan ini berupa sosialisasi dan pendampingan yang dilakukan melalui tahapan penentuan tujuan guna mendefinisikan kebutuhan dari UMKM. Kemudian, tahap persiapan yang dilakukannya pendataan dan survei langsung pada para pelaku UMKM. Selanjutnya pada tahap pelaksanaan, kegiatan digitalisasi dilakukan secara offline dan sebagai tahap evaluasi, di akhir kegiatan pembukaan rekening, pelaku UMKM diajak untuk melakukan diskusi. Adapun tahap evaluasi dari kegiatan sosialisasi, masyarakat diminta untuk mengisi kuesioner.  Dari hasil diskusi dari kegiatan pembukaan rekening BCA, pelaku UMKM mulai memiliki pemahaman mengenai cara kerja dari dompet digital. Sedangkan hasil evaluasi kegiatan sosialisasi menyatakan sebanyak 80% mengatakan bahwa kegiatan sosialisasi membantu para pelaku UMKM dalam mengelola usaha di aplikasi e-commerce.
Pelatihan Dasar IoT Menggunakan Tinkercad Bagi Siswa SMK Kristen Immanuel Pontianak Rochadiani, Theresia Herlina; Santoso, Handri
Dinamisia : Jurnal Pengabdian Kepada Masyarakat Vol. 7 No. 6 (2023): Dinamisia: Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/dinamisia.v7i6.16031

Abstract

Internet of Things (IoT) technology as one of the technologies in the Industrial Revolution 4.0 era allows communication between electronic devices and sensors via the internet. This is very helpful for human life. Various applications of IoT have expanded in the fields of medicine, agriculture, logistics, energy, and many more. With the rapid growth of IoT even in the industrial world, professionals who have capabilities in this field are needed. Responding to the need for manpower in the Industrial Revolution 4.0 era, this community service activity was carried out to equip students at Vocational High Schools (SMK). The implementation of this activity succeeded in providing understanding and knowledge to the students of Christian Vocational High School Immanuel, Pontianak. This is indicated by 63% of the student participants experiencing an increase in their pre-test and post-test scores.
Pengembangan Computational Thinking Melalui IoT Apps Programming Dengan Tinkercad Rochadiani, Theresia Herlina; Santoso, Handri; Mayatopani, Hendra
Jurnal ABDINUS : Jurnal Pengabdian Nusantara Vol 6 No 1 (2022): Volume 6 Nomor 1 Tahun 2022
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/ja.v6i1.16007

Abstract

Computational thinking is one of competencies are needed recently. Most countries had already included computational thinking into their curriculum. Based on PISA 2018, Indonesia placed 72nd ranking of 77 countries for reading, 72nd ranking of 78 countries for mathematics, and 70th ranking of 78 countries for sciences. It is of concern to government and us to elevate this computational thinking ability, especially for students. Through this community service, the training of IoT programming using Tinkercad is given to PAHOA Senior High School students. Theory and hands-on practical in this training was followed by 40 students for 4 months. Based on questionnaire in the end of this training, 62% participations agreed that their computational thinking increase through this training and 96% participations could make IoT apps.
Pelatihan Machine Learning Menggunakan Bahasa Pemrograman Python Bagi Karyawan PT. Yokogawa Indonesia Santoso, Handri; Rochadiani, Theresia Herlina
Jurnal ABDINUS : Jurnal Pengabdian Nusantara Vol 6 No 2 (2022): Volume 6 Nomor 2 Tahun 2022
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/ja.v6i2.16018

Abstract

Industry 4.0 insists companies to apply intelligent application technology to their industries. Machine learning as one of field of Artificial Intelligence has used widely in Smart Factory, such as to detect product defects, to predict potential problems and for its solutions. PT. Yokogawa Indonesia, one of global company, wanted to prepare its employees to implement Smart Factory, as its response for Industry 4.0 and competition with other companies. As a solution to this problem, the community service held machine learning training using Python for PT. Yokogawa Indonesia’s employees. The training was held once a week for five weeks. Interaction and discussion online between trainer and participants used Teams Microsoft application. It also used google classroom for managing materials and assignments during this training. More than 50% of participants never learn machine learning before this training. In the last session of the training, questionnaire was given to the participants. As the result, a half of total of participants agreed that their knowledge about machine learning has increased significantly through this training.
Machine Health in a Click: A Website for Real-Time Machine Condition Monitoring Rochadiani, Theresia Herlina; Santoso, Handri; Aprilia, Novia Pramesti; Laurenso, Justin; Suhandi, Vartin
The Indonesian Journal of Computer Science Vol. 12 No. 6 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i6.3592

Abstract

Globalization in the current digital era has made it easier to use information technology to obtain fast and accurate information. One source of information is a website that can be used to monitor machine conditions in the industry. A good machine maintenance strategy is needed to maintain and increase machine productivity. Therefore, this research aims to build a website to monitor machine conditions in real-time. The machine condition is monitored using sushi sensors to track parameters such as temperature, acceleration, and velocity. Deep learning analysis is then used to identify anomalies in the machine. Using the SCRUM method, this website was successfully built. From the results of tests carried out using unit testing and integrated testing, every feature on this website can run well and according to user needs.
Pendekatan Transfer Learning Untuk Klasifikasi Tangisan Bayi Dengan Imbalance Dataset Rochadiani, Theresia Herlina
The Indonesian Journal of Computer Science Vol. 13 No. 2 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i2.3834

Abstract

Klasifikasi tangisan bayi dapat dimanfaatkan untuk mengidentifikasi masalah kesehatan bayi dan memenuhi kebutuhan bayi dengan cepat. Dalam studi ini, teknik transfer learning, dengan model terlatih YAMNet, diterapkan untuk klasifikasi bayi dengan dataset terbatas dan tidak seimbang. YAMNet, sebuah model Convolutional Neural Network khusus untuk analisis audio, mengatasi keterbatasan metode tradisional yang bergantung pada interpretasi manusia. Dengan mempelajari fitur-fitur audio secara otomatis, memungkinkan kinerja klasifikasi yang lebih akurat. Dalam studi ini, dilakukan eksplorasi dan analisis manfaat penggunaan YAMNet, melalui perbandingan dengan model baseline tanpa teknik transfer learning. Hasilnya menunjukkan bahwa model YAMNet tidak hanya nilai akurasinya yang tinggi 0.8106, namun juga nilai skor-F1nya tinggi yaitu mencapai 0.9831. Terbukti bahwa penggunaan transfer learning dapat meningkatkan kinerja dalam klasifikasi tangisan bayi, terutama dalam mengatasi ketidakseimbangan data dan meningkatkan prediksi untuk kelas minoritas.
Image Captioning untuk Gambar Rambu Lalu Lintas Indonesia Menggunakan Pretrained CNN dan Transformer Novia Pramesti Aprilia; Rochadiani, Theresia Herlina
The Indonesian Journal of Computer Science Vol. 13 No. 3 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i3.4012

Abstract

This research aims to address the lack of understanding of traffic signs in Indonesia through the development of an image captioning model using Inception V3 and Transformer. With this approach, a dataset of traffic sign images consisting of 9,594 images with 31 classes was collected and modified. Model evaluation was conducted using BLEU, ROUGE-L, METEOR, and CIDEr metrics. The research results show good performance with BLEU-1 score of 0.89, BLEU-2 = 0.82, BLEU-3 = 0.75, BLEU-4 = 0.68, CIDEr = 0.57, ROUGE-L = 0.25, and METEOR = 0.26. From these results, it can be indicated that this model can enhance understanding of Indonesian traffic signs. This approach can assist road users in better understanding traffic signs and has the potential to be applied in practical applications to improve traffic safety