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All Journal TEKNIK Jurnal Transformatika Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING Dinamisia: Jurnal Pengabdian Kepada Masyarakat SINTECH (Science and Information Technology) Journal Jurnal Sisfokom (Sistem Informasi dan Komputer) Technomedia Journal Building of Informatics, Technology and Science JUTIS : Jurnal Teknik Informatika Jurnal ABDINUS : Jurnal Pengabdian Nusantara Society : Jurnal Pengabdian dan Pemberdayaan Masyarakat DECODE: Jurnal Pendidikan Teknologi Informasi The Indonesian Journal of Computer Science
Rochadiani, Theresia Herlina
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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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 (IJCS)
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 (IJCS)
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.
Implementasi CNN dan MediaPipe dalam Peningkatan Efektivitas Stretching pada Olahraga Futsal: Implementation of CNN and MediaPipe in Increasing the Effectiveness of Stretching in Futsal Sports Jericho, Vito; Rochadiani, Theresia Herlina
Technomedia Journal Vol 9 No 3 (2025): February
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v9i3.2294

Abstract

This study aims to develop an effective Convolutional Neural Network (CNN) model in recognizing stretchingmovements that are often performed by futsal players, with the aim of reducing the risk of injury. The dataset usedconsists of 3000 images covering five types of movements: High Knees, Jumping Jacks, Lunge, Side Lunge, and ButtKicks. The data was taken from YouTube videos and processed to produce landmarks through MediaPipe technology. The CNN model was trained using the ”Adam” optimizer, with 50 epochs, a batch size of 8, and a learning rate of 0.001. The training results showed an accuracy of 94%, with the best performance on the Lunge and Jumping Jack movements, and adequate performance on other movements. The implementation of this model allows real-time monitoring of stretching movements, provides direct feedback to users, and helps futsal players in stretching with the right technique to avoid injury. This study shows that the CNN-based approach for stretching motion recognition in futsal is effective and reliable. Furtherresearch is suggested to increase the amount of training data and explore different model architectures to strengthen the model’s generalization.
Skincare Recommendation System Based on Facial Skin Type with Real-Time Weather Integration Gabrielle Sheila Sylvagno; Rochadiani, Theresia Herlina
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 14 No. 2 (2025): MEY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v14i2.2355

Abstract

Skin conditions can be significantly affected by unpredictable weather changes, creating the need for a solution that can provide personalized skincare product recommendations. This study presents the development of an AI-based skincare recommendation system that integrates skin type classification using Convolutional Neural Networks (CNN) with real-time weather data via the OpenWeatherMap API. The system consists of three main components: a ResNet50-based Skin Analyzer, a Weather Analyzer using the Decision Tree algorithm, and a Product Recommendation module. The image dataset is sourced from two Kaggle datasets: "Dry, Oily, and Normal Skin Types" and "Acne Dataset." The total dataset consists of 2,885 images, divided into four classes: Acne (549 images), Dry (652 images), Normal (884 images), and Oily (800 images). The dataset exhibits diversity in skin types, allowing for a more valid evaluation of the CNN model. The training and testing process involved splitting the data into training and testing sets, with augmentation applied to the training data to enhance the feature diversity across classes. Evaluation results show an average validation accuracy of 90.94% ± 0.60% with consistent performance. This system aids users in identifying their skin type and suggests appropriate skincare products based on current weather conditions. It is expected to contribute to the advancement of AI-driven personalization in the skincare industry.
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.
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 (IJCS)
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
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.
Sound-Based Smart Toddler Monitoring System: AIoT Development with YAMNet on Raspberry Pi Rochadiani, Theresia Herlina; Santoso, Handri; Wasito, Ito; Sucipto, Nadya Rudie; Anggraini, Astria Febrian; Panna, Ariya
TEKNIK Vol 46, No 3 (2025): Juli 2025
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/teknik.v46i3.76484

Abstract

The safety of toddlers at home is paramount for parents, but constant monitoring is difficult due to busy schedules. The limitations of camera-based monitoring solutions, namely privacy concerns and heavy processing, drive the need to develop monitoring systems that utilize sound recognition. This research aims to develop Smart Guardian, an Artificial Intelligence of Things (AIoT) system that can detect risky or emergency sound patterns from children and send real-time notifications to parents' mobile phones. The applied method includes the development of a YAMNet-based speech recognition AI model, installed on a Raspberry Pi as an edge computing device, with a microphone functioning to record environmental sounds. This system is designed to identify crucial environmental sounds such as breaking glass, explosions, screaming, water, fire alarms, smoke detectors, in addition to infant crying. The results of prototype trials under laboratory conditions indicate that the fire alarm and smoke detector classes have extremely high confidence levels (around 0.95 and 0.83). However, the glass class showed varying confidence levels (around 0.5), while cough, explosion, water, and screaming had lower confidence levels (median 0.15, 0.13, 0.25, and 0.4, respectively). The conclusion from these findings is that Smart Guardian has great potential as a privacy-focused toddler monitoring solution, although further optimization is needed to improve the speech recognition performance of events with low and varying confidence levels.  
Co-Authors Anggraini, Astria Febrian Aprilia, Novia Pramesti Cahyadi, Marcelinus Fajar Canady, Richwen Chitiawan, Tommy Danendra, Danica Recca Djuardi, Rich Deshan Fernando, Felix Gabrielle Sheila Sylvagno Hadibrata, Lymanto Indrawan, Vincenzo Matalino Ito Wasito Jaklin, Vanessa Jericho, Vito Jiustian, Danny Karyadi, Phance Laurenso, Justin Mandasari, Rhea Mayatopani, Hendra Muhammad Muhammad Novia Pramesti Aprilia Panna, Ariya Purnomo, Bryan Elmer Santoso, Handri Sofian, Thamrin steven willian Sucipto, Nadya Rudie Suhandi, Vartin Tanaka, Steven Tanuwijaya, Yefta Thamrin Sofian Thendiwijaya, Alfred Gerald Tua, Jonathan Erik Maruli Wulandari , Islamiati