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All Journal HAYATI Journal of Biosciences Teknosains: Media Informasi Sains dan Teknologi Indonesian Journal on Computing (Indo-JC) IJoICT (International Journal on Information and Communication Technology) JURNAL NASIONAL TEKNIK ELEKTRO JOIN (Jurnal Online Informatika) Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA JMM (Jurnal Masyarakat Mandiri) Jurnal Ilmiah Ecosystem Building of Informatics, Technology and Science Jurnal Aplikasi dan Inovasi Iptek (JASINTEK) Jurnal Teknik Informatika (JUTIF) Charity : Jurnal Pengabdian Masyarakat KLIK: Kajian Ilmiah Informatika dan Komputer eProceedings of Engineering Eduvest - Journal of Universal Studies AMMA : Jurnal Pengabdian Masyarakat Jurnal Pemanfaatan Teknologi untuk Masyarakat
Satria Mandala
Universitas Telkom
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Neuroscience Nursing Physics Social Sciences Other

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Ensemble Deep Learning Study for Pest Detection in Strawberry Plants Kahargyan Ario Nugroho; Satria Mandala
Eduvest - Journal of Universal Studies Vol. 5 No. 6 (2025): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v5i6.50311

Abstract

This deep learning-based classification model was developed to recognize different types of pest infections in strawberry plants. The model aims to quickly identify pest symptoms, thus enabling efficient pest management in smart farming. This research uses an actual dataset containing images of strawberry leaves collected from smart farm trials. To expand the dataset, open data from platforms such as Kaggle were used, while images of infected leaves were obtained through web crawling with the help of Python libraries. The added data were converted to a uniform size, and PseudoLabeling was used to ensure stable learning on both training and testing datasets. The RegNet and EfficientNet models are selected as the main CNN-based models for iterative learning, with ensemble learning techniques to improve prediction accuracy. The proposed model aims to assist the early identification and treatment of pests on strawberry leaves during the early planting period, a crucial phase in the development of smart agriculture. It is hoped that this model can increase production in the agricultural industry and strengthen its competitiveness. Detecting early symptoms of plant diseases and pests is essential to prevent their development and minimize the damage caused. Although many methods have been developed using deep learning techniques, detecting early symptoms is still challenging due to the lack of datasets capable of training models against subtle changes in plants. Therefore, researchers built an automated data collection system to gather a large dataset of plant images and train ensemble models to detect diseases and pests of the target plants.
Redesain KMS Digital Ramah Lansia Untuk Penguatan Peran Kader Posyandu Di Desa Lebakwangi Satria Mandala; Ledya Novamizanti; Endro Ariyanto
AMMA : Jurnal Pengabdian Masyarakat Vol. 5 No. 6 : Juli (2026): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

This community service program was designed to improve the user experience of KMS Digital in posyandu services in Lebakwangi Village, Arjasari Subdistrict, Bandung Regency. The activity continued the previous implementation of KMS Digital as a digital tool for recording and monitoring toddler growth. During early use, several cadres reported that the application was not yet fully convenient, especially for older cadres. The main obstacles were related to a relatively long workflow, an interface that still needed clearer visual organization, and navigation that was not yet fully aligned with the daily practices of posyandu users. Based on this feedback, the 2026 activity placed usability at the center of the improvement process. The work included reorganizing the interface, simplifying the recording flow, strengthening data validation and reporting, and providing direct assistance to users. The stages consisted of reviewing the existing application, collecting user feedback, improving key features, conducting socialization, assisting users, and evaluating partner satisfaction. The revised components included the landing page, cadre dashboard, toddler detail page, parent list, monthly report, and health worker workspace. The socialization activity was held on June 19, 2026, in Lebakwangi Village and involved 24 participants. The questionnaire results showed that 72.50% of responses were in the agree category and 24.17% were in the strongly agree category. Together, these responses reached 96.67%, indicating strong acceptance from the partner community without any rejection. The results suggest that improving KMS Digital based on user needs can increase cadres acceptance of digital systems. Therefore, posyandu digitalization should not be viewed merely as the provision of an application, but as a process of aligning technology with the capacity and field conditions of users. A more elderly-friendly KMS Digital is expected to support more practical recording, monitoring, and reporting of toddler growth.
Pengembangan Aplikasi Web Sebagai Media Informasi Dan Sistem Pencatatan Data Pelanggan Pada Layanan Tour Guide Trip Asia Satria Mandala; Rajiv Dharma Mangruwa; Bramantya Hendrawan Yoga; Imam Arif Wicaksono; Adika Ghivan Pratama; Muhammad Ardiansyah Pratama; Deven Febrian Susilo
AMMA : Jurnal Pengabdian Masyarakat Vol. 5 No. 6 : Juli (2026): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

This community service activity aimed to assist Solo Tour Guide Specialist, a tourism guide service MSME under the HalloTrip brand, in strengthening digital promotion and organizing customer data recording. Before the activity, service information was still shared through WhatsApp and personal networks, while the partner did not yet have an official public information platform. As a result, business profiles, travel packages, testimonials, schedules, and booking channels were not presented in a centralized manner. The solution developed consisted of two web-based systems: a public landing page as a tourism service information showcase and an admin website for customer data recording. The systems were developed using HTML, CSS, JavaScript, and Tailwind CSS through a participatory approach with the partner. The activity workflow covered needs identification, interface design, system development, functional testing, training, mentoring, and evaluation. The outcome was the HalloTrip website, accessible at hallotrip.vercel.app, featuring Asian destination information, testimonials, a real-time weather widget, a WhatsApp booking button, and an admin website with login and customer data recording features. The socialization session was conducted online so that the partner could understand the website workflow and use the system more independently. Partner feedback showed very positive acceptance, with four main indicators receiving full agreement in the agree and strongly agree categories. Although 25% neutral responses appeared in the committee service aspect, the overall solution was considered relevant and practical as an initial step in digitally transforming the partner's promotion and administration.
An Interval-Informed Hybrid CNN-LSTM for Ten-Category ECG Beat and Event Classification I Putu Bagus Erix Wijaya; Arda Ardiyansyah; Satria Mandala
Building of Informatics, Technology and Science (BITS) Vol 8 No 2 (2026): September 2026
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v8i2.10916

Abstract

Automated electrocardiogram (ECG) classification remains challenging because waveform-based deep-learning models capture rich morphology, whereas clinically relevant conduction and timing intervals are not always represented explicitly. This study investigates whether a compact interval-informed representation can retain useful discriminative information for ten ECG beat and event categories. MIT-BIH Arrhythmia Database recordings were filtered and divided into seven-second segments. RR, PR, and QT intervals and QRS width were summarized using minimum, maximum, mean, median, skewness, and kurtosis, yielding 24 features. To prevent information leakage, the original samples were partitioned before oversampling; feature scaling and SMOTE were applied only to training data, while validation and held-out test data retained their original distributions. Leakage-controlled five-fold cross-validation yielded 92.15% ± 0.43% accuracy and 86.78% ± 0.68% macro-F1. On the untouched 826-sample test set, the model achieved 92.62% accuracy, 87.49% macro-F1, and 92.68% weighted F1. The most frequent bidirectional errors occurred between Normal and Premature Ventricular Contraction beats. These results support the use of interval-statistical features as a compact representation for multicategory ECG analysis, while showing that rare-class performance and fiducial reliability remain limiting factors for broader clinical use.
Co-Authors Abd. Rasyid Syamsuri Abdul Karim Adika Ghivan Pratama Adiwijaya Adly, Muhammad Ihsan Agus Alex Yanuar Akbar, Muh Aldebaran Bayu Nugroho Alwan, Maryam Hameed Andika Nugroho Putra Andreas Jonathan Silaban Annas, Aswar Arda Ardiyansyah Ardian Rizal Arifin, Rezki Fauzan Ashydiki Malik Asmi Citra Malina, Asmi Citra Assir, Andi Azha Alvin Rahmansyah Bilal Ibrahim Bakri Bramantya Hendrawan Yoga Budi Santosa Burchanuddin, Andi Deven Febrian Susilo Eko Darwiyanto Endro Ariyanto Erwid Jadied Mustofa Erwid M Jadied Erwid Mustofa Jadied Erwied M. Jadied Faiz Rofi Hencya Faizal Akbari Putra Fenty Alia Fikry, Maurice Fityanul Akhyar Hameed, Zainab Hasanuddin Hasanuddin Hidayatus Sholikhin Hilal Hudan Nuha I Putu Bagus Erix Wijaya Ilham Alimuddin, Ilham Imam Arif Wicaksono Indrayuni, Armi Irma Ruslina Defi Jumadil, Jumadil Juni, Juni Kahargyan Ario Nugroho Kumala Ayu Purbawati Wiyono Kusuma Adi Achmad Ledya Novamizanti Marmin, Hidayat Martin Halomoan Tamba Maurice Fikry Miftah Pramudyo Ming, Eileen Su Lee Mochamad Reza, Dandi Mohd Fadzil Hasssan Mohd Shahrizal Sunar Mohd Soperi Mohd Zahid Muhajir, Humaidid Muhamad Irsan Muhammad Alif Akbar Muhammad Aniq Wafa Muhammad Ardiansyah Pratama Muhammad Hablul Barri Muhammad Ihsan Adly Muhammad Qomaruddin Muhammad Rafli Ramadhan Muhammad Yaumil Ihza Ihza Musfirah, Andi Nadia Ariana Nia Madu Marliana Niken Dwi Wahyu Cahyani Putu Harry Gunawan Raey Faldo Rafael Sebastian Rafi Ullah Rafly Athalla Rajiv Dharma Mangruwa Ramadhan, Yusril Rifqi Syafiq Hibatul Aziz Rino Andias Anugraha Rio Guntur Utomo Rita Purnamasari Rizal, Ardian Salim M. Zaki Sobirin Sobirin Sutiyo Suyanto Suyanto Tong Boon Tang Tora Fahrudin Vera Suryani Wael M.S. Yafooz Wiyono Sutari Yafooz, Wael M.S. Yuan Wen Hau Yusril Ramadhan Zaki, Salim M. Zelmi Muhammad Adjel