Rengga Asmara

@pens.ac.id

Informatics and Computer Engineering
Politeknik Elektronika Negeri Surabaya

Rengga Asmara


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https://researchid.co/rengga.asmara

EDUCATION

Informatics and Computer Engineering

RESEARCH, TEACHING, or OTHER INTERESTS

Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Information Systems and Management
11

Scopus Publications

304

Scholar Citations

9

Scholar h-index

8

Scholar i10-index

Scopus Publications

  • Spatial-Temporal Visualization of Tuberculosis Vulnerability in Surabaya, Indonesia, Using K-Means Clustering
    Alfira Putri Nurlita, Arna Fariza, Rengga Asmara, Fitrah Maharani Humaira
    2025 International Electronics Symposium Ies 2025, 2025
    Tuberculosis (TB) is a highly infectious disease in Indonesia, including Surabaya. The high number of Tuberculosis cases in Surabaya highlights the need for vulnerability mapping to support prevention and treatment. This research aims to build a website-based spatial and temporal visualization system that can display the level of Tuberculosis vulnerability in each sub-district in the city of Surabaya. The data used included five criteria: the number of Tuberculosis cases, the number of substandard housing units, population density, the number of health facilities, and sanitation. Before clustering, a normalization process was carried out using the Simple Additive Weighting (SAW) method was applied to standardize each variable to a scale of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$0-1$</tex>, ensuring fair contribution to clustering regardless of unit differences. K-Means Clustering was then used to group the data, and clusters were labeled based on the average total of all normalized variables. Clusters with higher averages were labeled as low vulnerability, followed by medium and high. The labeled clusters were visualized on an interactive map using open map data. The system successfully grouped regions into three clusters and visualized them annually from 2019 to 2023. Evaluation showed an average <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{R}^{\mathbf{2}}$</tex> score of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{0. 5 4 2}$</tex>, indicating that the visualization reflects real-world vulnerability levels across sub-districts. This system can be a valuable tool for the Surabaya City Health Office to identify priority areas for intervention, plan prevention programs, and support data-driven decision-making efficiently and accurately.
  • Usability Evaluation of a Crowdsourced Disaster and Psychosocial Support Platform for Gen Z Users
    Widi Sarinastiti, Bherna Yughes Mahara, Veronica Lita Hapsari, Rengga Asmara, Halimatus Sa'dyah
    2025 International Electronics Symposium Ies 2025, 2025
    This study presents a usability evaluation of a web-based platform that integrates crowdsourced disaster reporting with digital psychosocial support, tailored for Generation Z users. The platform combines geospatial mapping with mental health tools such as journaling, mood tracking, and self-help content. Usability testing was conducted with ten participants aged 17–25, using seven task scenarios and the System Usability Scale (SUS) questionnaire. All participants successfully completed the tasks without observed errors. Task durations varied, with reflective tasks like journaling requiring more time. The SUS results yielded an average score above 80.3, reflecting excellent usability across all participants. In addition to quantitative findings, participant feedback revealed concerns related to data privacy, interface terminology, and emotional sensitivity when engaging with disaster-related content. While most users responded positively, some comments reflected emotional hesitation, suggesting that certain design elements may benefit from added psychological consideration. These insights contribute to a deeper understanding of usability in emotionally sensitive contexts, particularly for digitally native users.
  • Merchant Review Analysis in Food Delivery Apps: LSTM-Based Sentiment and Dual-Model Topic Classification with LLM and Logistic Regression
    Tri Hadiah Muliawati, Nabilatulhawa, Fitrah Maharani Humaira, Rengga Asmara, Arna Fariza
    2025 International Electronics Symposium Ies 2025, 2025
    Technological advancements, particularly in natural language processing and deep learning, have enabled the automatic extraction of insights from user-generated content such as user reviews. In the context of food delivery services, merchant applications like GoBiz, Shopee Partner, and Grab Merchant offer various features and policies that often cause confusion and dissatisfaction among business users. This study proposes a sentiment analysis and topic classification approach using user reviews from the Google Play Store to help merchants evaluate these merchant applications. The system employs a Long Short-Term Memory (LSTM) model for sentiment analysis and uses logistic regression and zero-shot for topic classification. Data preprocessing involved data reduction, data labeling, and text preprocessing, followed by data augmentation through rule-based and generative paraphrasing techniques. The sentiment model for GoBiz achieved the highest accuracy of 92.55% and a weighted F1-score of 94%, while the Shopee Partner model produced the most contextually relevant sentiment predictions. The system also categorized topics into key areas such as service, technical issues, platform policies, etc., providing meaningful insights to support application evaluation and future improvement.
  • Tooth and Supporting Tissue Anomalies Detection from Panoramic Radiography Using Integrating Convolution Neural Network with Batch Normalization
    International Journal of Intelligent Engineering and Systems, 2024
    Abnormalities commonly encountered in dental practice include tooth and supporting tissue issues such as caries, periapical abnormalities, resorption, and impacted third molars.Panoramic radiographs are frequently used for image scanning in dentistry and oral surgery.Diagnosing dental anomalies can be time-consuming due to the complexity of the orthodontic area, potentially leading to inaccuracies.This research proposes an end-to-end automated detection of dental and supporting tissue anomalies in patients, encompassing cavities, periapical lesions, resorption, and impacted third molars.This study evaluated the effectiveness of employing various pre-trained Convolutional Neural Network architectures, including ResNet-50, ResNeXt-50 32×4d, Inception-V3, and EfficientNet-V2.To enhance model performance, a batch normalization technique was integrated into the classification layer of these pre-trained models.Data pre-processing techniques, including horizontal and vertical flips, as well as random affine transformations, were applied to augment the dataset.Additionally, an image normalization procedure was implemented before the training and prediction phases.In the evaluation on 202 images, the integrated ResNeXt-50 32x4d model with batch normalization achieved the highest accuracy, precision, recall, and F1-score of 83.663%, 81.615%, 81.271%, and 81.066%, respectively.Based on the F1-score, this model demonstrates promising predictions of tooth and supporting tissue anomalies in an imbalanced dataset.
  • Exploring Crowdsourced Data Validation Methods for Flood Mitigation: A Comprehensive Review
    Widi Sarinastiti, Rengga Asmara, Ashafidz Fauzan D., Asy Syaffa Khoirunnisa, Suryan Mustafa E.P.W
    2024 International Electronics Symposium Shaping the Future Society 5 0 and Beyond Ies 2024 Proceeding, 2024
    Floods are One of the most devastating natural disasters and hence require immediate mitigating mechanism. This work begins by exploring the use of crowdsourced data for flood mitigation, focusing on technology-related components such as real-time processing, verification strategies and platforms. Contributions of various techniques, such as social-media, mobile-apps and Internet-of-Things devices in decreasing response-times and increasing data accuracy are also discussed. The emphasis of the project is done on Complex Data Validation, Predictive Modeling BigData Analyics for Improving Early Warning Systems. The new area for the future remains in developing data validation processing and immediate user interaction to improve efficiency while not affecting matters of privacy or security.
  • Stunting Program Classification in East Java, Indonesia from Internet News Using Location-Based and SVM
    Caesar Jalu Ananta, Arna Fariza, Rengga Asmara
    Ies 2023 International Electronics Symposium Unlocking the Potential of Immersive Technology to Live A Better Life Proceeding, 2023
    Stunting is a serious health problem for toddlers in Indonesia, especially in East Java, which makes the Indonesian government seriously try to overcome it to achieve the Golden Generation of Indonesia. To reduce the prevalence of stunting, programs related to stunting are held regularly. This research aims to compile and classify information regarding stunting programs in East Java from internet news. The solution is to create a website that visualizes the prevalence of stunting and stunting programs in East Java, Indonesia, in the form of a map that is divided into several districts in East Java. Stunting prevalence data is taken from SSGI data that has been collected by the Indonesian Ministry of Health, while information about the stunting program is taken from mined internet news, filtered using the SVM machine learning algorithm, and classified based on the location of the stunting program reported. The SVM filtering model created can classify and filter news with an accuracy rate of up to 87%. With this website, it is hoped that the public can easily get information about stunting programs in their location and that the government can conduct an interactive analysis of stunting data in East Java.
  • Automatic Tooth Enumeration on Panoramic Radiographs Using Deep Learning
    Arna Fariza, Rengga Asmara, Muhammad Oktavian Fajar Rojaby, Eha Renwi Astuti, Ramadhan Hardani Putra
    2023 IEEE 9th International Conference on Computing Engineering and Design Icced 2023, 2023
    Accurate tooth numbering is essential for dental procedures, treatment planning, and patient record management. Automatic tooth enumeration in dental panoramic radiographs is crucial in modern dental image analysis and diagnosis. Tooth enumeration in panoramic radiographs has relied on handcrafted features and traditional image processing techniques. Still, these methods often lack the accuracy and robustness required for complex cases and varied image qualities. Despite the advancements in deep learning-based object detection algorithms, a significant research gap remains in the specific domain of automatic tooth enumeration on panoramic radiographs. This research paper presents an innovative approach for automatic tooth enumeration on panoramic radiographs using the state-of-the-art You Only Look Once (YOLO) object detection framework focused on implementing the YOLOv5 library. The YOLOv5 model is evaluated as an efficient system capable of accurately detecting and enumerating individual teeth from panoramic radiographs. The 612 panoramic radiograph images evaluation shows the bounding-box results show the best tooth detection rate in the YOLOv5x model. The YOLOv5 model is generally very good at predicting tooth enumeration on panoramic radiographs in a relatively small dataset. This advancement is expected to enhance dental diagnosis and treatment planning, benefiting dental professionals and patients.
  • Evaluation of Convolutional Neural Network for Automatic Caries Detection in Digital Radiograph Panoramic on Small Dataset
    Arna Fariza, Rengga Asmara, Muhammad Oktavian Fajar Rojaby, Eha Renwi Astuti, Ramadhan Hardani Putra
    Proceedings of 2022 International Conference on Data and Software Engineering Icodse 2022, 2022
    Dental caries or tooth decay is damage to the hard tissues of the teeth that can occur in the enamel, dentin, and cementum areas. Panoramic radiography is a screening tool for tactile or visual examination of the oral cavity which is useful for further diagnosis and treatment. The process of segmentation of panoramic radiographs is a difficult process because there is no homogeneity between panoramic images with one another. Noise levels, vertebral column images, and low contrast are the main challenges in image processing. This study evaluates CNN to detect caries automatically on panoramic radiographs on a small dataset. The dataset consisted of manually cropped maxillary and mandibular premolars and molars. An augmentation strategy consisting of horizontal flip, vertical flip, and affine transformation is used to produce a wider variety of images. This study compares the architecture of non-pretrained and pretrained models consisting of 3-layer CNN, 3-layer CNN with batch normalization, ResNet18, and ResNeXt50 32×4d. Evaluation was carried out on 400 training data and 76 testing data. Combination of augmentation strategies and pre-trained ResNet18 and ResNeXt50 32×4d achieves high accuracy compared to other models.
  • Game Data Analytics using Descriptive and Predictive Mining
    Narendra Yogha Prathama, Rengga Asmara, Ali Ridho Barakbah
    Ies 2020 International Electronics Symposium the Role of Autonomous and Intelligent Systems for Human Life and Comfort, 2020
    The game industry is an industry that includes game development, marketing, and monetization. However, to be able to enter the game industry is not easy. Game developers must know how the market is going to be able to reap huge profits. By knowing the market situation, game developers can also determine whether the games made are in accordance with market conditions. Getting this information is not easy, especially for small game studios. In this research, we made a new application to find knowledge about games that are and will be trending. We used data mining is used to obtain this information. Data mining uses data from the Steam API to do clustering using the Hierarchical K-Means method and predictive using the Multiple Linear Regression method. The use of the Hierarchical K-Means method produces 3 clusters for the game's popularity level. The use of the Multiple Linear Regression method produces predictions of the game's popularity in the future. This new system will be able to help indie game studios to be able to obtain information about the condition of the gaming market thereby increasing the benefits that can be obtained.
  • The 3-dimensional arcade game application of Khalid ibn al-Walid
    K Fathoni, H A T Nurhadi, R Y Hakkun, R Asmara
    Iop Conference Series Materials Science and Engineering, 2020
    Khalid ibn al-Walid was a hero of Islam who was very meritorious and inherited many exemplary values, namely sincerity, struggle and intelligence. But many people don’t know this hero. This is due to the widely available media introduction of Khalid ibn al-Walid figures such as history books and comic books that are less interesting. This can be overcome by developing an interactive historical game Khalid ibn al-Walid. This game is built with 3D characters using the arcade genre and the First Person Shooter viewpoint. There are 4 parts in this game namely Prologue, Phase Before Islam, Islamic Phase, Epilogue. The test results show that all game features can work properly. Then the game was tested on 10 users and they stated that they had received adequate information about Khalid ibn al-Walid from this game.
  • A New Digital Application Approach of Garbage Transaction for Suroboyo Bus
    Nindy Ilhami, Arna Fariza, Rengga Asmara
    Ies 2019 International Electronics Symposium the Role of Techno Intelligence in Creating an Open Energy System Towards Energy Democracy Proceedings, 2019

RECENT SCHOLAR PUBLICATIONS

  • Spatial-Temporal Visualization of Tuberculosis Vulnerability in Surabaya, Indonesia, Using K-Means Clustering
    AP Nurlita, A Fariza, R Asmara, FM Humaira
    2025 International Electronics Symposium (IES), 751-758 , 2025
    2025
  • Usability Evaluation of a Crowdsourced Disaster and Psychosocial Support Platform for Gen Z Users
    W Sarinastiti, BY Mahara, VL Hapsari, R Asmara, H Sa'dyah
    2025 International Electronics Symposium (IES), 910-915 , 2025
    2025
  • Merchant Review Analysis in Food Delivery Apps: LSTM-Based Sentiment and Dual-Model Topic Classification with LLM and Logistic Regression
    TH Muliawati, FM Humaira, R Asmara, A Fariza
    2025 International Electronics Symposium (IES), 765-770 , 2025
    2025
  • Pembuatan Sistem Dashboard Pemantau Penerangan Jalan Umum (PJU) Terintegrasi di Daerah Keputih Surabaya
    WM Rahmawati, AS Ahsan, R Asmara, DI Permatasari, ...
    Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat 5 (3), 238-246 , 2025
    2025
    Citations: 1
  • Sistem Informasi Manajemen Budidaya Tanaman Melon Modul Pengelolaan Keuangan di CV Agro Utama Mandiri Lestari
    FM Humaira, VN Prastita, T Karlita, R Asmara
    Riau Jurnal Teknik Informatika 4 (1), 92 –99-92 –99 , 2025
    2025
  • Exploring Crowdsourced Data Validation Methods for Flood Mitigation: A Comprehensive Review
    W Sarinastiti, R Asmara, A Fauzan, AS Khoirunnisa, SM EPW
    2024 International Electronics Symposium (IES), 687-692 , 2024
    2024
    Citations: 2
  • Tooth and Supporting Tissue Anomalies Detection from Panoramic Radiography Using Integrating Convolution Neural Network with Batch Normalization.
    A Fariza, R Asmara, ER Astuti, RH Putra
    International Journal of Intelligent Engineering & Systems 17 (2) , 2024
    2024
    Citations: 6
  • Rancang Bangun Sistem Informasi Sekolah di SMK Negeri 1 Jetis Mojokerto
    AA Yunanto, HY Martono, I Prasetyaningrum, AS Ahsan, R Asmara, ...
    El-Mujtama: Jurnal Pengabdian Masyarakat 4 (2), 1393-1401 , 2024
    2024
  • Automatic Tooth Enumeration on Panoramic Radiographs Using Deep Learning
    A Fariza, R Asmara, MOF Rojaby, ER Astuti, RH Putra
    2023 IEEE 9th International Conference on Computing, Engineering and Design … , 2023
    2023
    Citations: 3
  • Stunting Program Classification in East Java, Indonesia From Internet News Using Location-Based and SVM
    CJ Ananta, A Fariza, R Asmara
    2023 International Electronics Symposium (IES), 527-532 , 2023
    2023
    Citations: 4
  • Sistem informasi dan pengelolaan disposisi surat perintah perjalanan dinas pada Dinas Lingkungan Hidup Kabupaten Nganjuk
    AN Azizah, R Asmara, W Yuwono
    Jurnal Informatika dan Teknik Elektro Terapan 11 (3) , 2023
    2023
    Citations: 5
  • SISTEM INFORMASI RADIODIAGNOSIS DARI CITRA RADIOGRAFI PANORAMIK PADA KLINIK DOKTER GIGI MENGGUNAKAN PENDEKATAN USER CENTERED DESIGN
    R Asmara, A Fariza
    Jurnal Informatika dan Teknik Elektro Terapan 11 (3) , 2023
    2023
    Citations: 3
  • Yoga pose rating using pose estimation and cosine similarity
    AD Astuti, T Karlita, R Asmara
    Jurnal Ilmu Komputer dan Informasi 16 (2), 115-124 , 2023
    2023
    Citations: 4
  • Mobile Based Mosquito Larvae Recognition from Photo Image Using Convolutional Neural Network
    A Fariza, W Yuwono, R Akbar, R Asmara, IGKP Aryawan
    Advances in Science and Technology 126, 128-136 , 2023
    2023
    Citations: 3
  • Visualisasi Spasial Temporal Tingkat Risiko Stunting di Jawa Timur Menggunakan Metode Fuzzy
    A Fariza, R Asmara, GN Istiqomah
    Jurnal Teknologi Dan Informasi 13 (1), 83-95 , 2023
    2023
    Citations: 4
  • Sistem Penjadwalan Hybrid Learning di Politeknik Elektronika Negeri Surabaya
    LS Amalia, I Prasetyaningrum, R Asmara
    Jurnal Teknologi dan Informasi 13 (1), 69-82 , 2023
    2023
    Citations: 3
  • Sistem Informasi Dan Pengolahan Data Manajemen Iso 9001: 2008 DI SMK Negeri 1 Surabaya Berbasis Web
    R Asmara
    2023
  • IMPLEMENTASI MODEL DYNAMIC PRICING KHUSUS PRODUK AGRO PERISHABLE DENGAN MEMPERTIMBANGKAN PENURUNAN KUALITAS, TINGKAT PERMINTAAN SERTA PREFERENSI PEMBELI
    ZA Fachrian, R Asmara, A Basofi, FA Saputra
    Jurnal Sistem Informasi, Teknologi Informatika dan Komputer , 2022
    2022
  • Evaluation of Convolutional Neural Network for Automatic Caries Detection in Digital Radiograph Panoramic on Small Dataset
    A Fariza, R Asmara, MOF Rojaby, ER Astuti, RH Putra
    2022 International Conference on Data and Software Engineering (ICoDSE), 65-70 , 2022
    2022
    Citations: 5
  • Cat breeds classification using compound model scaling convolutional neural networks.
    T Karlita, NA Choirunisa, R Asmara, F Setyorini
    International Conference on Applied Science and Technology on Social Science … , 2022
    2022
    Citations: 16

MOST CITED SCHOLAR PUBLICATIONS

  • Brosur interaktif berbasis augmented reality
    M Chafied, R Hakkun, R Asmara
    Institut Teknologi Sepuluh November: Surabaya , 2010
    2010
    Citations: 36
  • Deteksi Ras Kucing Menggunakan Compound Model Scaling Convolutional Neural Network
    R Asmara
    Technomedia Journal , 2021
    2021
    Citations: 27
  • Aplikasi Pembelajaran Sistem Isyarat Bahasa Indonesia (SIBI) Berbasis Voice Menggunakan OpenSIBI
    R Fatmawati, R Asmara, YR Prayogi, RY Hakkun
    Technomedia J 7 (1), 22-39 , 2022
    2022
    Citations: 18
  • Cat breeds classification using compound model scaling convolutional neural networks.
    T Karlita, NA Choirunisa, R Asmara, F Setyorini
    International Conference on Applied Science and Technology on Social Science … , 2022
    2022
    Citations: 16
  • Monitoring proyek akhir mahasiswa berbasis android pada sistem informasi manajemen pens
    PA Monitoring
    2022
    Citations: 15
  • Analisa Sentiment Masyarakat terhadap Pemilu 2019 berdasarkan Opini di Twitter menggunakan Metode Naive Bayes Classifier
    R Asmara, MF Ardiansyah, M Anshori
    INOVTEK Polbeng-Seri Informatika 5 (2), 193-204 , 2020
    2020
    Citations: 13
  • Integrasi E-Government Kabupaten Sidoarjo dengan Service Oriented Architecture (SOA)
    R Asmara, JAN Hasim, AP Utama
    Jurnal Inovtek Polbeng Seri Informatika 5 (1), 16-30 , 2020
    2020
    Citations: 10
  • Aplikasi tata kelola dan audit sistem informasi menggunakan framework COBIT pada domain PO dan AI
    R Ramadiansyah, H Martono, R Asmara
    Institut Teknologi Bandung, Bandung , 2011
    2011
    Citations: 10
  • Image Database Menggunakan Sistem Content Based Image Retrieval dengan Ekstraksi Fitur Terstuktur
    B Bagus
    Jurusan Teknologi Informasi, Politeknik Elektronika Negeri Surabaya-Institut … , 2007
    2007
    Citations: 9
  • Sistem Informasi Pemeliharaan Tempat Ibadah Dalam Efektifitas Penyaluran Dana Sumbangan
    R Asmara, AS Ahsan, MO Rachmawan
    Sistemasi: Jurnal Sistem Informasi 9 (1), 176-190 , 2020
    2020
    Citations: 7
  • Penyusunan Itinerary Otomatis Tempat Wisata Jatim Menggunakan Google Maps Dan Multitransportasi
    R Asmara
    INOVTEK Polbeng-Seri Informatika , 2019
    2019
    Citations: 7
  • Basis Data Terdistribusi untuk Aplikasi Kependudukan berbasis Web
    TA Cinderatama, W Yuwono, R Asmara
    EEPIS Final Project , 2011
    2011
    Citations: 7
  • Tooth and Supporting Tissue Anomalies Detection from Panoramic Radiography Using Integrating Convolution Neural Network with Batch Normalization.
    A Fariza, R Asmara, ER Astuti, RH Putra
    International Journal of Intelligent Engineering & Systems 17 (2) , 2024
    2024
    Citations: 6
  • Sistem informasi dan pengelolaan disposisi surat perintah perjalanan dinas pada Dinas Lingkungan Hidup Kabupaten Nganjuk
    AN Azizah, R Asmara, W Yuwono
    Jurnal Informatika dan Teknik Elektro Terapan 11 (3) , 2023
    2023
    Citations: 5
  • Evaluation of Convolutional Neural Network for Automatic Caries Detection in Digital Radiograph Panoramic on Small Dataset
    A Fariza, R Asmara, MOF Rojaby, ER Astuti, RH Putra
    2022 International Conference on Data and Software Engineering (ICoDSE), 65-70 , 2022
    2022
    Citations: 5
  • Aplikasi Tata Kelola dan Audit Informasi Menggunakan Framework COBIT pada domain DS dan ME
    A Habsoro
    EEPIS Final Project , 2012
    2012
    Citations: 5
  • Stunting Program Classification in East Java, Indonesia From Internet News Using Location-Based and SVM
    CJ Ananta, A Fariza, R Asmara
    2023 International Electronics Symposium (IES), 527-532 , 2023
    2023
    Citations: 4
  • Yoga pose rating using pose estimation and cosine similarity
    AD Astuti, T Karlita, R Asmara
    Jurnal Ilmu Komputer dan Informasi 16 (2), 115-124 , 2023
    2023
    Citations: 4
  • Visualisasi Spasial Temporal Tingkat Risiko Stunting di Jawa Timur Menggunakan Metode Fuzzy
    A Fariza, R Asmara, GN Istiqomah
    Jurnal Teknologi Dan Informasi 13 (1), 83-95 , 2023
    2023
    Citations: 4
  • Pemantauan kualitas udara terintegrasi dengan semantic web of thing
    MUH Al Rasyid, R Asmara, HY Setianto
    INFORMATICS FOR EDUCATORS AND PROFESSIONAL: Journal of Informatics 4 (2 … , 2020
    2020
    Citations: 4