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Journal : Scientific Journal of Informatics

Pneumothorax Detection System in Thoracic Radiography Images Using CNN Method Fardana, Nouvel Izza; Isnanto, R. Rizal; Nurhayati, Oky Dwi
Scientific Journal of Informatics Vol. 11 No. 4: November 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i4.16635

Abstract

Purpose: This research aims to develop an automatic pneumothorax detection system using Convolutional Neural Networks (CNN) to classify thoracic radiography images. By leveraging CNN's effectiveness in identifying medical abnormalities, the system seeks to enhance diagnostic accuracy, reduce evaluation time, and minimize subjective interpretation errors. The output will provide a predicted label of "pneumothorax" or "non-pneumothorax," facilitating faster clinical treatment and improving diagnostic services while supporting radiologists in making more accurate and efficient decisions for this critical condition. Methods: This research employs an experimental deep learning approach using Convolutional Neural Networks (CNN) to detect pneumothorax in thoracic radiography images. The CNN model is trained on an annotated dataset with preprocessing steps, including zooming, brightness adjustment, flipping and format adjustment, followed by performance evaluation using accuracy, precision, recall, and F1 score metrics. Result: The results showed that the CNN model detected pneumothorax with 79.59% accuracy, a loss of 1.3056, and 1,092 correct predictions out of 1,372 test data. Precision was 51.12%, recall 78.62%, and F1 score 61.96%, confirming the system's potential, though further optimization is needed. Novelty: The novelty of this research lies in developing an automated pneumothorax detection system using a CNN architecture, improving diagnostic accuracy and efficiency. Despite high accuracy, precision and recall can be improved. Future research can focus on optimizing the model and applying data augmentation techniques.
User Experience Improvement (MSMEs and Buyers) Mobile AR Using Design Thinking Methods Dwiyanasari, Desty; Nurhayati, Oky Dwi; Surarso, Bayu; Nugraheni, Dinar
Scientific Journal of Informatics Vol. 12 No. 2: May 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v12i2.24088

Abstract

Purpose: This research aims to improve the User Experience (UX) of Augmented Reality (AR) mobile applications for MSMEs and buyers through the Design Thinking method. This research solves the problem of suboptimal UX in AR-based mobile applications. This study hypothesizes that the application of Design Thinking can result in significant improvements in the UX of AR mobile applications, which is evidenced by an increase in heuristic evaluation scores. Methods: The Design Thinking approach (Empathize, Define, Ideate, Prototype, Test) is implemented. Data were collected through interviews, observations, and heuristic evaluation questionnaires. Result: Initial heuristic testing showed several usability problems in the developed AR mobile applications, such as Help and Documentation (H10), Recognition Rather than Recall (H6), and Error Prevention (H5). After the application of the Design Thinking method and design iteration, the heuristic testing showed that the results of the evaluation comparison before and after the improvement showed a high effectiveness of the corrective actions taken, with an average decrease in severity score of 37% based on the Nielsen scale (0–4), indicating that the most critical and major issues were successfully reduced to cosmetic or minor levels. Novelty: This research contributes in the form of a practical framework to improve the UX of AR mobile applications for MSMEs and buyers by utilizing the Design Thinking method. The results of this research can be a reference for developers in designing user-friendly AR mobile applications.
Elementary School Accreditation Assessment Using Fuzzy Tsukamoto and SMARTER Method Rahmawati, Nurhita; Nurhayati, Oky Dwi; Surarso, Bayu
Scientific Journal of Informatics Vol. 12 No. 4: November 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v12i4.30729

Abstract

Purpose: The primary objective of this study is to develop and validate an Elementary School Accreditation Evaluation Model that is both measurable and fair. The proposed model integrates the Fuzzy Tsukamoto method to calculate and consistently generate the final score of each alternative, and the SMARTER method to produce a prioritized ranking that serves as a practical guide for schools in their efforts to improve and strengthen quality. Methods: This study integrates the Fuzzy Tsukamoto method to process numerical data through a rule-based inference mechanism. Simultaneously, the SMARTER method is employed to systematically assign weights to each criterion and sub-criterion using the Rank Order Centroid (ROC) approach. The evaluation is carried out on 16 alternatives based on four main criteria. The research data are derived from the IASP 2020 instrument issued by BAN-S/M, which serves as the official accreditation standard for schools and madrasahs in Indonesia. Result: The developed structured assessment model proved effective. Through ROC weighting, Criterion K1 was identified as the main determining factor (0.611). System validation using Fuzzy Logic showed a high level of consistency (87.5% agreement) with the manual assessor's decisions, confirming the model's accuracy in replicating assessments based on data triangulation. The SMARTER ranking provides targeted recommendations, placing Alternatives A13, A2, A7, and A8 as standards to be maintained, while pointing to A3 as the priority for immediate improvement. Novelty: This study offers a novel approach by integrating the Fuzzy Tsukamoto and SMARTER methods within the context of primary school accreditation a combination that has been rarely explored in previous research. The proposed model not only generates evaluation scores but also produces a ranking system that can serve as a reference for school evaluation.
Co-Authors Achmad Hidayatno Adhi Susanto Adi Mora Tunggul Adi, Yudi Restu Agung Budi Prasetijo Agung Budi Prasetijo Agus Subhan Akbar, Agus Subhan Agus Subkhi Hermawan Agus Supriyanto Ahmad Aviv Mahmudi Ahmad Muzami Aji Yudha Al Iman, Yusraka Dimas Alim Muadzani Ambrina Kundyanirum Amrina Rosyada Anggi Anugraha Putra Anggit Sri Herlambang Anggoro Mukti Anisa Eka Utami Annisa Hedlina Hendraputri Aria Hendrawan, Aria Arief Puji Eka Prasetya Atik Zilziana Muflihati Noor Aulia Medisina Ramadhan Bayu Surarso Budi Warsito Catur Edi Widodo Christine Dewi Damar Wicaksono Danal Meizantaka Daeanza Dania Eridani Dania Eridani Deryan Gelrandy Diana Nur Afifah, Diana Nur Dinar Mutiara Kusumo Nugraheni Dwiana Okviandini Dwiyanasari, Desty Eggy Listya Sutigno Eko Didik Widianto Eko Sediyono Fardana, Nouvel Izza Fathuddin, Harits Febi Andrea Renatha Galuh Boy Hertantyo Gayuh Nurul Huda Gumay, Naretha Kawadha Pasemah Hadi Hilmawan Hanna Mariana Baun, Hanna Mariana hastuti, Isti Pudji Hendra Pria Utama Hengki Hengki Ike Pertiwi Ike Pertiwi Windasari Ike Pertiwi Windasari Ikhsan, Hammas Zulfikar Imaduddin Abdul Rahim Indra Aditia Indra Permana Isti Pudjihastuti Julce Adiana Sidette, Julce Adiana Juwanda, Farikhin Keszya Wabang Kurniawan Teguh Martono Kusworo Adi Lazuardi Arsy Lia Dorothy M Irfan Syarif Hidayatullah M. Rizki Kurniawan Maesadji Tjokronagoro Menur Wahyu Pangestika, Menur Wahyu Merdekawati, Utami Mey Fenny Wati Simanjuntak Mifta Ardianti Migunani Migunani Muhammad Nasrullah Muhammad Naufal Prasetyo Muhammad Ridwan Asad Mustafid Mustafid Ningrum, Alifvia Arvi Ninik Rustanti Nofiyati Nofiyati, Nofiyati Nugraheni, Dinar Nugroho Adhi Santoso Nurazizah Nurazizah Nurhuda Maulana Nurul Arifa Nuryanto . Otong Saeful Bachri Prio Pambudi R Rizal Isnanto R. Rizal Isnanto R. Rizal Isnanto Rahmat Gernowo Rahmawati, Nurhita Reza Najib Hidayat Reza Setiawan Rian Haris Muda Nasution Rinta Kridalukmana Risma Septiana Rismawan Fajril Falah Riyadhi Sholikhin Rizki Galang Rahmadani Satriaji Cahyo Nugroho Siswo Sumardiono Sri Widodo, Thomas Suryo Mulyawan Raharjo Suryono Suryono Teguh Hananto Widodo Thomas Sri Widodo Tristy Meinawati Tsalavin, Muhammad Hafiz Tyas Panorama Nan Cerah Ulinuha, Ajik Wahyul Amien Syafei Wijaya Wahyudi Akbar Yessy Kurniasari Yudhi Kasih Pasaribu Yudi Eko Windarto Yudi Restu Adi Yusuf Arya Yudanto Zaskia Wiedya Sahardevi