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All Journal IJITEE (International Journal of Information Technology and Electrical Engineering) Jatilima : Jurnal Multimedia Dan Teknologi Informasi Jurnal Teknimedia: Teknologi Informasi dan Multimedia Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Emerging Information Science and Technology Duta Abdimas: Jurnal Pengabdian Masyarakat jabdimasunipem JKTi - Jurnal Keilmuan Teknologi Informasi Jurnal Pengabdian Masyarakat Terapan
Krisna Nuresa Qodri
Universitas Muhammadiyah Klaten
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Public Health Social Sciences

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Image Analysis for MRI-Based Brain Tumor Classification Using Deep Learning Krisna Nuresa Qodri; Indah Soesanti; Hanung Adi Nugroho
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 5, No 1 (2021): March 2021
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijitee.62663

Abstract

Tumors are cells that grow abnormally and uncontrollably, whereas brain tumors are abnormally growing cells growing in or near the brain. It is estimated that 23,890 adults (13,590 males and 10,300 females) in the United States and 3,540 children under the age of 15 would be diagnosed with a brain tumor. Meanwhile, there are over 250 cases in Indonesia of patients afflicted with brain tumors, both adults and infants. The doctor or medical personnel usually conducted a radiological test that commonly performed using magnetic resonance image (MRI) to identify the brain tumor. From several studies, each researcher claims that the results of their proposed method can detect brain tumors with high accuracy; however, there are still flaws in their methods. This paper will discuss the classification of MRI-based brain tumors using deep learning and transfer learning. Transfer learning allows for various domains, functions, and distributions used in training and research. This research used a public dataset. The dataset comprises 253 images, divided into 98 tumor-free brain images and 155 tumor images. Residual Network (ResNet), Neural Architecture Search Network (NASNet), Xception, DenseNet, and Visual Geometry Group (VGG) are the techniques that will use in this paper. The results got to show that the ResNet50 model gets 96% for the accuracy, and VGG16 gets 96% for the accuracy. The results obtained indicate that transfer learning can handle medical images.
Analisis sentimen terhadap pelayanan Kesehatan berdasarkan ulasan Google Maps menggunakan BERT Ardiansyah; Adika Sri Widagdo; Krisna Nuresa Qodri; Fachruddin Edi Nugroho Saputro; Nisrina Akbar Rizky P
JURNAL FASILKOM Vol 13 No 02 (2023): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v13i02.5170

Abstract

The utilization of technology has developed in various scientific fields, without exception in health. Hospitals, health centers, and clinics are part of the health sector. Thus, it must evolve according to health service standards and patient measures or service user satisfaction that needs to be measured using sentiment analysis. The Media to give opinions to Health service providers is Google Maps. However, the anomaly is that the reviews and the given text are sometimes not correlated. Thus, The utilization of sentiment analysis using the scientific branch of artificial intelligence, namely Natural Language Processing (NLP), is an effective way to infer opinions. The research concluded that the BERT indobenchmark/indobert-base-p1 model has good performance to use of Indonesian text classification with a dataset of 4228 data after preprocessing, which at the beginning of the collection process obtained data as much as 4748 data. Split datasets into 3 data, namely training, validation, and test data, with a ratio of 70:30:30. The experimental results, The researchers found that the model allows the use of the model with other Indonesian texts. The results are 0.85 for accuracy and weighted avg, and macro avg 0.75 on the validation data training process. While the testing data training process is 0.86 for accuracy and weighted avg, the macro avg 0.73. In addition, researchers found that services are the most frequent topic in Health Services. Even though health services have improved, positive sentiment is the highest compared to other sentiment classes.
PEMANFAATAN SAM DAN YOLOV8 UNTUK DETEKSI DAN SEGMENTATION MRI TUMOR OTAK Ardiansyah, Ardiansyah; Qodri, Krisna Nuresa; Banna, Dion Al; Al-Baihaqi, Muhammad Zulfikhar
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 5 No. 1 (2024): Juni 2024
Publisher : Badan Penelitian dan Pengabdian Masyarakat (BP2M) STMIK Syaikh Zainuddin NW Anjani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46764/teknimedia.v5i1.192

Abstract

The development of artificial intelligence (AI) is specific to the field of Computer Vision (CV) to obtain information based on data contained in visual media. AI in the healthcare field such as image recognition and Deep Learning (DL) is a discussion that is often used as an object of research and development. The health sector Limitation is the emergence of AI utilization in the health sector, which encourages DL research. Segmentation Anything Model (SAM) and YOLOv8 are new algorithms introduced. Thus, this research aims to measure the utilization of SAM and YOLOv8 for making the detection and segmentation of Brain Tumor MRI data. Before the training process, researchers first compared roboflow segmentation and the SAM model. The dataset was labeled with a Bounding Box by experts. The dataset contains 455 gliomas, 550 meningiomas, and 620 pituitaries. The research concluded that the utilization of SAM greatly simplified the annotation process. The segmentation YOLOv8 obtained Box accuracy results for all classes of 86% precision, 87% Recall, 89% mAP50, and 71% mAP 50-95. The mask performance evaluation gets the results of 86% precision, 87% Recall, 89% mAP50, and 70% mAP50-95. The research obtained the YOLOv8n-seg model to get excellent results even though it is a tiny model of YOLOv8. This study found the glioma tumor class to be the class with the lowest results because the dataset used was not much. The researcher encourages other researchers to use data augmentation to increase the use of datasets for each class to provide better results.
The Influence of Developing an Understanding of Basic Programming Concepts Through Educational Games as A Learning Method For Elementary School Students. Kurnianti, Apriliya; Praditia, Rizky Nanda; Qodri, Krisna Nuresa
Emerging Information Science and Technology Vol. 5 No. 2 (2024): November
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v5i2.24781

Abstract

Integrating engaging learning methods into the educational landscape has become increasingly crucial for enhancing student understanding and engagement. This study investigates the impact of educational games as a learning method for improving elementary school students' comprehension of basic programming concepts. The research hypothesizes that educational games can significantly enhance the understanding of programming concepts by making abstract ideas more tangible and engaging through interactive and enjoyable learning environments. Using a quasi-experimental design, the study involved two groups of elementary school students: the experimental group, which utilized an educational game designed for teaching introductory programming concepts, and the control group, which received traditional instruction. Both groups underwent assessments of their understanding of basic programming concepts before and after the intervention through standardized tests. The results demonstrated a statistically significant improvement in the scores of students in the experimental group compared to those in the control group. This suggests that educational games not only aid in better understanding complex subjects such as programming and increase students' motivation and engagement levels. The findings of this study contribute to educational practices by illustrating how educational games can effectively support the introduction and teaching of programming at an early age within the elementary educational system. Furthermore, the study highlights the potential of integrating such tools into standard curricula to enhance student learning across various subjects. The study urges future research to explore the long-term impacts of educational games on learning outcomes and how these tools can be further integrated into the educational system
Innovative Learning Strategy Using H5P to Create Engaging Learning Modules for Students Kurnianti, Apriliya; Isnanda, Reza Giga; Farkhani, Jodi Nur; Qodri, Krisna Nuresa
Emerging Information Science and Technology Vol. 6 No. 1 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v6i1.27169

Abstract

Technology in education plays a crucial role in delivering effective learning, especially for students in Indonesian schools abroad. This study aims to develop and evaluate an interactive learning website based on WordPress and H5P, with a focus on Indonesian culture, particularly traditional dance. The website was developed locally using XAMPP and integrated with interactive videos, quizzes, and simulations. Evaluation results indicate that most students felt a greater connection to Indonesian culture, and the learning process became more engaging. This strategy has proven to enhance student engagement and strengthen national identity in multicultural environments
UI/UX Prototype Design of Employee Presence Application Using Design Thinking Sri Widagdo, Adika; Sapurtro , Fachruddin Edi Nugroho; Qodri, Krisna Nuresa; Ronaldo, Rizal Adimas
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 02 (2025): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i02.1220

Abstract

Employee Presence management is a crucial aspect of organizational productivity. However, manual Presence systems often result in inefficiencies, requiring alternative technological solutions. This study aims to design a UI/UX prototype for a mobile-based Presence application at Universitas Muhammadiyah Klaten using the Design Thinking approach. The research follows five stages: Empathize, Define, Ideate, Prototype, and Test. Data collection involved surveys and interviews with 62 respondents, including lecturers, staff, and education personnel. The prototype was evaluated using the System Usability Scale (SUS), resulting in a usability score of 76.6% in the "Good" category. The findings indicate that the proposed design effectively addresses the limitations of manual presence systems, enhancing user experience and efficiency. Future improvements include additional features such as a "forgot password" option, different presence button and broader usability testing. This study suggests that a well-designed presence application can streamline presence recording and improve operational effectiveness.
Prediksi Analitik untuk Penyakit Ginjal Kronis: Perbandingan Metode Machine Learning Nuresa Qodri, Krisna; Rausan Fikri, Muhammad; Ardi, Luthfi
JKTI Jurnal Keilmuan Teknologi Informasi Vol 1 No 1 (2025)
Publisher : Universitas Muhammadiyah Klaten

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61902/jkti.v1i1.1686

Abstract

Chronic kidney disease (CKD) is a progressive malady defined by reduced glomerular filtration rate, increased urinary albumin excretion or both, and is a major global public health concern with an extremely high unmet medical need. CKD is estimated to occur in 8-16% of the worldwide population and results in a substantially reduced life expectancy. Early detection and accurate prediction of CKD is crucial to reduce health complications such as hypertension, anemia, and premature death. This study aims to develop CKD prediction models using three machine learning methods: Random Forest, Naive Bayes, and Support Vector Machine, then compare the performance of each method. The dataset used is the CKD dataset from UCI Machine Learning Repository consisting of 400 instances with 24 attributes. Experimental results show that Random Forest achieved 90.50% accuracy, Naive Bayes achieved the highest accuracy of 94.21%, while SVM achieved 88.84% accuracy. The results indicate that Naive Bayes provides the best performance for chronic kidney disease prediction with superior accuracy compared to other methods. This prediction model can assist medical practitioners in early detection and appropriate clinical decision-making for CKD patient management.
Implementasi Deteksi Tumor Otak Menggunakan YOLOv11 dan Flask Ardiansyah, Ardiansyah; Sri Widagdo, Adika; Nuresa Qodri, Krisna; Hidayani, Diesti; Romadhani, Mustofa
JURNAL FASILKOM Vol. 15 No. 2 (2025): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v15i2.9703

Abstract

Kecerdasan buatan (AI) telah mengalami kemajuan yang sangat signifikan untuk membantu kehidupan masyarakat salah satunya adalah bidang kesehatan. Kemajuan AI didorong karena banyaknya kesalahan yang diakibatkan beberapa faktor fundamental dan tingginya permintaan dari masyarakat terhadap layanan kesehatan terus meningkat. AI juga mampu meminimalkan kesalahan diagnosa maupun pengobatan dalam praktik klinis pasien seperti deteksi tumor otak. Algoritma YOLO yang sering digunakan untuk deteksi objek karena akurasi yang tinggi. YOLO juga dapat digunakan untuk real-time diagnosa menjadi nilai tambah pada algoritma tersebut. YOLOv11 merupakan algoritma terbaru dan memiliki performa yang lebih baik dibandingkan seri sebelumnya. Meskipun begitu, tantangan terhadap keterbatasan dataset menjadi salah satu permasalahan yang perlu diselesaikan. Penelitian yang dilakukan memiliki tujuan yaitu meningkatkan jumlah dataset citra medis menggunakan Data Augmentasi dan mengintegrasikan algoritma YOLO dengan Flask untuk memberikan tampilan yang lebih baik kepada pengguna. Penelitian yang dilakukan menggunakan Data Augmentasi pada dataset menggunakan teknik Flip (Horizontal dan Vertical), 90° Rotate (Clockwise, Counter-Clockwise, Upside Down), serta penambahan Noise: Up to 1.5% of pixels. Hasilnya, diperoleh F1-score 0.951 dari 4 kelas (0.902 Glioma, 0.989 Meningioma, 0.915 Pituitary, dan 0.997 No tumor). Sehingga terbukti efektif mengatasi keterbatasan data. Selanjutnya, Integrasi YOLO dengan Flask dapat memberikan tampilan deteksi objek yang lebih baik tanpa menurunkan skor dari hasil deteksi objek tumor otak, sehingga Flask dapat dijadikan framework yang dipertimbangkan untuk pengembangan interface machine learning
Pelatihan Pemanfaatan Media Informasi Dalam Pelayanan Informasi Obat Kepada Masyarakat Di SMK Muhammadiyah 1 Prambanan Nurhaini, Rahmi; Sri Widagdo, Adika; Edi Nugroho Saputro, Fachruddin; Nuresa Qodri, Krisna; Kumalasari, Puput; Pandu Cahyadi, Fian
Duta Abdimas Vol. 2 No. 2 (2023): Duta Abdimas: Jurnal Pengabdian Masyarakat
Publisher : LPPM Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47701/abdimas.v2i2.2806

Abstract

SMK Muhammadiyah 1 Prambanan merupakan salah satu amal usaha muhammadiyah yang bergerak dibidang pendidikan dan salah satu peminatannya adalah bidang Farmasi Klinis dan Komunitas. Sebagai calon farmasis dibidang pelayanan farmasi klinis dan komunitas, siswa diharuskan memiliki pemahaman tentang edukasi pelayanan informasi obat serta pemanfaatan media guna meningkatkan kualitas edukasi dan pemahaman pasien. Salah satu upaya dalam menjamin kompetensi keahlian siswa pada peminatan tersebut, adalah salah satunya dengan Ujian Kompetensi Keahlian (UKK). Salah satu mata uji pada program keahlian tersebut adalah promosi kesehatan atau desain kemasan produk yang sesuai dengan pangsa pasar. Meskipun demikian terdapat beberapa kendala dari siswa yang dihadapi, yaitu masih terbatasnya pelatihan pelayanan informasi obat, masih minimnya pemanfaatan media digital dalam proses pelayanan informasi obat, dan hanya beberapa bagian dari power point yang diajarkan dan belum ada pemanfaatan media lain selain power point yang pernah diajarkan guna memberikan Pelayanan Informasi Obat (PIO). Solusi yang ditawarkan pada pengabdian ini adalah pelatihan tentang macam-macam edukasi untuk meningkatkan pelayanan kefarmasian, pelatihan pemanfaatan media edukasi seperti Microsoft PowerPoint, brosur guna mendukung pelayanan informasi obat dan pendampingan pembuatan media edukasi kepada siswa. Hasil dari kegiatan ini adalah para siswa mengetahui arti penting edukasi terhadap peningkatan pengetahuan tentang kesehatan dan pengobatan, bisa membuat perencanaan edukasi kesehatan dan obat kepada kelompok masyarakat serta mengetahui media edukasi yang sesuai dengan kelompok masyarakat, mengetahui penggunaan aplikasi grafis dan power point lebih mendalam sehingga dapat diterapkan pada produk farmasi, cukup terampil pada proses pembuatan logo sederhana dan berkas presentasi.
PELATIHAN DIGITAL MARKETING UNTUK MENINGKATKAN KINERJA PELAYANAN HAPUS TATO PRO CARE Fachruddin Edi Nugroho Saputro; Adika Sri Widagdo; Ardiansyah; Habib Ismail; Krisna Nuresa Qodri; Nisrina Akbar Rizky Putri
Jurnal Abdimas Universitas Insan Pembangunan Indonesia Vol. 2 No. 1 (2024): Abdimas Unipem
Publisher : LPPM Universitas Insan Pembangunan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58217/jabdimasunipem.v2i1.21

Abstract

Promotion is an activity that aims to inform, influence, and influence consumer attitudesand behavior so that they are interested in and buy the products or services offered. In itsapplication, promotion has many methods including direct promotion or calledconventional promotion. Conventional promotion refers to promotion methods orstrategies that have long been used before the digital era or have not utilized informationtechnology. Promotion by utilizing information technology also known as digital marketingis an innovation in the marketing process promotional activities that involve the use oftechnology and digital platforms to achieve marketing goals to expand and enhancetraditional marketing functions.‘Hapus Tato Pro Care’ have constraints that have notmaximized the use of information technology in the promotion of tattoo removal servicesand the limited reach of targeting in the promotion of tattoo removal services. Byconducting training and being guided in creating content that will be used as promotionalmedia. In addition, participants will be guided to create captions and keywords used onsocial media to attract the attention of other social media users, participants gain skills inmanaging social media and doing graphic design better.
Co-Authors Adika Sri Widagdo Adika Sri Widagdo Al-Baihaqi, Muhammad Zulfikhar Ardi, Luthfi Ardiansyah Ardiansyah Ardiansyah Banna, Dion Al Edi Nugroho Saputro, Fachruddin Erma Widyastuti Fachruddin Edi Nugroho Saputro Farkhani, Jodi Nur Habib Ismail Hanung Adi Nugroho Hidayani, Diesti Indah Soesanti Kumalasari, Puput Kurnianti, Apriliya Nisrina Akbar Rizky Putri Pandu Cahyadi, Fian Praditia, Rizky Nanda Putri, Nisrina Akbar Rizky Rahmi Nurhaini, Rahmi Rausan Fikri, Muhammad Reza Giga Isnanda, Reza Giga Romadhani, Mustofa Ronaldo, Rizal Adimas Sapurtro , Fachruddin Edi Nugroho Saputro, Fachruddin Edi Nugroho Sri Widagdo, Adika Widagdo, Adika Sri