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All Journal Jurnal Matematika Sainstek Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Riset Kimia Annual Research Seminar LIBRARIA Proceeding of the Electrical Engineering Computer Science and Informatics AKSIOMA Jurnal Penelitian Sains Jurnal Ecodemica : Jurnal Ekonomi Manajemen dan Bisnis Perspektif : Jurnal Ekonomi dan Manajemen Universitas Bina Sarana Informatika JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer Jurnal Infomedia JUTIM (Jurnal Teknik Informatika Musirawas) Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) Jurnal Teknik Elektro dan Komputasi (ELKOM) International Journal of Applied Sciences and Smart Technologies Jurnal Pedagogi dan Pembelajaran TADBIR: Jurnal Manajemen Dakwah FDIK IAIN Padangsidimpuan BAKTI : Jurnal Pengabdian Kepada Masyarakat Pattimura International Journal of Mathematics (PIJMath) Bakti: Jurnal Pengabdian Kepada Masyarakat
Ali Amran
Sriwijaya University
Religion Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Journal : JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING

 1 
Liver Segmentation Using Convolutional Neural Network Method with U-Net Architecture Muhammad Awaludin Djohar; Anita Desiani; Ali Amran; Sugandi Yahdin; Dewi Lestari Dwi Putri; Des Alwine Zayanti; Novi Rustiana Dewi
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 6, No 1 (2022): Issues July 2022
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v6i1.6751

Abstract

Abnormalities in the liver can be used to identify the occurrence of disorders of the liver, one of which is called liver cancer. To detect abnormalities in the liver, segmentation is needed to take part of the liver that is affected. Segmentation of the liver is usually done manually with x-rays. . This manual detection is quite time consuming to get the results of the analysis. Segmentation is a technique in the image processing process that allocates images into objects and backgrounds. Deep learning applications can be used to help segment medical images. One of the deep learning methods that is widely used for segmentation is U-Net CNN. U-Net CNN has two parts encoder and decoder which are used for image segmentation. This research applies U-Net CNN to segment the liver data image. The performance results of the application of U-Net CNN on the liver image are very goodAccuracy performance obtained is 99%, sensitivity is 99%. The specificity is 99%, the F1-Score is 98%, the Jacard coefficient is 96.46% and the DSC is 98%.  The performance achieved from the application of U-Net CNN on average is above 95%, it can be concluded that the application of U-Net CNN is very good and robust in segmenting abnormalities in the liver. This study only discusses the segmentation of the liver image. The results obtained have not been applied to the classification of types of disorders that exist in the liver yet. Further research can apply the segmentation results from the application of U-Net CNN in the problem of classifying types of liver disorders.
Application of the Waterfall Method in Software Design on Android-Based Programming Language Course Applications Anita Desiani; Ali Amran; Nuni Gofar; Chairu Nisa Apriyani; Redina An Fadhila Chaniago
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 6, No 1 (2022): Issues July 2022
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v6i1.6995

Abstract

In this era of technology and information proliferating, programming skills are needed. Technology affects every area of life from industry, business, communication, transportation, health, and others. Everyone has the same opportunity to learn and master technology thus programming language courses are needed to provide education, innovation, and improvement of skills and abilities in the field of programming and data science to the public. Until now, programming language courses still use the conventional system, where everything is done manually, from class registration, class scheduling, teaching and learning process, and payment processing which results in many archives that must be stored for administrative purposes and require a relatively large amount of time for customers to come to the course location. Therefore, an information technology-based system is needed to fix the weaknesses of the old system. In this study, an Android-based programming language course application is designed to facilitate customers and course owners in teaching and learning activities and transactions. The design in this study uses the waterfall method, which consists of five stages, needs analysis, design, code, testing, and maintenance. The results obtained from testing applications using questionnaires on programming language course applications are 80% stated by course customers, where the application is easy to use, faster, and more practical in registering. In conclusion, this designed application can make it easier for customers to carry out teaching and learning activities and transact quickly and practically.
Co-Authors Adinda Ayu Lestari Ajeng Islamia Putri Alfensi Faruk Alga Mahida Anita Desiani Apriyani, Eka Ardila, Nebi Aulia Salsabila Bambang Suprihatin Carolina Rahman Chairu Nisa Apriyani Chairunnisa Siregar, Fitri Danny Matthew Saputra Danny Matthew Saputra Des Alwine Zayanti, Des Alwine Dewi Lestari Dwi Putri Dian Cahyawati Doni Purnama Alamsyah Endang Sri Kresnawati Enyta Yuniar Evi Yuliza, Evi Ganafri, Ganafri HARDIMANSYAH HARDIMANSYAH Hasibuan, MS Hermansyah Hermansyah Hermansyah Indah Verdya Alvionita Irmeilyana Luckieta, Meiliani M Al-Ariq Maya Meilensa Mega Tiara Putri MS Hasibuan Muhammad Akbar Muhammad Awaludin Djohar Muhammad Azwar Annas Ngudiantoro . Nopri Nasir Novi Rustiana Dewi NUNI GOFAR Nur Avisa Calista Nyanyu Chika Marselina Redina An Fadhila Chaniago Shintia, Clara Siddiq Makhalli Sri Indra Maiyanti Sugandi Yahdin Triyani Triyani Yuli Andriani Yuli Andriani