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All Journal Jurnal Informatika Jurnal Ilmu Komputer dan Informasi Jurnal Ilmu Komputer Jurnal Teknik ITS IPTEK The Journal for Technology and Science Semantik Techno.Com: Jurnal Teknologi Informasi Jurnal Buana Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Ilmiah Kursor Scan : Jurnal Teknologi Informasi dan Komunikasi Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Sistem dan Informatika Scientific Journal of Informatics Journal of Information Systems Engineering and Business Intelligence Jurnal Ilmiah Pangabdhi Register: Jurnal Ilmiah Teknologi Sistem Informasi EMITTER International Journal of Engineering Technology Jurnal Inspiration Briliant: Jurnal Riset dan Konseptual JOIV : International Journal on Informatics Visualization Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) INTEGER: Journal of Information Technology IKRA-ITH Informatika : Jurnal Komputer dan Informatika JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) SISFO Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Journal of Information System,Graphics, Hospitality and Technology ILKOMNIKA: Journal of Computer Science and Applied Informatics Insyst : Journal of Intelligent System and Computation Jurnal Nasional Teknik Elektro dan Teknologi Informasi Sewagati Nusantara Journal of Computers and its Applications
Diana Purwitasari
Alumni Jurusan Teknik Informatika, Fakultas Teknologi Informasi, Institut Teknologi Sepuluh Nopember
Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mechanical Engineering Public Health Social Sciences Other

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Journal : EMITTER International Journal of Engineering Technology

 1 
An Image Processing Framework for Breast Cancer Detection Using Multi-View Mammographic Images Nada Fitrieyatul Hikmah; Tri Arief Sardjono; Windy Deftia Mertiana; Nabila Puspita Firdi; Diana Purwitasari
EMITTER International Journal of Engineering Technology Vol 10 No 1 (2022)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v10i1.695

Abstract

Breast cancer is the leading cause of cancer death in women. The early phase of breast cancer is asymptomatic, without any signs or symptoms. The earlier breast cancer can be detected, the greater chance of cure. Early detection using screening mammography is a common step for detecting the presence of breast cancer. Many studies of computer-based using breast cancer detection have been done previously. However, the detection process for craniocaudal (CC) view and mediolateral oblique (MLO) view angles were done separately. This study aims to improve the detection performance for breast cancer diagnosis with CC and MLO view analysis. An image processing framework for multi-view screening was used to improve the diagnostic results rather than single-view. Image enhancement, segmentation, and feature extraction are all part of the framework provided in this study. The stages of image quality improvement are very important because the contrast of mammographic images is relatively low, so it often overlaps between cancer tissue and normal tissue. Texture-based segmentation utilizing the first-order local entropy approach was used to segment the images. The value of the radius and the region of probable cancer were calculated using the findings of feature extraction. The results of this study show the accuracy of breast cancer detection using CC and MLO views were 88.0% and 80.5% respectively. The proposed framework was useful in the diagnosis of breast cancer, that the detection results and features help clinicians in making treatment.
Deep Learning Approaches for Automatic Drum Transcription Cahyaningtyas, Zakiya Azizah; Purwitasari, Diana; Fatichah, Chastine
EMITTER International Journal of Engineering Technology Vol 11 No 1 (2023)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v11i1.764

Abstract

Drum transcription is the task of transcribing audio or music into drum notation. Drum notation is helpful to help drummers as instruction in playing drums and could also be useful for students to learn about drum music theories. Unfortunately, transcribing music is not an easy task. A good transcription can usually be obtained only by an experienced musician. On the other side, musical notation is beneficial not only for professionals but also for amateurs. This study develops an Automatic Drum Transcription (ADT) application using the segment and classify method with Deep Learning as the classification method. The segment and classify method is divided into two steps. First, the segmentation step achieved a score of 76.14% in macro F1 after doing a grid search to tune the parameters. Second, the spectrogram feature is extracted on the detected onsets as the input for the classification models. The models are evaluated using the multi-objective optimization (MOO) of macro F1 score and time consumption for prediction. The result shows that the LSTM model outperformed the other models with MOO scores of 77.42%, 86.97%, and 82.87% on MDB Drums, IDMT-SMT Drums, and combined datasets, respectively. The model is then used in the ADT application. The application is built using the FastAPI framework, which delivers the transcription result as a drum tab.
A Combination of Lexicon-based and Distributional Representations for Classification of Indonesian Vaccine Acceptance Rates Suwida, Katon; Kardawi, Muhammad Yusuf; Purwitasari, Diana; Mabahist, Fahril
EMITTER International Journal of Engineering Technology Vol 11 No 1 (2023)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v11i1.768

Abstract

When the COVID-19 pandemic hit, the use of vaccines was advertised as the end of the pandemic by the entire world. However, the chances of vaccination depended on the sentiments of society and individuals about the vaccine. People's acceptance of vaccines can change depending on conditions and events. Social media platforms such as Twitter can be used as a source of information to find out the conditions and attitudes of the community toward the program. By implementing a machine learning technique on the COVID-19 vaccine dataset, we hope to impact the classification result with text. This study suggests three distinct machine learning models for classifying texts of the COVID-19 vaccination, namely a model based on the first lexicon using the feature extraction method; second, using the word insertion technique to utilize distribution representation; and third, a combination model of distribution representation and feature extraction based on the lexicon. From the evaluation that has been carried out, we found that a combination of lexicon-based and distributional representation methods succeeded in giving the best results for classifying the level of acceptance of the COVID-19 vaccine in Indonesia with an accuracy score of 71.44% and an F1-score of 71.43%.
Co-Authors Abdillah, Surya Abid Famasya Abdillah Abid Famasya Abdillah Achmad Affandi Addien Haniefardy Ade Afrian Adhi Nurilham Adi Surya Suwardi Ansyah Adillion, Ilham Gurat Adni Navastara, Dini Agus Budi Raharjo Agus Budi Raharjo Agus Zainal Arifin Agus Zainal Arifin Ahmad Syauqi Ahmad Syauqi Aida Muflichah Akwila Feliciano Akwila Feliciano Alif Akbar Fitrawan, Alif Akbar Alqis Rausanfita Aminul Wahib Aminul Wahib Aminul Wahib Anisa Nur Azizah Apriantoni Apriantoni Apriantoni Apriantoni Ardianto Ardianto Ariadi Retno Tri Hayati Arief Rahman Arif Fadllullah Arini Rosyadi Ario Bagus Nugroho Arrie Kurniawardhani Arya Putra Kurniawan Asiyah Nur Kholifah Bambang Setiawan Baskoro Adi Pratomo Baskoro, Fajar Benito, Davian Budi Pangestu Budi Rahardjo Budi Raharjo, Agus Buliali, Joko Lianto Cahyaningtyas, Zakiya Azizah Chastine Fatichah Chilyatun Nisa, Chilyatun Christian Sri kusuma Aditya, Christian Sri kusuma Cornelius Bagus Purnama Putra Daniel Oranova Siahaan Daniel Swanjaya Dasrit Debora Kamudi Dhian Kartika Dian Saputra Dini Adni Navastara, Dini Adni Dwi Sunaryono Dwi Sunaryono Edy Sukotjo Eko Riduwan Elshe Erviana Angely Erlinda Argyanti Nugraha Erlinda Argyanti Nugraha Esti Yuniar F.X. Arunanto Fahmi Amiq Fahrur Rozi Fajar Baskoro Fajar Baskoro Fandy Kuncoro Adianto Fandy Kuncoro Adianto Faried Effendy Febri Fernanda Febriliyan Samopa Fransiscus Xaverius Arunanto Galih Hendra Wibowo Ginardi, Raden Venantius Hari Glory Intani Pusposari Gurat Adillion, Ilham Gus Nanang Syaifuddiin Hadziq Fabroyir Hafidz, Abdan Hamidi, Mohammad Zaenuddin Handayani Tjandrasa Hani’ah, Mamluatul Hanif Affandi Hartanto Hani’ah, Mamluatul Haykal, Muhammad Farhan Herdayanto Sulistyo Putro Hilya Tsaniya Hudan Studiawan Husna, Farida Amila I Ketut Eddy Purnama I Made Satria Bimantara Ifnu Wisma Dwi Prastya Ilmi, Akhmad Bakhrul Imam Santosa Indra Lukmana Irdayanti, Marina Ivonne Soejitno Juanita, Safitri Juanita, Safitri Juli Purwanto Kardawi, Muhammad Yusuf Kautsar, Faiz Kevin Christian Hadinata Kevin Christian Hadinata Khadijah F. Hayati Kurnia Aji Tritamtama Lailatul Hidayah Luthfi Atikah M. Abdillah M. Abdul Wakhid Mabahist, Fahril Maheswari, Clarissa Luna Mauridhi Hery Purnomo Mauridhi Hery Purnomo Mirza Hamdhani Misbachul Falach Asy'ari Misbakhul Munir Irfan Subakti Mohammad Zaenuddin Hamidi Muhamad Nasir Muhammad Machmud Muhammad Mirza Muttaqi Nabila Puspita Firdi Nada Fitrieyatul Hikmah Nanik Suciati Narandha Arya Ranggianto Nova Rijati Novemi Uki A Novrindah Alvi Hasanah Nugraha, Raditya Hari Nur Hayatin Nurilham, Adhi Oktaviandra Pradita Putri Oktaviandra Pradita Putri, Oktaviandra Pradita Paramastri Ardiningrum Putri Damayanti Putu Praba Santika Putu Utami Andarini S. Putu Yuwono Kusmawan Raihan, Muhammad Rangga Kusuma Dinata Rangga Kusuma Dinata Ratih Nur Esti Anggraini, Ratih Nur Esti Rendra Dwi Lingga P. Resti Ludviani Rio Indralaksono Rizal Setya Perdana Rizka Sholikah Rizka Wakhidatus Sholikah Rizka Wakhidatus Sholikah, Rizka Wakhidatus Rizqa Afthoni Rozi, Fahrur RR. Ella Evrita Hestiandari Rully Soelaiman Rully Sulaiman Ryfial Azhar, Ryfial Safhira Maharani Safhira Maharani Safitri Juanita Safitri, Julia Salim Bin Usman Salim Bin Usman Salsabila Mazya Permataning Tyas Salsabila Salsabila Satrio Hadi Wijoyo Satrio Verdianto Satrio Verdianto Sembiring, Fred Erick Septiyan Andika Isanta Septiyan Andika Isanta Septiyawan Rosetya Wardhana Septiyawan Rosetya Wardhana Sherly Rosa Anggraeni Sherly Rosa Anggraeni Sidharta, Bayu Adjie Sihombing, Drigo Alexander Siti Rochimah Surya Sumpeno Suwida, Katon Syadza Anggraini Tanzilal Mustaqim Tegar Rachman Muzzammil Tesa Eranti Putri Tri Arief Sardjono Tsabbit Aqdami Mukhtar, Tsabbit Aqdami Umy Rizqi Verdianto, Satrio Victor Hariadi Vit Zuraida Wakhid, Muhammad Abdul Wardhana, Septiyawan Rosetya Wicaksono, Farhan Wijayanti Nurul Khotimah Wijoyo, Satrio Hadi Windy Deftia Mertiana wulansari wulansari Yanuardhi Arief Budiyono Yasinta Romadhona Yatestha, Anak Agung Yoga Yustiawan Yonathan, Vincent Yos Nugroho Yudhi Purwananto Yufis Azhar Yuhana, Umi Laili Yulia Niza Yulia Niza Yulian Findawati Zahrul Zizki Dinanto Zakiya Azizah Cahyaningtyas Zakiya Azizah Cahyaningtyas Zuraida, Vit