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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Annual Research Seminar Proceeding of the Electrical Engineering Computer Science and Informatics JOIN (Jurnal Online Informatika) Jurnal Teknik Komputer AMIK BSI Jurnal Teknoinfo JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) Jiko (Jurnal Informatika dan komputer) JUMANJI (Jurnal Masyarakat Informatika Unjani) MIND (Multimedia Artificial Intelligent Networking Database) Journal Jurnal ICT : Information Communication & Technology METIK JURNAL JATI (Jurnal Mahasiswa Teknik Informatika) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Tematik : Jurnal Teknologi Informasi Komunikasi Jurnal Teknik Informatika (JUTIF) Informatics and Digital Expert (INDEX) AJAD : Jurnal Pengabdian kepada Masyarakat Jurnal Locus Penelitian dan Pengabdian Jurnal Algoritma Industrial Research Workshop and National Seminar Jurnal Sosial dan Sains SisInfo : Jurnal Sistem Informasi dan Informatika J-Icon : Jurnal Komputer dan Informatika Jurnal Sains Student Research Jurnal Global Ilmiah Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika
Ridwan Ilyas
Program Studi Teknik Informatika, Universitas Jenderal Achmad Yani
Aerospace Engineering Humanities Astronomy Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences Other

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Object Detection of BISINDO Sign Language Letters Using Residual Network Maulidina Norick Eriyadi; Ridwan Ilyas; Gunawan Abdillah; Asep Id Hadiana
Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika Vol. 10 No. 1 (2024): April 2024
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v10i1.3670

Abstract

Indonesian Sign Language or BISINDO is an alternative language used by people who suffer from disabilities, especially those who have hearing impairments. This language grew and developed from the deaf community, so its use is based on the visual aspect. This research aims to apply Residual Networks to detect objects in the context of Bisindo Letter Sign Language, with the hope of increasing accuracy and efficiency in letter recognition. Object detection goes through 2 stages, namely feature extraction and model training. ResNet is a type of Convolutional Neural Network (CNN) architecture that utilizes models that have been previously trained, so it can save the time required in the model development process. In this research, Residual Network (ResNet) was used for feature extraction to recognize important aspects in the Bisindo letter sign image, such as hand position, finger shape characteristics, and direction of movement. The research results show that the new dataset used as training data and test data has a fairly good ability to detect with a division of 70% train set, 20% valid set and 10% test set with size 640x640 with 300 epochs for the training model.
Imputasi Data Menggunakan Teknik Statistik Hot-Deck Untuk Klasifikasi Penyakit Menular HIV Dengan Metode Random Forest Anida Fitri Hardiantari; Fajri Rakhmat Umbara; Ridwan Ilyas
JOURNAL SAINS STUDENT RESEARCH Vol. 4 No. 6 (2026): Desember : Jurnal Sains Student Research
Publisher : CV. KAMPUS AKADEMIK PUBLISING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61722/jssr.v4i6.13255

Abstract

Infectious diseases caused by microorganisms, such as the Human Immunodeficiency Virus (HIV), remain a significant global health issue. In health data management, the problem of missing values frequently arises, potentially compromising data quality and affecting analysis results and classification processes. Therefore, appropriate methods for handling missing values are essential to maintain data quality. This study aims to implement the Hot-deck Imputation method to address missing values in an HIV dataset and to evaluate classification performance using the Random Forest algorithm. The dataset was obtained from Harvard Dataverse and split into two subsets: 80% for training and 20% for testing. Model performance was evaluated using several metrics: Accuracy, Precision, Recall, and F1-Score. The evaluation results demonstrate that the Hot-deck Imputation method successfully handled missing values, enabling the dataset to be used for classification with the Random Forest algorithm. Testing results showed an Accuracy of 56.07%, Precision of 54.86%, Recall of 63.58%, and an F1-Score of 58.90%. These results serve as a pre-processing step for handling missing values prior to the classification process for the HIV dataset.
Peringkasan Otomatis Makalah Menggunakan Maximum Marginal Relevance Wildan Pratama; Ridwan Ilyas; Fatan Kasyidi
Informatics and Digital Expert (INDEX) Vol. 3 No. 1 (2021): INDEX, MEI 2021
Publisher : LPPM Universitas Perjuangan Tasikmalaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36423/index.v3i1.677

Abstract

Makalah merupakan karya tulis yang memuat pemikiran tentang suatu masalah atau topik tertentu yang ditulis secara sistematis disertai dengan analisis yang logis objektif. Membaca merupakan proses melihat serta memahami isi dari apa yang tertulis. Proses membaca dipengaruhi beberapa factor yang diantaranya jumlah dari bacaan, sehingga penyederhaan atau perinkasan suatu bacaan contoh seperti makalah maka akan menambah kecepatan membaca. Ringkasan merupakan suatu cara yang efektif untuk menyajikan suatu karangan yang panjang dalam bentuk yang singkat. Peringkasan makalah dilakukan untuk menyajikan jumlah bacaan lebih sedikit tanpa mengurangi informasi yang disampaikan dan mempertahankan dalam bentuknya yang singkat. Dalam membuat ringkasan kita diharuskan untuk membaca keseluruhan isi makalah tersebut terlebih dahulu, untuk kemudian meringkasnya. Hal ini tentu menjadi masalah dimana ringkasan dibuat dengan tujuan untuk meminimalkan waktu membaca tetapi tetap dapat memberikan teks yang isinya langsung mengarah pada tujuan utama atau ide pokoknya. Untuk memecahkan masalah tersebut diperlukan suatu perangkat atau aplikasi yang dapat meringkas teks secara otomatis. Beberapa penelitian terdahulu menggunakan graph-based summarization untuk meringkas dokumen tunggal bahasa Indonesia. Penelitian ini membangun sistem yang dapat meringkaskan makalah menjadi ringkasan menggunakan maximum marginal relevance. maximum marginal relevance dipilih karena mampu menilai kalimat dan merankingnya sebagai acuan untuk pembentukan ringkasan. Penelitian ini mendapatkan hasil ringkasan terbaik dengan pengujian Rouge-1 dengan rata-rata yang diraih 0.68.
Co-Authors Achmad Aziz Adriana, Reyhan Agung Besti Akbar, Tzazkia Febriyana Aminuddin Ihsan, Aminuddin Anida Fitri Hardiantari Ari Sri Windyaswari Ariq Irawan, Muhamad Asendra, Irfan Asep Id Hadiana Asep Saepul Ridwan Ashaury, Herdy Aziz, Achmad Azmira Mifti Harjana Besti, Agung Chandani Nurul Hafizah Destri Wulansari Dhimas Ariya Wibiksana Djamal, Esmeralda Contesa Dwi Hendratmo Widyantoro Dwifani, Bella Melati Wiranur Eddie Khrisna Putra Esmeralda C Djamal Esmeralda C Djamal Esmeralda C. Djamal Esmeralda C. Djamal Esmeralda Contessa Djamal Fadhilahsyah Ramadhan, Muhammad Diky Fahrauk Faramayuda, Fahrauk Fajri Rakhmat Umbara Fajri Rakhmat Umbara Fajri Umbara Fatimah Indrianti, Nisa Fildzah Syarafina Fitri Nur Suciani Gunawan Abdillah Gunawan Abdillah Hadiana, Asep Id Hidayat, Ferdian Afza Iqbal Prayoga Willyana Ismail, Nursafira Khairunnisa Iyan Taufik Hidayat Janjan Nurjaman Kania Ningsih, Ade Kasyidi, Fatan Komarudin, Agus Luthfi Ahmad Fadhil Masayu Leylia Khodra Maulidina Norick Eriyadi Melina Melina Muhamad Ramdan Muhamad Rizal Firmansyah Muhammad Ramdhani, Muhammad Muhammad, Azri Naufal Akhfasy, Muhammad Neneng Nurhamidah NIDA MUTHI ANNISA Nur Shabrina, Nariswari Nurhamidah, Neneng Nursafira Khairunnisa Ismail Nurul S, Puspita Nurul Sabrina, Puspita Paramita, Veronika Santi Purnama Ginandjar, Ichas Putra, Dion Revaldy Putri, Dhiffa Namira Alifia Ramdani, Maullidan Alfa Rizki Fikri Ramdhan, Edvin Resa Abdilah Rey Aji Darusalam Reyhan Adriana Deris Reza Dwi Putra Reza Indrawan Rezki Yuniarti Rezky Yuniarti ridwan fauzi Rifaz Muhammad Sukma RIZKA KHOIRUNNISA GUNTINA, RIZKA KHOIRUNNISA Rizki Kurniawan, Moch. Sopian, Annisa Mufidah Susilowati, Merliana Tri Syarafina, Fildzah Tzazkia Febriyana Akbar Wildan Pratama Wina Witanti Wina Witanti Yamina Azmi Yoga Esa Mahendra Yulison Herry Chrisnanto Yustiana Fauziyah