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All Journal Jurnal Algoritma Jurnal Wawasan Ilmiah Jurnal Teknologi Informasi dan Ilmu Komputer JAIS (Journal of Applied Intelligent System) Jurnal Ilmu Sosial dan Ilmu Politik JOIN (Jurnal Online Informatika) Edu Komputika Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Seminar Nasional Teknologi Informasi Komunikasi dan Industri JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Elektronika dan Telekomunikasi Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal ULTIMATICS Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JURTEKSI Jurnal Sistem Cerdas Aiti: Jurnal Teknologi Informasi Jurnal Teknik Informatika (JUTIF) Teknika Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal PkM MIFTEK Jurnal Algoritma Engineering Science Letter IT-Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi Integrated : Journal Of Information Technology and Vocational Education JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Journal of Intelligent Systems Technology and Informatics International Journal of Applied Information Systems and Informatics

Dede Kurniadi

Institut Teknologi Garut

Author-ID : 2656422

Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Social Sciences Other

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Implementasi Superenkripsi Dsa dan Aes 128 Bit Dalam Pengamanan File Surat Digital Nuraeni, Fitri; Amrulloh, Muhammad Fawaz; Mulyani, Asri; Kurniadi, Dede
Jurnal Algoritma Vol 22 No 1 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-1.1832

Digital signatures are important for companies to overcome distance and time constraints. Therefore, a digital signature system is needed that is not only efficient but also has a high level of security to prevent data falsification or document legality. This research contributes to improving data security and integrity by implementing DSA and AES 128 Bit superencryption in the “Paperless Room” Digital Signature application. The implementation of the technology used is such as ReactJS, NodeJS, NextJS, cryptography modules in JavaScript, and PostgreSQL databases. Evaluation is done through penetration testing and measurement of encryption and decryption performance. The results show that this superencryption successfully improves efficiency and security, with an average encryption time of 165.67 ms and decryption of 98.17 ms, as well as an entropy value of 6.2837 which reflects a high level of security. In comparison, using DSA alone requires a longer encryption time of 242.97 ms and decryption of 312.83 ms, with a lower entropy of 4.8663. These findings confirm that DSA and AES-128 superencryption offer an optimal combination of efficiency and security for securing digital mail files in an enterprise environment.

Improving Algorithm Performance using Feature Extraction for Ethereum Forecasting Tri Julianto, Indri; Kurniadi, Dede; Rohmanto, Ricky; Alisha Fauzia, Fathia
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 1 (2024): February 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i1.4872

Ethereum is a cryptocurrency that is now the second most popular digital asset after Bitcoin. High trading volume is the trigger for the popularity of this cryptocurrency. In addition, Ethereum is home to various decentralized applications and acts as a link for Decentralized Finance (DeFi) transactions, Non-Fungible Tokens (NFTs) and the use of smart contracts in the crypto space. This study aims to improve the performance of the forecasting algorithm by using feature extraction for Ethereum price forecasting. The algorithms used are neural networks, deep learning, and support vector machines. The research methodology used is Knowledge Discovery in Databases. The data set used comes from the yahoo.finance.com website regarding Ethereum prices. The results show that the neural network Algorithm is the best Algorithm compared to Deep Learning and support vector machine. The root mean square error value for the neural network before feature selection is 93,248 +/- 168,135 (micro average: 186,580 +/- 0,000) Linear Sampling method and 54,451 +/- 26,771 (micro average: 60,318 +/- 0,000) Shuffled Sampling method. Then after feature selection, the root mean square error value improved to 38,102 +/- 31,093 (micro average: 48,600 +/- 0,000) using the Shuffled Sampling method

Prewedding Location Selection Recommendation System using Count Vectorization and Cosine Similarity Kurniadi, Dede; Maulana, Ilham Ahmad
ULTIMATICS Vol 17 No 1 (2025): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v17i1.4050

Choosing the right pre-wedding location is a concern for many couples due to the many options available, which often causes confusion and is time-consuming in decision-making. Therefore, a recommendation system is needed to assist couples in determining the prewedding location that suits their preferences. This research aims to provide alternative recommendations for prewedding locations and simplify the process of selecting a suitable location. This system integrates the content-based filtering method by applying count vectorization and cosine similarity calculations to calculate and measure the level of similarity between locations based on features in the dataset when producing prewedding location recommendations. The Rapid Throwaway Prototyping method ensures the system development is done iteratively and involves direct feedback from users. The recommendation system is evaluated using the Mean Reciprocal Rank (MRR) metric to measure the effectiveness of the recommendations provided by the system. The results show that the developed prewedding location recommendation system can provide relevant location recommendations with good performance, as evidenced by the Mean Reciprocal Rank (MRR) value of 0.88, which indicates that the system is effective in placing the most relevant locations at the top of the recommendation list. The high MRR value shows the system's effectiveness in providing relevant recommendations, improving customer experience, and supporting the company's competitiveness in the prewedding documentation industry.

RMSProp Optimizer and KAN Method-Based CNN on Rupiah Banknote Classification for Visually Impaired Kurniadi, Dede; Rahmi, Murni Lestari; Balilo Jr, Benedicto B.; Aulawi, Hilmi
Engineering Science Letter Vol. 4 No. 02 (2025): Engineering Science Letter
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/IISTR.esl.00936

The visually impaired refers to individuals who experience a loss of visual function. Approximately 4 million people, or about 1.5% of Indonesia's total population, are visually impaired. They rely on their sense of touch to recognize banknote denominations in financial transactions. However, damaged banknotes often hinder identification and increase the risk of fraud. Therefore, this study aims to develop a rupiah banknote denomination classification model to assist them in conducting independent transactions. The researchers developed a CNN-KAN model with the RMSProp optimizer using a private dataset comprising 800 images of Rupiah banknotes with denominations of IDR 1,000, IDR 2,000, IDR 5,000, IDR 10,000, IDR 20,000, IDR 50,000, IDR 75,000, and IDR 100,000 from the 2016, 2020, and 2022 emission years. The dataset encompasses variations in image perspectives, lighting conditions, and the physical state of banknotes, including both intact and damaged ones, with up to 30% of the samples comprising damaged banknotes. Data augmentation techniques were implemented to improve data diversity. The dataset was then utilized for training and testing with different split ratios: 50:50, 60:40, 70:30, 80:20, and 90:10. Performance evaluation was conducted using loss, accuracy, precision, recall, and AUC-ROC metrics. Experimental results indicate that the CNN-KAN model with the RMSProp optimizer achieved optimal performance. In the 90:10 data split scenario, the model achieved 100% accuracy, precision, and recall, with an AUC-ROC of 1 and a loss of 0.008. Therefore, the CNN-KAN model with the RMSProp optimizer has been proven effective for implementing Rupiah banknote denomination detection for the visually impaired in an automated system.

Peningkatan Literasi Digital dan Pandu Digital Kepada Masyarakat Desa Cimurah Terkait Covid-19 dengan Aplikasi Android Kurniadi, Dede; Abdurrahman, Fauzan; Haekal, Mohamad Fikri; Burhanuddin, Ridwan; Nugraha, M Aldi; Ikhrom, Taufik Darul
Jurnal PkM MIFTEK Vol 1 No 2 (2020): Jurnal PkM MIFTEK
Publisher : Institut Teknologi Garut

Desa Cimurah di RT 03 RW 10 yang baru saja selesai tahap pembangunan infrastruktur Masjid dan di dalamnya juga terdapat Madrasah. Di RW 10 ini masih sangat kurang sekali dalam pencegahan COVID-19 seperti menggunakan masker, penyediaan hand sanitizer dan fasilitas umum cuci tangan. Selain hal itu karena baru saja selesai tahap pembangunan maka banyak sekali fasilitas umum yang belum dimiliki seperti alat kebersihan, mading dan peralatan belajar mengajar. Meski sudah melaksanakan pembelajaran dalam jaringan (daring) namun masih banyak aplikasi yang sangat bermanfaat dalam membantu kegiatan sehari-hari namun minim sekali digunakan oleh siswa-siswi yang bertempat di RW 10. Solusi terbaik dari permasalahan di atas ialah dengan mengadakan literasi COVID-19, literasi digital pengenalan aplikasi serta penambahan infrastruktur di RW 10. Kegiatan dilaksanakan melalui tahapan identifikasi permasalahan, bimbingan dan perencanaan, pembuatan materi, pre-test, penyampaian materi, post-test, pembuatan dan penyebaran konten COVID-19, pendataan penduduk, peningkatan infrastruktur, kemanusiaan dan pembuatan video dokumentasi. Kegiatan berhasil meningkatkan minat, pengetahuan dan keterampilan peserta. Hasil yang didapat dari kegiatan Kuliah Kerja Nyata ini yaitu masyarakat khususnya pelajar lebih paham akan pentingnya protokol kesehatan dan pemilik usaha kecil dan menengah pendapatannya meningkat dengan cara jual beli online menggunakan aplikasi android.

Implementasi Aplikasi Covid-19 Dalam Rangka Sosialisasi Terhadap Masyarakat Desa Padasuka Alamsyah, Renaldy; Safei P, M Iqbal Ismail; Rajab, Ilham Syahidatul; Wahidah, Tania Agusviani; Helmalia P, Nabilla Febriani; Kurniadi, Dede
Jurnal PkM MIFTEK Vol 1 No 2 (2020): Jurnal PkM MIFTEK
Publisher : Institut Teknologi Garut

Pandemi COVID-19 membuat banyak negara menyusun kebijakan untuk menghindari warga yang tertular bisa turun. Tiap harinya jumlah kasus positif di Indonesia terus bertambah. Kurang pahamnya masyarakat akan pandemi COVID-19 menjadi dasar untuk mengampanyekan pencegahan penyebaran COVID-19 sesuai arahan pemerintah yang dilakukan oleh perguruan tinggi melalui kegiatan Kuliah Kerja Nyata. Upaya yang dilakukan agar mencegah penyebarannya adalah dengan edukasi mengenai cuci tangan, pakai masker, jaga jarak, dan tetap bersih. Kemudian pembuatan aplikasi Pusat Informasi COVID-19 Padasuka agar masyarakat lebih mudah untuk mendapatkan informasi dan bisa melakukan check-up secara mandiri. Hasil yang didapat dari kegiatan Kuliah Kerja Nyata ini yaitu para pelajar sekolah dasar menjadi lebih paham akan pentingnya mematuhi protokol kesehatan serta masyarakat khususnya perangkat desa bisa menggunakan aplikasi ini sebagai upaya untuk mencari informasi dan dapat melakukan check-up mandiri bisa mengetahui tertular COVID-19 atau tidak secara dini.

Edukasi Cara Berpikir Komputasi Melalui Tantangan Bebras 2020 di Garut Tresnawati, Dewi; Latifah, Ayu; Nashrulloh, Muhammad Rikza; Fitriani, Leni; Rahayu, Sri; Mulyani, Asri; Cahyana, Rinda; Satria, Eri; Setiawan, Ridwan; Septiana, Yosep; Kurniadi, Dede
Jurnal PkM MIFTEK Vol 1 No 2 (2020): Jurnal PkM MIFTEK
Publisher : Institut Teknologi Garut

Bebras Computational Thinking Challenge atau Tantangan Bebras merupakan suatu kegiatan kompetisi untuk mengukur kemampuan cara berpikir komputasi dengan cara menyelesaikan soal-soal mengenai computational thinking yang disajikan melalui uraian dengan disertai gambar yang menarik. Sekolah Tinggi Teknologi Garut sebagai salah satu Biro dari Bebras Indonesia telah menyelenggarakan kegiatan ini sejak tahun 2016 hingga saat ini. Pada Tantangan tahun 2020 jumlah peserta Bebras Computational Thinking Challenge berjumlah 724 siswa yang terdiri dari 95 siswa Sekolah Dasar/MI, 313 siswa Sekolah Menengah Pertama/MTs, 316 siswa Sekolah Menengah Atas/SMK/MA. Terdapat 42 sekolah yang mengikuti kegiatan Tantangan Bebras tahun 2020. Hasil kompetisi menunjukkan kemampuan berpikir komputasi pada siswa-siswa di Garut sudah cukup tinggi dengan pencapaian nilai 100 untuk kategori Sikecil dan 90,28 untuk kategori Siaga.

Program Pelatihan Web Development untuk Komunitas Maya Ade Sutedi; Dzikri Nursyaban; Cahya Mutiara; Dede Sopiah; Diaz Radhian Salam; Diva Nuratnika Rahayu; Hasfi Syahrul Ramadhan; Ilham Muhamad Ramdan; Intan Sri Fatmalasari; Irsyad Ahmad; Kurniadi, Dede
Jurnal PkM MIFTEK Vol 2 No 1 (2021): Jurnal PkM MIFTEK
Publisher : Institut Teknologi Garut

Di era serba digital seperti saat ini, web sudah tidak asing lagi di telinga masyarakat. Bahkan, profesi sebagai Web Developer banyak diminati oleh kaum muda yang ingin menjadi freelancer. Oleh sebab itu, banyak kaum muda terutama siswa dan mahasiswa yang kini mulai tertarik untuk mempelajari Web Development. Program pelatihan ini bertujuan untuk memberikan pembelajaran dasar mengenai Web Development bagi pemula atau masyarakat umum. Metode pelaksanaanya dilakukan secara daring dengan mengadakan sesi webinar setiap minggu dan pembekalan modul secara berkala disertai tugas project yang berlangsung dalam kurun waktu satu bulan. Hasil yang dicapai yaitu dengan meningkatnya pemahaman dan kemampuan para peserta dalam membuat web sederhana.

Pengabdian Kepada Komunitas Maya Webinar Productive Daring A Pandemic di Desa Situjaya Zaqiah, Neng Nufus; Nurpatmah, Lisna; Nurlisina, Elisa; Nursa'diah, Rifania Sapta; Maulana , Muhammad Arief; Prayoga, Moch. Gumelar; Wildan, Muhammad; Syaiffani, Moch Assami; Nugraha, Nikolas Pranata; Maulana, Ahmad Rakha; Budik; Kurniadi, Dede
Jurnal PkM MIFTEK Vol 2 No 1 (2021): Jurnal PkM MIFTEK
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/miftek/v.2-1.1105

Pada masa pandemic covid-19 ini yang masih belum juga usai masalah yang dihadapi masyarakat bertambah. Salah satu masalah yang dihadapinya yaitu banyaknya masyarakat yang kehilangan pekerjaan ataupun kurangnya konsumen dan banyak terjadi masyarakat yang menjadi abai terhadap protocol kesehatan dimasa pandemic seperti ini yang dikarenakan pandemic ini belum juga usai. Program webinar productive daring a pandemic ini dilakukan dengan empat tema dengan tujuan agar masyarakat dapat menambah ilmu dan pengetahuan mengenai bagaimana menghadapi masa pandemic seperti ini dengan lebih baik, agar lebih baik dalam melakukan pemasaran secara digital, dapat megetahui agar tidak salah dalam menerimma informasi yang salah ataupun hoax dizaman seperti ini serta menambah pengetahuan mengenai peluang usaha dimasa seperti ini dikarenakan banyaknya para pekerja yang kehilangan pekerjaannya. Metodologi yang digunakan menggunakan metode online dengan dilakukannya webinar series. Hasil yang dicapai yaitu dengan diadakannya webinar series ini agar masyarakat dapat pengetahuan lebih banyak dan lebih produktif dimasa pandemic seperti ini.

Ensemble Voting Classifier Berbasis Multi-Algoritma dan Metode SMOTE untuk Klasifikasi Penyakit Jantung Dede Kurniadi; Asri Indah Pertiwi; Asri Mulyani
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 14 No 2: Mei 2025
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v14i2.17157

The heart is a vital organ responsible for pumping blood throughout the body. Hence, impairments can disrupt blood circulation and are the leading causes of mortality worldwide. World Health Organization (WHO) reported that, in 2021, the mortality rate attributed to heart disease reached a significant number. In Indonesia, the prevalence of heart disease attained 1.5%. Consequently, it is essential to prevent and detect heart disease at an early stage utilizing machine learning technologies. This study aims to develop a heart disease classification model using the naïve Bayes and random forest algorithms through the ensemble voting classifier approach. The data were obtained from Kaggle, comprising 1,000 records with 14 variables, including one classification target. Imbalanced data were handled using the synthetic minority oversampling technique (SMOTE), while feature selection was conducted in consultation with cardiologists to ensure clinical relevance. The model was trained using the naïve Bayes algorithm, random forest, and integration of both through the ensemble voting classifier method, in contrast to previous studies that only compared several algorithms to determine the highest accuracy. The test results showed that the model trained with the ensemble voting classifier yielded the best performance, with an accuracy, precision, recall, and F1 score of 98.28%, 98.41%, 98.41%, and 98.41%, respectively. This study demonstrates that the ensemble voting classifier method provides better accuracy than the individual algorithms. This model falls within the excellent classification category and is expected to contribute to the medical field and support the development of decision-support systems for diagnosing heart disease.

Co-Authors Abania, Nia Abdulah, Farhan Naufal Abdurrahman, Fauzan Abdussalam, Iqbal Abdussalam Abdusy Syakur Amin Ade Sutedi Ade Sutedi Ade Sutedi, Ade Adiwangsa, Alfian Akmal Agus Hermawan Agus Nugraha Agustiansyah, Yoga Ahmad Habib Lutfi Aisyah Fitri Islami Ajif, Arvin Muhammad Ajiz, Rafi Nurkholiq Akbar, Gugun Geusan Alamsyah, Renaldy Aldy Rialdy Atmadja Ali Djamhuri Alisha Fauzia, Fathia Alkamal, Chaerulsyah Alvin Zainal Musthafa Alwan Nul Hakim Amrulloh, Muhammad Fawaz Andri Saepuloh Aneu Suci Nurjanah Asri Indah Pertiwi Asri Mulyani Asri Rahayu Ningsih Ayu Suryani B. Balilo Jr , Benedicto B. Balilo Jr, Benedicto Balilo Jr, Benedicto B. Barlinti Maryam Budik Burhanuddin, Ridwan Cahya Mutiara Dede Sopiah Della Adelia Anugrah Detila Rostilawati Dewi Tresnawati Dhea Arynie Noor Annisa Diar Nur Rizky Diaz Radhian Salam Diazki, Moch Haiqal Diki Jaelani Dini Destiani Siti Fatimah Diva Nuratnika Rahayu Dudy Mohammad Arifin Dyka Afan Afthori Dzikri Nursyaban Efi Sofiah Elsen, Rickard Eri Satria Erick Fernando B311087192 Erwan Yani Erwan Yani, Erwan Erwin Gunadhi Rahayu, Raden Erwin Widianto Fadillah, Hadi Bagus Faisal, Ridwan Nur Fajar Rahman Faturrohman, Nadhif Fauziah, Fathia Alisha Fauziyah, Asyifa Fikri Zakaria Rahman Firmansyah, Marshal Fitri Nuraeni Fitriani, Ranti Fitriyani Gelar Panca Ginanjar Ghilman Hasbi Basith Gisna Fauzian Dermawan H. Bunyamin Hadi Wijaya, Tryana Haekal, Mohamad Fikri Hamzah Nurrifqi Fakhri Fikrillah Hari Ilham Nur Akbar Hasfi Syahrul Ramadhan Hazar, Aura Fitria Helmalia P, Nabilla Febriani Hendri Aji Pangestu Heri Johari Heri Suhendar Heri Suhendar Hilmi Aulawi Ida Farida Ikbal Lukmanul Hakim Ikhrom, Taufik Darul Ikmal Muhammad Fadhil Ilham Muhamad Ramdan Imas Dewi Ariyanti Inda Muliana Indra Trisna Raharja Indri Tri Julianto Indri Tri Julianto Intan Sri Fatmalasari Irawan, Muhammad Randy Irfan Qusaeri Irfanov, Muhammad Irsyad Ahmad Iskandar, Joko Jajang Jaenudin Jajang Romansyah Jembar, Tegar Hanafi Khaerunisa, Nisrina Khoerunisa, Sarah Kusmayadi, Kusmayadi Latif, A. Abdul Latifah, Ayu Leni Fitriani Leni Fitriani, Leni Lia Amelia Lindayani, Lindayani M. Mesa Fauzi Mahendra Akbar Musadad Maulana , Muhammad Arief Maulana, Ahmad Rakha Maulana, Ilham Ahmad Maulana, Yusep Maulina, Wina Senja Meta Regita Mochamad Deni Ramdani Muhamad Solihin Muhammad Abdul Yusup Hanifah Muhammad Affan Al Sidqi Muhammad Rikza Nashrulloh Muhammad Saleh Muhammad Sanusi Muhammad Wildan Muliana, Inda Muttaqin, Moch Riefky Chaerul Nita Nurliawati Nugraha, M Aldi Nugraha, Nikolas Pranata Nurfadillah, Rifa Sri Nurhaliza, Nabila Putri Nurlisina, Elisa Nurpatmah, Lisna Nursa'diah, Rifania Sapta Nursyaban, Dzikri Nurul Fauziah Nurul Khumaida Nurzaman, Muhammad Zein Omar Komarudin Pratama, Reifalga Gais Prayoga, Moch. Gumelar Putri, Mita Hidayani Raharja, Indra Trisna Rahayu, Diva Nuratnika Rahayu, Raden Erwin Gunadhi Rahmat, Agil Rahmi, Murni Lestari Rajab, Ilham Syahidatul Ramdhan, Dekha Ramdhani Hidayat Randy Wardan Ridwan Setiawan Ridwan Setiawan Ridwan Setiawan Ridwan Setiawan Rifky Muhammad Shidiq Rinda Cahyana Rinda Cahyana Risfiyanisa Fasha Rizki Fauziah Roeri Fajri Firdaus Rohman, Fauza Rohmanto, Ricky Rostina Sundayana Rubi Setiawan Rudi Sutrio Safei P, M Iqbal Ismail Sarah Khoerunisa Sermana, Elsa Maharani Sheny Puspita Indriyani Siti Rima Fauziyah Sofwan Hamdan Fikri Sopiah, Dede Sri Intan Multajam Sri Mulyani Lestari Sri Rahayu SRI RAHAYU Sri Rahayu Syahrul Sidiq Syaiffani, Moch Assami Tina Maryana Undang Indrajaya W, Faksi Ahmad Wahidah, Tania Agusviani Wiwit Septiani Yanti Sofiyanti Yayat Supriatna Yoga Handoko Agustin Yosep Septiana Yosep Septiana Yuni Yuliani Yusfar Ilhaqul Choer Yusuf Mauluddin Zaqiah, Neng Nufus Zulkarnaen, Ade Iskandar

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