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Journal : JURIKOM (Jurnal Riset Komputer)

Desain Masterplan Direktorat Sistem Teknologi Informasi Universitas Teknologi Sumbawa Menggunakan Framework Garuda Smart City I Made Widiarta; Shinta Esabella; Nora Dery Sofya; Erwin Mardinata
JURIKOM (Jurnal Riset Komputer) Vol 9, No 6 (2022): Desember 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i6.5173

Abstract

The purpose of this study was to design a master plan for the Directorate of Information Systems and Technology, Sumbawa University of Technology (UTS), an educational institution located in Sumbawa, West Nusa Tenggara Province with an area of 60 hectares, has 32 study programs and has 3,772 active students. Master plan create using the smart campus model adopted from the Garuda Smart City framework. The smart campus model consists of three main models, namely smart people, smart governance, and smart infrastructure, technology and environment. The development of intelligent people includes services to Education Personnel (Tendik), services to teaching staff, and services to students. Meanwhile, smart governance refers to a written document issued officially in the form of a circular letter by the Directorate of Systems and Information Technology. The third model, namely smart infrastructure, technology and environment which includes hardware and software. With the draft master plan for the Directorate of Information Systems and Technology, this is one way to realize good quality, efficient and integrated information technology services for the entire academic community of the Sumbawa University of Technology
Perbandingan Kinerja Deep Learning Dalam Pendeteksian Kerusakan Biji Kopi Yayang Hafifah; Kahlil Muchtar; Ahmadiar Ahmadiar; Shinta Esabella
JURIKOM (Jurnal Riset Komputer) Vol 9, No 6 (2022): Desember 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i6.5151

Abstract

Coffee is one of the most consumed beverages today. The coffee beans are first sorted by the farmers. This is because there are many types of coffee beans that differ in terms of shape and texture. After sorting, farmers must detect whether the coffee beans are damaged or not. The process is still done manually by coffee farmers so it takes a long time and results in errors due to lack of knowledge about coffee. In addition, efforts are also being made to improve the quality of the coffee beans which will affect the selling value of the coffee beans. Based on these problems, this study aims to design a deep learning model to detect coffee bean damage and evaluate the architecture of ResNet-34 and VGG-16. The classification model built using a Convolutional Neural Network (CNN) is expected to be able to know a better architecture and be able to detect damaged or normal coffee beans accurately and precisely
Co-Authors Abdul Karim Abdul Karim Abdul Rahman Adriani Tamo Ina Talu Afriliansyah, Jonathan Ahmad Juliansyah Ahmadiar Ahmadiar Aldrin Alia Wartiningsih Alsepianingsih, Feti Andi Ernawati Andriani, Titi Anna Sayuni Aprianti, Ade Lilis Arbain Ardiansyah Putra Ardiansyah Putra Aries ZA, Muhammad Aryanto, Nova Aswin Try Juniarta Athifah Muthi’ah Atmawan Oktavia, Siska Aulia, Masyitah Awaliah, Rita Azzahratun Jannah, Linda Azzam, Muhammad R. Bayu Fajar Pratama Bobbi Kurniawan Nasution, Muhammad Brenny Prasetyo Waty Cece Listiana Umbara Chairul Hudaya Darmawan, Indra Deby Monalisa Simanjuntak Delia, Khofifah Desi Maulidyawati Desiana Puspita Desyanti - Desyanti Doddy Teguh Yuwono E, Ekastini Eri Sasmita Susanto Erwin Mardinata Erwin Mardinata Eva Rahmiati Evi Nurmala Fahliyah Diani Fahmi Yuliono Fahri Hamdani Farida Idifitriani Fatihhurroyyan Fatihurroyyan Fauzi Widyawati Fithriati Fitriana, Yasinta Bella Ghifron Akhiru Syahroni Gunawan Gunawan Habib Shibghatallah Halid Nuryadi Hanif Fauzan Ramadhan Harri Gunawan Haryati Haryati Hasanuddin Hermanto, Koko Hidayatullah, Muhammad Hilmy Adrizul Rifqi Hidayat Houri Sobirin Hudaya, Chairul I Made Widiarta I Made Widiarta Ika Gita Listiana Iksan Adiasa Ilmiah, Zaddwi Jiwa Imanura Bagaskara, Kukuh Indah Putrianti Iskandar Fitri Jaya, Ahmad Jonathan Afriliansyah Juanda Hakim Lubis Julianingsih Juliansyah, Ahmad Julkarnain, M. Juniardi Akhir Putra Kahlil Muchtar Kantari, Yuliana Tissya Karisma, Yana Kiki Rizki Kusmanto Kusmanto Kusmanto Liska Della Erlanda M. Julkarnain Mardinata, Erwin Maria Dissriany Vista Banggur Marliana Mashabai, Ismi Mesran, Mesran Mhd Ali Hanafiah Mhd Alwi Syaputra Pulungan Miftahul Haq Muhammad Aries ZA Muhammad Bobbi Kurniawan Nasution Muhammad Fauzi Muhammad Hidayatullah Muhammad Hidayatullah Muhammad Hudzaifah Asy Syidiq Muhammad R. Azzam Muhammad Rifqi Fawzan Muhammad Saleh Muhammad Syukur Mulyanto, Yudi Nasution, Mhd Bobbi Kurniawan Nawassyarif Neva Nurliana Nisa, Haerun Nora Dery Sofya Ismail Nuryadi, Halid Paris Ali Topan Purba, Elvitrianim Rahmadin, Aku Nur Reski, Tri Reza Sangga Rasefta Rizka Irjiba Robban, Farisan Rodianto, Rodianto Sari, Nikmata Sobirin, Houri Sofya, Nora Dery Sri Lis Apriliani Surya, Rizky Andika Suryadi, Sudi Susainanda, Riki Susilawati, Tri Syahidah, Khaula T. Ndomaina, David Teguh Hamdala Tirta, Andy Titi Andriani Topan, Paris Ali Uswatun Hasanah W, Yunanri Warda Wulandari Wartiningsih, Alia Wayan Satru Widiantara, Putu Widiantara Widiarta, I Made Widiya Lis Susana Winda Aryani Wiryatari, Dimas Yanti, Sahri Yasinta Bella Fitriana Yayang Hafifah Yuliadi Yuliadi Yuliadi Yuliadi Yuliadi Yuliadi Yunanri Yunanri W