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All Journal Voteteknika (Vocational Teknik Elektronika dan Informatika) Syntax Jurnal Informatika KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Sinkron : Jurnal dan Penelitian Teknik Informatika International Journal of Artificial Intelligence Research JURNAL MEDIA INFORMATIKA BUDIDARMA Faktor Exacta JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Sisfokom (Sistem Informasi dan Komputer) Conference on Innovation and Application of Science and Technology (CIASTECH) Building of Informatics, Technology and Science Systematics Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Scientific Student Journal for Information, Technology and Science Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Buana Pengabdian Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Pengabdian Masyarakat Nasional Inovasi Gagasan Abdimas & Kuliah Kerja Nyata Scientific Journal of Informatics
Baihaqi, Kiki Ahmad
Universitas Buana Perjuangan Karawang
Religion Agriculture, Biological Sciences & Forestry Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Medicine & Pharmacology Public Health Social Sciences Other

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Journal : Systematics

 1 
Analisis Vulnerability pada Website Universitas Singaperbangsa Karawang menggunakan Acunetix Vulnerability Mayasari, Rini; Ali Ridha, Azhari; Juardi, Didi; Ahmad Baihaqi, Kiki
SYSTEMATICS Vol 2 No 1 (2020): April 2020
Publisher : Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35706/sys.v2i1.3450

Abstract

Isu keamanan website merupakan hal yang sangat krusial pada masa sekarang, sehingga masalah keamanan dan kerentanan website menjadi sangat penting dalam mengembangkan aplikasi website. Dalam mendeteksi kerentanan dalam penelitian ini digunakan metode kualitatif dengan memanfaatkan perangkat lunak Acunetix Vulnerability Scanner, yang dimulai dari tahap inisiasi, investigasi, pengujian dan verifikasi. Hasil dari penelitian ini, tingkt kerentanan website Universitas Singaperbangsa Karawang berada pada level 2 yaitu Medium, sehingga kemungkinan untuk mengakses dan mengumpulkan informasi sensitif, karena dengan infromasi tersebut penyusup bisa dengan mudah mengeksploitasi kelemahan yang ada.
Analisis Vulnerability pada Website Universitas Singaperbangsa Karawang menggunakan Acunetix Vulnerability Rini Mayasari; Azhari Ali Ridha; Didi Juardi; Kiki Ahmad Baihaqi
SYSTEMATICS Vol 2 No 1 (2020): April 2020
Publisher : Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35706/sys.v2i1.3450

Abstract

Isu keamanan website merupakan hal yang sangat krusial pada masa sekarang, sehingga masalah keamanan dan kerentanan website menjadi sangat penting dalam mengembangkan aplikasi website. Dalam mendeteksi kerentanan dalam penelitian ini digunakan metode kualitatif dengan memanfaatkan perangkat lunak Acunetix Vulnerability Scanner, yang dimulai dari tahap inisiasi, investigasi, pengujian dan verifikasi. Hasil dari penelitian ini, tingkt kerentanan website Universitas Singaperbangsa Karawang berada pada level 2 yaitu Medium, sehingga kemungkinan untuk mengakses dan mengumpulkan informasi sensitif, karena dengan infromasi tersebut penyusup bisa dengan mudah mengeksploitasi kelemahan yang ada.
Securing the Website Login System with the SHA256 Generating Method and Time-based One-time Password (TOTP) Iman Permana; Mardi Hardjianto; Kiki Ahmad Baihaqi
SYSTEMATICS Vol 2 No 2 (2020): August 2020
Publisher : Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35706/sys.v2i2.3756

Abstract

Security to enter a system has a very important role because as the main entrance to access data sources. But often lack the attention of the owners and managers of information systems. To reduce these weaknesses, one method that is widely used today is to use One-Time password, which is where the password we have becomes dynamic, meaning that at a certain time the password is always changing, the positive side is that it makes it difficult for others to steal our passwords because besides representative passwords that are difficult to understand and passwords are always changing. This study discusses One-Time Password installed on a mobile device where the password is randomized using a combination of two algorithms, namely SHA256 and Time-based One Time Password. The development of this login method can reduce the level of theft of passwords owned by users who are entitled to access information sources.
Application of Convolution Neural Network Algorithm for Rice Type Detection Using Yolo v3: Penerapan Algoritma Convolution Neural Network untuk Deteksi Jenis Padi Menggunakan Yolo v3 Kiki Ahmad Baihaqi; Yana Cahyana
SYSTEMATICS Vol 3 No 2 (2021): August 2021
Publisher : Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35706/sys.v3i2.5874

Abstract

Rice is a staple food that contains a lot of energy for human life. There are several types of rice that are often sold in rice shops in general, namely IR42 rice, Pera rice, glutinous rice and Pandan fragrant rice. For now, there are still many people who do not recognize the 4 types of rice, especially millennials, for this reason, research is carried out on the introduction of rice types. The purpose of this study is to make it easier for buyers to identify the type of rice that is in the rice shop so as to minimize fraud by rice traders. The method used in this study is the YOLO (You Only Look Once) v3 method for detecting rice types. The implementation of the image detection process using YOLO (You Only Look Once) v3 has been tested for 12 samples. Based on the results of testing 12 detection experiments on digital image objects, it was obtained 100% where in the picture there were 4 types of rice, 4 grains of rice and 3 types of rice shapes.
Co-Authors Adi Rizky Pratama Adinata, Abdul Rohim Aditya Zatnika Agung Susilo Yuda Irawan Agustin, Rachmayanti Tri Ahmad Fauzi Ahmad Fauzi April Lia Hananto Awal, Elsa Elvira Azhari Ali Ridha Azhari, Febrian Akbar Bagja Nugraha Bagus Setiawan Bambang Sukowo Billy Ibrahim Hasbi Candra Zonyfar Candra Zonyfar Danny Manongga Deden Wahiddin Dendi Prana Yudha Deny Adi Faldano Devi Fitrianah Didi Juardi Dwiasnati, Saruni Eko Purwirawansyah Faisal, Sutan Fauzi Ahmad Muda Fitria, Denisa Habib Abdullah Hanny Hikmayanti Handayani Hardjianto, Mardi Hendry Hendryanto Dwi Purnomo Herfandi Herfandi Heryana, Nono Iman Permana Indah Listiyowati Indra, Jamaludin Iwan Setyawan Juardi, Didi Krisna Perdana Jaya Sitompul Madani, Puja Milenia Sriwildan Mayasari, Rini Muhammad Raja Nurhusen Narwan Nahrudin Nisa Utami, Nisa Nurdin, Cherry Januar Nurlaelasari, Euis Pertiwi, Anggun Rafikoh, Zahra Anggun Rahmat Rahmat Reza Avrizal Reza Maulana Rini Mayasari Rini Mayasari Rizki Septian Akbar Rohana, Tatang Salsa Desmalia Saruni Dwiasnati Siregar, Amril Mutoi suhliyyah Suja Priyanto Sulistya, Dwi Sutan Faisal Tatang Rohana Tatang Rohana Ulfatus Soleha Waiddin, Deden Wardi Karto Destian Yana Cahyana Yudo Devianto Zonyfar, Candra