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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Penelitian Pendidikan IPA (JPPIPA) bit-Tech Jurnal Sistem informasi dan informatika (SIMIKA) Jurnal Informasi dan Teknologi Jurnal Perangkat Lunak Jurnal Computer Science and Information Technology (CoSciTech) Journal of Computer Scine and Information Technology Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Jurnal Komtekinfo Jurnal Informatika Ekonomi Bisnis RJOCS (Riau Journal of Computer Science) JR : Jurnal Responsive Teknik Informatika The Indonesian Journal of Computer Science Jurnal Responsive Teknik Informatika
Sumijan
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Agriculture, Biological Sciences & Forestry Arts Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Physics

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Journal : Jurnal Computer Science and Information Technology (CoSciTech)

 1 
Audit Keamanan Website Menggunakan Acunetix Web Vulnerability (Studi Kasus Di SMK Muhammadiyah 3 Terpadu Pekanbaru) Supriyanto, Boby; Sumijan; Yuhandri
Computer Science and Information Technology Vol 5 No 1 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i1.6705

Abstract

Perkembangan teknologi informasi berkembang pesat seiring dengan pertumbuhan penggunanya. Contoh dari perkembangan teknologi adalah penggunaan website untuk mendukung kegiatan pembelajaran. Website merupakan kumpulan halaman web yang dapat diakses secara publik. Website dapat terdiri dari teks, gambar, video, dan media suara lainnya. Namun dengan berkembangnya suatu teknologi, maka perkembangan kerentanan atau serangan terhadap teknologi tersebut juga bertambah. Berdasarkan laporan tahunan monitoring keamanan siber tahun 2021 oleh Badan Siber dan Sandi Negara (BSSN), terdapat lebih dari 1,6 miliar serangan siber yang telah terjadi di Indonesia. Penelitian ini akan menggunakan Acunetix Web Vulnerability Scanner (WVS) untuk mengaudit keamanan website SMK Muhammadiyah 2 Terpadu Pekanbaru (SMK MUTI). Penelitian ini akan mengkaji kelemahan keamanan website SMK MUTI dan membahas bagaimana Acunetix Web Vulnerability dapat membantu dalam meningkatkan tingkat keamanan website tersebut. Metode Vulnerability Assessment (VA) yang digunakan adalah analisis deskriptif, yaitu data yang diperoleh disajikan dalam bentuk tabel, sehingga memungkinkan untuk memperjelas hasil analisis yang dilakukan dalam meng-audit. Berdasarkan data yang diperoleh dari hasil scanning iterasi 1 yang dilakukan, website SMK MUTI berada pada level ancaman 3 tergolong tinggi dengan ditemukan 192 peringatan atau kerentanan, dimana 2 diantaranya berada pada level tinggi dan 11 berada pada level sedang. Berdasarkan audit, dilakukan perbaikan dan pengujian pada penelitian di situs SMK MUTI ini, hasil yang telah dilakukan tingkat ancaman yang dicapai berada pada level 1, dimana pada level tinggi, jumlah kerentanan menjadi 0 dan tingkat dukungan juga menjadi 0, sehingga dapat disimpulkan bahwa situs SMK MUTI saat ini dengan status level 1 dapat bebas dari kerentanan keamanan.
Implementasi Convolutional Neural Netowork Untuk Klasifikasi Citra KTP-El SATRIA, SATRIA; Sumijan; Billy Hendrik
Computer Science and Information Technology Vol 5 No 1 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i1.6708

Abstract

The Electronic Identity Card (e-KTP) serves as the official proof of identity for residents, issued by the relevant implementing agency across the entire territory of the Unitary State of the Republic of Indonesia. Mandatory for both Indonesian citizens (WNI) and foreigners (WNA) holding a Permanent Stay Permit (ITAP) and aged 17 or married, the e-KTP is susceptible to potential damage, often arising from factors such as prolonged usage or improper handling. Physical damage to the e-KTP can impede the document's ability to accurately verify identity, potentially impacting public services and government administration. This research aims to assess the condition of e-KTPs, determining whether they are in good or damaged condition. The study employs the Convolutional Neural Network (CNN) method, known for its significant results in image recognition by attempting to emulate the image recognition system in the human visual cortex, facilitating the processing of image information. This method comprises two architectural layers: Feature Learning and Classification. The dataset utilized in this research comprises images of e-KTPs sourced from the Population and Civil Registration Office of Bengkalis Regency, totaling 400 images categorized into two classes: 200 for good condition and 200 for damaged condition. The research findings enable the determination of the e-KTP image's condition, achieving a 90% accuracy rate.
Implementasi Data Mining untuk Pemetaan Persebaran Infeksi Human Imunodeficiency Virus di Provinsi Riau Fadillah, Riszki; Sarjon Defit; Sumijan
Computer Science and Information Technology Vol 5 No 1 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i1.6712

Abstract

Based on data released by the Riau Provincial Health Service until October 2022, there were 8034 people living with HIV/AIDS (PLWHA), of which 3,711 were in the AIDS stage. Human Immunodeficiency Virus is a virus that attacks the body's immune system, while Acquired ImmunoDeficiency Syndrome (AIDS) is a collection of diseases caused by the HIV virus due to damage to the immune system in humans, resulting in the body being susceptible to potential diseases. This research aims to map the spread of HIV/AIDS in Riau Province to prevent and control the spread of the HIV/AIDS virus by the relevant agencies. The method used in this research is Fuzzy C-Means to carry out clustering in districts/cities which will then be visualized using a map or with a Geography Informatics System (GIS). The Fuzzy C-Means method is a data grouping technique that uses the existence of each data point in A cluster as determined by the degree of membership. The output from Fuzzy C-Means is a series of cluster centers and several degrees of membership for each data point. The data used in this research is HIV/AIDS data in Riau Province from 1997 to 2023. Based on the results of the tests that have been carried out, the results obtained are 3 clusters, namely the safe zone has 5 districts/cities, the alert zone has 5 districts/cities, and There are 2 districts/cities in the dangerous zone. There needs to be treatment through the Health Service, the AIDS Control Commission, and related Non-Governmental Organizations (NGOs) to prevent and control HIV/AIDS in Riau Province for areas that have a high potential for the spread of HIV/AIDS. The tests that have been carried out obtain a minimum error value of 0.008251 in the 8th iteration with the performance of Fuzzy C-Means being 13.271 in the distance between clusters.
Penerapan jst perceptron untuk mengenali huruf hijaiyah sebagai media pembelajaran anak usia dini Dwiprihatmo, Mohammad Reza; Sarjon Defit; Sumijan
Computer Science and Information Technology Vol 5 No 1 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i1.6718

Abstract

Computer vision is the transformation of data obtained or taken from a webcam into another form to determine the decisions to be taken. All forms of transformation are carried out to achieve certain goals. One of the techniques that supports the application of computer vision to a system is digital image processing, because the aim of digital image processing techniques is to transform images into digital format so that they can be processed by a computer. Computer vision and digital image processing can be implemented into a hijaiyah letter pattern recognition system on cards that have been prepared and placed on a white board which is supported by the perceptron algorithm artificial neural network method which is used as a learning technique for the system to be able to learn and recognize hijaiyah letter patterns. This research aims to enable computers to read hijaiyah letters using a camera. The methods used in this research are image processing and the perceptron algorithm. The data set processed in this research comes from 783 hijaiyah letters consisting of 29 hijaiyah letters and 30 samples per each hijaiyah letter. How it works is that each hijaiyah letter is captured using a webcam and produces a continuous image which is transformed into a digital image and processed using several techniques including grayscale images, binary images and cropping images. The results of this research are that the system is able to identify and classify hijaiyah letters with a testing rate of 99,746%. Therefore, this research can be a reference in the modern teaching and learning process and is expected to help children's interest in learning hijaiyah letters.
Analisis Data Forensik Pada Rekaman CCTV Menggunakan Metode National Institute Of Standard Techology (NIST) Ilham Asy'ari; Yuhandri; Sumijan
Computer Science and Information Technology Vol 5 No 3 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i3.7779

Abstract

CCTV (Closed-Circuit Television) recordings have become one of the important instruments in monitoring and securing various places such as companies, commercial buildings, public institutions, and households. CCTV recordings are often vital evidence in investigating crimes, accidents, or other incidents. However, in addition to the visual content stored in CCTV recordings, metadata also plays an essential role in forensic analysis and event reconstruction. The NIST method has developed several techniques and guidelines for forensic metadata analysis on CCTV recordings. This research aims to explore and apply the forensic metadata analysis methods recommended by NIST (National Institute of Standards and Technology) in the context of CCTV recordings. By involving forensic data analysis techniques and information security principles, this study will delve into the potential of metadata analysis in supporting criminal investigations, event reconstructions, and meeting the security standards established by NIST. This research is crucial in the context of digital security and modern forensic investigations. The outcome of applying the NIST methods in forensic data analysis of CCTV recordings is the preparation of an official report derived from the stages outlined in the NIST method, so that the report can serve as a reference in court, and the authenticity of the digital evidence can be validated. By applying the NIST method in forensic data analysis of CCTV recordings, the case handling process becomes structured and adheres to procedures, with a valid report ensuring the integrity of the digital evidence.
Co-Authors Aal, Defrizal Adawiyah, Quratih Ade, Ade Puspita Sari Aditra Agustin, Riris Akbar, Muhamad Rafi Aktavera, Beni Aldi, Febri Auriga, Wira Billy Hendrik Budiantoro, Hendro Budiarti, Lela dedi irawan Defit , Sarjon Deti Karmanita Devi Yuliana, Devi Dewi, Dian Cyntia Dinul Akhiyar Dwiprihatmo, Mohammad Reza Enggari, Sofika Eriyanto, Joko Fadillah, Riszki Fajrul Islami Feriantano Sundang Pranata Feriantano Sundang Pranata Geni, Bias Yulisa Gunadi Widi Nurcahyo Habdi, Habdi Hakim, Wijaya Hendrik, Billy Ilham Asy'ari Jufriadif Na`am, Jufriadif Julius Santony Lubis, Siti Sahara Meiditra, Irzon Mulyanda, Sandy Nst, Ely Nurhalizah Nurcahyo , Gunadi Widi Okmarizal, Bisma Pipin Refina Afindania Pulungan, Akhiruddin Putri, Yolan Ananda Rais, Edo Rinaldi Refina Afindania, Pipin Resnawita Ridho, Ridho Afwan Ridwan, Ridwan Ruri Hartika Zain Sarjon Defit Sarjon Defit Satria Satria, Satria Sovia, Rini Supriyanto, Boby Suri, Ghea Paulina Surmayanti Syafri Arlis Syaputra, Eka B. Syofneri, Nandel Ulfa, Ulia Vidyanti, Angela Yani, Zulfitri Yanti, Salma Nofri Yuda, Fitra Yuda Yuhandri