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Web-Based Dashboard for Monitoring Penetration Testing Activities Based on OWASP Standards Yansyah Saputra Wijaya; Imaniar Ramadhani
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 6, No 1 (2020): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v16i1.17019

Abstract

Financial Services Authority Regulation concerning Application of Risk Management in the Use of Information Technology by Commercial Banks which requires Banks to ensure information security to maintain which must be done periodically at least once a year. The most popular way to have security is through pentest, to determine an application whether it is safe and successfully passed the pentest, we need a measurement standard, specifically for web applications, the standard commonly used is OWASP. However, OWASP has a very large list of vulnerabilities, so to simplify the process of monitoring the pentest process in an organization we need a tool that can visualize existing vulnerabilities from various applications to be more easily measured, calculated, and monitored during the pentest process. The tool commonly used to present information to managers is a Dashboard. The dashboard produced in this research is the monitoring dashboard of pentest monitoring activities, it is made using the PHP programming language so that it is web-based and uses the OWASP standard until 2017. The system is also capable of displaying application vulnerabilities based on their frequency of appearance.
Monitize Facebook Video untuk Bisnis di SMK YAPIM Siak Hulu Junadhi; Mardainis; Agustin; Hadi Asnal; Yansyah Saputra Wijaya
J-PEMAS - Jurnal Pengabdian Masyarakat Vol. 1 No. 1 (2020): Jurnal Pengabdian Masyarakat J_PEMAS
Publisher : STMIK Amik Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (340.936 KB)

Abstract

SMK YAPIM Siak Hulu terletak di Kecamatan Siak Hulu Kabupaten Kampar. Selain kompetensi utama yang harus dimiliki oleh siswa sesuai jurusannya,perlu juga kompetensi tambahan yaitu tentang bisnis teknologi di era digital, yang populer saat ini adalah ad breaks. Ad Breaks merupakan salah satu fitur untuk memonitisasi akun facebook yang dapat menghasilkan uang bagi pengguna dengan menayangkan jeda iklan komersil di sela-sela video. Tujuan dari kegiatan pengabdian masyarakat ini adalah Untuk meningkatkan pengetahuan siswa tentang software camtasia, ad break, dan fanpage facebook setelah pelatihan dan memberikan pengetahuan kepada siswa tentang cara pembuatan konten video dengan software camtasia dan fanpage facebook. Hasil dari kegiatan pengabdian masyarakat ini adalah siswa-siswi SMK YAPIM Siak Hulu bisa membuat video konten dengan Software Camtasia dan mampu mengunggahnya ke Fanpage Facebook dan siswa-siswi memilki semangat yang tinggi untuk mengeksplorasi kemampuan mereka terkait aplikasi Software Camtasia dan media Fanpage Facebook.
PENERAPAN ALGORITHMA APRIORI UNTUK MENEMUKAN POLA PEMILIHAN KONSENTRASI STUDI MAHASISWA Muhammad Jamaris; Hadi Asnal; Yansyah Saputra Wijaya
AL-ULUM: JURNAL SAINS DAN TEKNOLOGI Vol 5, No 2 (2020)
Publisher : Universitas Islam Kalimantan Muhammad Arsyad Al Banjari

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (549.812 KB) | DOI: 10.31602/ajst.v5i2.2882

Abstract

Exploring information or new knowledge from existing data sets is an important point of the data mining process, such as a collection of course value data that has been stored, but its potential has not been raised to find new benefits. While on the other hand there is the problem of how to find the concentration of studies that are in accordance with the competencies of the students themselves. This study was conducted to find the concentration selection pattern, based on some of the best value data from the courses that have been taken using the Apriori Algorithma, where the rules in this method will be used to find the pattern in question. Using a minimum support value of 70% produces rules with 5 item sets, namely courses in logic and algorithms, system analysis, system design, web programming and software engineering. The pattern / rule produced can be a guide for students in choosing concentration.
Chatbot Designing Information Service for New Student Registration Based on AIML and Machine Learning Yansyah Wijaya; Rahmaddeni; Fransiskus Zoromi
JAIA - Journal of Artificial Intelligence and Applications Vol. 1 No. 1 (2020): JAIA - Journal of Artificial Intelligence and Applications
Publisher : STMIK Amik Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (863.021 KB) | DOI: 10.33372/jaia.v1i1.638

Abstract

One of the efforts made by universities to serve prospective students is by providing consulting services and information that is usually carried out directly at the booth provided, through phone service or live chat support available on the college website. Increased visitors will result in waiting times due to limited availability of officers, which results in decreased satisfaction of prospective new students, moreover this service is only available during campus operating hours. One alternative solution to overcome this problem is to use Chatbot, able to answer questions raised by prospective new students which can be categorized as Frequently Asked Questions abbreviated as FAQ. Chatbot technology can be developed with a variety of AI (Artificial Intelligence) techniques. One of them is the AIML (Artificial Intelligence Markup Language) technique. One of the main drawbacks of AIML is that there is no reasoning ability so a learning system that is focused on supervised learning is needed. In the chatbot that will be built the learning process uses a selective neural conversational model or commonly called the Deep Semantic Similarity Model (DSSM) developed by Microsoft. Meanwhile, the measurement of chatbot performance will be done using Confusion Matrix which is a method of evaluating the performance of the algorithm from Machine Learning (ML). The results of the study stated that the chatbot system that was built was able to answer questions posed by prospective students properly and correctly while the questions were available in the chatbot knowledge base.
4 Star Complementary Food Menu Recommendation System Using the Mobile-Based Fuzzy Multiple Attribute Decision Making (FMADM) Method Rahmaddeni; Fransiskus Zoromi; Yansyah Saputra Wijaya; M. Khairul Anam
JAIA - Journal of Artificial Intelligence and Applications Vol. 1 No. 2 (2021): JAIA - Journal of Artificial Intelligence and Applications
Publisher : STMIK Amik Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1269.823 KB) | DOI: 10.33372/jaia.v1i2.793

Abstract

Toddler in the age category of six to twenty-four months should be ready to be given complementary food. In order to fulfill the nutritional needs for the toddler's growth, complementary foods must be sufficient for the kid according to their age while still paying attention to the continuity of breastfeeding. One thing that must be considered in choosing complementary foods is the Recommended Dietary Allowances (RDA) which is categorized by age, weight, and food texture, which is adjusted to the toddler age category. In terms of fulfilling all aspects of choosing complementary foods, this study proposes the design of a 4-star daily menu recommendation system for toddlers which refers to the intake of daily calorie needs for toddlers, namely carbohydrates, animal protein, vegetable protein, and vitamins/minerals using the FMADM method (Fuzzy Multiple Attribute Decision Making). The FMADM method used is the Electre method. In this study, the authors succeeded in building the desired recommendation system using the Electre method which produces a daily menu based on the number of mealtimes, based on the age and weight of toddlers by observing the user's tendency to the texture and composition of food and its nutritional content in the recommendation system that is built, so that can be accessed via mobile devices owned by the user.