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Journal : JAST

Web Based Security System Academic Exam Questions Using Advanced Encryption Standard Bagus Satrio Waluyo Poetro; Sam Farisa Chaerul Haviana; Arief Budiman
Journal of Applied Science and Technology Vol 1, No 02 (2021): Juli 2021
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30659/jast.1.02.13-22

Abstract

One way to measure the success of the academic process and achievement of student competence, is giving exams, from the smallest level namely daily tests, semester exams, to the highest level, namely the national exam. In an effort to maintain the security of exam question data, there is a data security method known as cryptography. In this research, a security system was designed that serves to protect exam questions so that data cannot be read by student before its time by using the Advanced Encryption Standard (AES) algorithm.  The AES algorithm is a type of symmetric algorithm where the encryption and decryption processes have the same key for the encryption and decryption processes. In the system that will be designed, the Caesar Cipher algorithm is used to form an additional key (seed) that is kept secret from the public. The results of this study indicate that AES encryption method can give results maximum so that the AES method can applied to virtual data storage system to protect the transmitted data.
SYSTEM DESIGN OF AUTHICAL DISTURBANCE DIAGNOSIS IN CHILDREN USING THE K-NEAREST NEIGHBOR METHOD Achya Puji Sari; Dedy Kurniadi; Sam Farisa Chaerul Haviana
Journal of Applied Science and Technology Vol 1, No 01 (2021): Januari 2021
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30659/jast.1.01.22-25

Abstract

Autisme dapat dialami oleh anak dari berbagai ras, suku, strata sosial, dan ekonomi. Autisme merupakan gangguan perkembangan pervasif pada anak yang ditandai dengan adanya gangguan dan keterlambatan dalam bidang komunikasi, kognitif, perilaku, bahasa, dan interaksi sosial. Orang tua terkadang menganggap gangguan-gangguan tersebut sebagai keterlambatan perkembangan biasa namun pada kenyataanya jumlah penyandang spektrum autisme semakin meningkat. Menurut data dari badan kesehatan dunia (WHO) pada tahun 2009, prevalensi autis di Indonesia mengalami peningkatan luar biasa, dari 1 per 1000 penduduk menjadi 8 per 1000 penduduk. Pada tahun 2009 dilaporkan bahwa jumlah anak penderita autisme mencapai 150-200 ribu. Salah satu cara agar orang tua dapat mengetahui anaknya adalah penderita autism dengan menggunakan fasilitas pendeteksi. penelitian ini dalam mendiagnosis autism pada anak menggunakan metode K-Nearest Neighbor dengan menetukan parameter setting untuk nilai k. Di lakukan pengujian dengan black box testing dan confusion matrix, di dapat nilai akurasi tertinggi sebesar 95%, presisi 95.45%, recall 95.45%, f-measure 95.44%, pada nilai k=4.
Rancang Bangun Aplikasi Klasifikasi Topik Artikel Ilmiah Bahasa Indonesia Menggunakan Metode Support Vector Machine Sam Farisa Chaerul Haviana; Badieah Badieah; Ghozi Fidaul Haq
Journal of Applied Science and Technology Vol 3, No 01 (2023): Januari 2023
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30659/jast.3.01.%p

Abstract

Scientific articles were wrote as result of the research process that follow agreed rules, methods, and systematics so that the fact can be accounted for. Those scientific articles or publications were commonly available in the internet as indexed list. One of the biggest source of publication indexed in SINTA (Science and Technology Index) of Ministry of Education, Culture, Research and Technology of Indonesia. According to SINTA, the number of Indonesian publications continues to increase over years since 2017. Because of this increasing number of publications, the need of managing those documents is emerging. The management of published document data would be very difficult to do manually, including grouping or classifying documents based on the research topic. This become the background of this research on how to classify the articles topic automatically. This research utilizing support vector machine classifier to achieve the solution. After conducting research using 600 documents, we successfully classify the topic of Indonesian scientific article documents using the support vector machine method with a 94% accuracy, 95% precision, and 94% recall.