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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Jurnal Mantik Jusikom: Jurnal Sistem Informasi Ilmu Komputer
Bayu Angga Wijaya
Universitas Prima Indonesia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Languange, Linguistic, Communication & Media

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An Aplikasi Sistem Pakar Diagnosa Penyakit Mata Pada Manusia Menggunakan Metode Certainty Factor Berbasis Web Wijaya, Bayu Angga; Tanjung, Juliansyah Putra
Sinkron : jurnal dan penelitian teknik informatika Vol. 5 No. 1 (2020): Article Research, October 2020
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v5i1.10579

Abstract

Eye is the important senses. If the eye is disrupted then ignore it, it will disturb. In fact, many people delay to checked eye diseases that them suffered, due to the lack of knowledge society, the cost is quite expensive and the imbalance between patients and doctors so that should be queued if will check the eye health. It is necessary for the expert system that can diagnose eye diseases, so a people can checking their eye diseases suffered without have to go to the doctors. This expert system is based on web with the programming language PHP and MySQL database. In the process of withdrawal conclusion, system using the certainty factors method that use a value to assume degree of confidence from an expert to a data. Expert system provides results in the form of the possibility of illness suffered, the value of the percentage of beliefs from the illness and the treatment solution based on the value of confidence that given and system is able to know the type of eye disease experienced by the user based on the symptoms chosen by the user. So, it can help the people to know the eye disease their suffered and the action can be done faster.
Facial Recognition Implementation using K–NN and PCA Feature Extraction in Attendance System Tanjung, Juliansyah Putra; Wijaya, Bayu Angga
Sinkron : jurnal dan penelitian teknik informatika Vol. 5 No. 1 (2020): Article Research, October 2020
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v5i1.10612

Abstract

Attendance is the fact that someone is present at an event or goes regularly to an institution, or attendance at an event is the number of people present at that time. The Saifiatul Amaliyah school itself is one of the many schools in Indonesia where the attendance of students or attendance is still done manually. This can cause problems, namely allowing fraud when filling in attendance and errors in data recapitulation. Therefore, in this study a computerized face attendance was created, which was formed using the K-Nearest Neighbor (K-NN) method and combined with the extraction of the Principal Component Analysis (PCA) feature where the attendance process can be done with a person's face. The face attendance system using the K-NN and PCA methods has an accuracy of 82%.
Perancangan Aplikasi Enkripsi Data Menggunakan Algoritma XXTEA Bayu Angga Wijaya; M Harahap; Siti Aisyah
Jurnal Sistem Informasi dan Ilmu Komputer Prima(JUSIKOM PRIMA) Vol. 3 No. 2 (2020): Jurnal Sistem Informasi dan Ilmu Komputer Prima (JUSIKOM Prima)
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jusikom.v3i2.847

Abstract

Keamanan telah menjadi aspek yang sangat penting untuk mengamankan data. Salah satu upaya pengamanan data adalah dengan kriptografi. Kriptografi adalah ilmu yang mempelajari bagaimana supaya pesan atau dokumen tetap aman, tidak dapat dibaca oleh pihak yang tidak berhak (anauthorized persons). Pada penelitian ini algoritma kriptografi yang digunakan adalah algoritma XXTEA (Corrected Block Tiny Encryption Algorithm) untuk melakukan pengamanan data pada proses pengiriman data aplikasi E-Surat. Sistem ini dibuat dengan menggunakan Node.js dengan bahasa pemrograman Javascript dan Express sebagai kerangka kerjanya. Uji performa pada penelitian ini dibagi menjadi dua kasus, yaitu uji performa aplikasi dan uji performa algoritma. Uji performa aplikasi menunjukan jumlah request per second yang dapat dihasilkan pada penggunaan 10 node CPU tidak stabil dan memiliki ruang nilai yang rendah. Nilai tertinggi request per second yang dapat dihasilkan adalah sebesar 26 request yaitu saat nilai concurent-nya 4 dan 256. Sedangkan nilai terendah request per second-nya adalah 20 yaitu saat nilai concurent-nya 512 Dari hasil uji performa algoritma XXTEA, dapat disimpulkan bahwa waktu enkripsi dan dekripsi pada algoritma XXTEA relatif cepat. Rata-rata waktu yang digunakan XXTEA untuk mengenkripsi pesan adalah 2.23987272 ms. Sedangkan, rata-rata waktu yang dihasilkan algoritma XXTEA untuk mendekripsi pesan adalah 2.05297956 ms.
Penerapan Metode Simple Additive Weighting (SAW) Penentuan Lokasi Tower Operator Selular Muhammad Syahputra Novelan Novelan; Bayu Angga Wijaya Wijaya
JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Vol. 4 No. 1 (2021): Jutikomp Volume 4 Nomor 1 April 2021
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jutikomp.v4i1.1738

Abstract

Perkembangan kehidupan manusia yang semakin kompleks dan dinamis secara tidak langsung menuntut adanya kemajuan teknologi telekomunikasi yang dapat menghubungkan setiap manusia satu dengan lainnya dimanapun mereka berada di dalam menjalankan aktivitasnya sehari-hari. Masing – masing perusahaan operator membangun menaranya secara terpisah sesuai kebutuhan dan perencanaan tiap operator. Hal tersebut menjadikan pertumbuhan tower BTS tidak terkendali. Pada umumnya, lokasi tower berada pada sebuah lahan kosong yang dikhususkan untuk pendirian tower, namun yang terjadi hingga kini lokasi tower dapat berada pada tempat manapun.Lokasi tower telah berada pada pemukiman padat penduduk. Hal itu merupakan sebuah peringatan sekaligus permasalahan bagi pemerintah. Karena apabila tidak segera ditanggulangi, maka pendirian tower akan menggaggu estetika kota. maka dari itu diperlukannya Metode Simple Additive Weighting (SAW) dalam menentukan lokasi tower BTS agar sinyal operator dapat menjangkau semua wilayah namun aman bagi warga dan ramah terhadap lingkungan sekitar. Sistem yang dirancang membantu user dalam mengambil keputusan untuk menentukan lokasi alternatif Tower yang tepat sesuai dengan jumlah alternatif yang dibutuhkan
Film Recommendation System with Social-Union Algorithm: Film Recommendation System with Social-Union Algorithm Bayu Angga Wijaya; Amar Nugraha; Juandry Juandry; Jimy Okinawa; Jovan Kinoto
Jurnal Mantik Vol. 4 No. 2 (2020): Augustus: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.Vol4.2020.932.pp1278-1284

Abstract

A Recommendation System applies several classic Collaborative Filtering (CF) methods. Some CF methods are combined with social networks, for instance Fusing ESR, Social Regularization, and Trust-Aware. Nonetheless, these three methods are not able to be developed if they are integrated with other types of implicit or explicit relationships. Their selection of parameter weights is not optimal enough when it combines preferences between users from the two types of relationships into one. Usually, a group of friends will be similar in terms of interest and preference for an item. The similarities between users will increase the accuracy of the prediction results. The selection of parameter weights can be done manually or automatically through the calculation of global and local density coefficients so the determination of parameter weights will be optimal. Therefore, the Social-Union (SU) method proposed in this research use that method to overcome the problems from previous research. The result of this research is a website that applies the Social-Union method and let the user get recommendations that depend on the value of the parameter a.
Implementation of Genetic Algorithm in Making a Covid-19 Vaccination Schedule K. Dilpani Laksmi; Bayu Angga Wijaya; Desniari Gea
Jurnal Mantik Vol. 5 No. 3 (2021): November: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

At the end of 2019, the World was attacked by a very deadly virus. Starting from the city of Wuhan in China, this virus began to grow and attack the world and became a pandemic. Until now the world is still being attacked by this pandemic. Various experts in this world took turns looking for a solution to this problem. Various studies and studies were carried out to find a way out and treatment. In the middle of 2020, research began to be intensively carried out to make a covid 19 vaccine. In doing things that are quite complicated, of course we need the help of technology to do it. In this case, we can use an algorithm in scheduling the covid 19 vaccination. In this regard, this study would like to discuss the application of genetic algorithms in making the covid 19 vaccination schedule. The genetic Algorithm was chosen because it can use many variables in its application compared to the FIFO method. The FIFO method is indeed simpler, the first to register will be scheduled, but to support more variables it is more efficient to use Genetic Algorithms. The use of genetic algorithms in this study was to find solutions and apply them to the program to schedule the covid 19 vaccination. genetics in scheduling accurate and effective COVID-19 vaccinations.
Steganography Text Message Using LSB and DCT Methods Bayu Angga Wijaya; Adrian Julio Manalu; Bayu Andreas Tarigan; Lovely Septian Silitonga
Jurnal Mantik Vol. 5 No. 3 (2021): November: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Advances in human thinking patterns make people realize that information technology is an important part of civilization. In line with the development of information technology, many parties are not responsible for committing crimes such as theft and falsification of information from data. These problems can be overcome using a variety of methods and techniques, one of which is steganography. Steganography is a technique of hiding confidential data in a digital (media) container so that the existence of the secret data is difficult to know by irresponsible people or parties. The purpose of this study is to provide a solution to the problem of hiding messages into images using two different steganographic methods, namely LSB and DCT, then both methods will be tested for their efficiency. In this study, it was concluded that the PSNR value for LSB steganography was 8.887, and the MSE value was 104.85. On the other hand, DCT Steganography got a PSNR of 83,728, and an MSE value of 0.0592. From the PSNR and MSE test results, it can be concluded that the better image quality comes from DCT Steganography, this is because, in processing DCT images, the author must convert the images first, then can encode, but this conversion is not done on the LSB method.
Penerapan Algoritma Huffman dan Unary Codes untuk Kompresi File Teks Bayu Angga Wijaya; Sarwando Siboro; Mahendra Brutu; Yelita Kristiani Lase
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 3 (2022): Article Research Volume 7 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11567

Abstract

Technique in carrying out data compression is an important point in technological developments. With compression in data in the form of text can include many uses, including for data transfer, copying and for backing up data. From its uses, this aspect is important for data security. There are many compression techniques on the data, including using huffman algorithms and unary code. One of its applications will be implemented on a text data that is widely used by digital actors in storing important data. The data must not be known by unauthorized parties in accessing the data. Therefore, huffman algorithms and unary code can solve this problem. By compressing the selected data also encrypts it as an extra security. The Huffman algorithm is a lossless compression algorithm or a technique that does not change the original data, by converting the unit of data content into bits. So this algorithm is widely used in the compression process. The Unary Codes algorithm is also a lossless compression technique that is generally used by combining several modification techniques. In this unary codes algorithm, each symbol in the string will be searched for its frequency. Then sorted from the last order (descending). The use of these two text data compression techniques results in a file size that is smaller than the original but can be returned to the original data
Application of Data Mining using Naive Bayes for Student Success Rates in Learning Bayu Angga Wijaya; Vijay Kumar; Berlian Fransisco Jhon Wau; Juliansyah Putra Tanjung; N P Dharshinni
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4639

Abstract

Education is a very important part of human life because through education quality human resources will be formed. Quality education can be read and measured by the achievement of various indicators. However, achieving these indicators is not easy, because learning success is influenced by several factors. One of the factors that can affect the success of learning is the learning system. To understand the level of student success in learning, a data mining processing technique is needed. The algorithm that will be used in this research is the naive Bayes algorithm. This study uses 601 datasets per year from Academic Year 2019/2020 to Academic Year 2021/2022, the data used are attendance score data, assignment scores, mid-exam scores, semester exam scores, and averages. The test is divided into 3, namely testing for the Academic Year 2019/2020 dataset, testing for the Academic Year 2020/2021 dataset, and testing for Academic Year 2021/2022 using the split validation operator. The test results using the Academic Year 2019/2020 – Academic Year 2020/2021 student score dataset have an accuracy value of 95.01% while the Academic Year 2021/2022 student score dataset has an accuracy value of 97.79%.
The Optimization of CNN Algorithm Using Transfer Learning for Marine Fauna Classification Insidini Fawwaz; Yennimar Yennimar; N P Dharsinni; Bayu Angga Wijaya
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 4 (2023): Article Research Volume 8 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.12893

Abstract

Marine fauna are all types of organisms that live in the marine environment. Marine fauna is also an important part of the marine ecosystem that has an important role in maintaining environmental balance. However, the survival of marine fauna is threatened due to activities carried out by humans, such as pollution, overfishing, industrial waste disposal into marine waters, plastic pollution and so on. Therefore, efforts are needed to monitor and protect marine fauna so that marine ecosystems can remain stable. One way to monitor marine fauna is by using classification technology. One of the technologies that can be used in marine fauna classification technology is Convolutional Neural Network (CNN). CNN is one of the classification methods that can be used to classify objects in images with a high level of accuracy. The CNN architecture models used are MobileNet, Xception, and VGG19. Furthermore, the method used to improve the performance of the CNN algorithm is the Transfer Learning method. The test results show that the MobileNet architecture model produces the highest accuracy value of 91.94% compared to Xception and VGG19 which only get an accuracy value of 87.64% and 88.42%. This shows that the MobileNet model has a more optimal performance in classifying marine fauna.
Co-Authors Adrian Julio Manalu Amar Nugraha Bayu Andreas Tarigan Berlian Fransisco Jhon Wau Desniari Gea Insidini Fawwaz Jimy Okinawa Jovan Kinoto Juandry Juandry Juliansyah Putra Tanjung Juliansyah Putra Tanjung K. Dilpani Laksmi Lovely Septian Silitonga M Harahap Mahendra Brutu Muhammad Syahputra Novelan N P Dharshinni N P Dharsinni Sarwando Siboro Siti Aisyah Vijay Kumar Yelita Kristiani Lase Yennimar Yennimar