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Journal of Computer System and Informatics (JoSYC)
Published by Forum Kerjasama Pendidikan TInggi
ISSN : 27147150     EISSN : 27148912     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Industrial & Manufacturing Engineering
Journal of Computer System and Informatics (JoSYC) covers the whole spectrum of Artificial Inteligent, Computer System, Informatics Technique which includes, but is not limited to: Soft Computing, Distributed Intelligent Systems, Database Management and Information Retrieval, Evolutionary computation and DNA/cellular/molecular computing, Fault detection, Green and Renewable Energy Systems, Human Interface, Human-Computer Interaction, Human Information Processing Hybrid and Distributed Algorithms, High Performance Computing, Information storage, Security, integrity, privacy and trust, Image and Speech Signal Processing, Knowledge Based Systems, Knowledge Networks, Multimedia and Applications, Networked Control Systems, Natural Language Processing Pattern Classification, Speech recognition and synthesis, Robotic Intelligence, Robustness Analysis, Social Intelligence, Ubiquitous, Grid and high performance computing, Virtual Reality in Engineering Applications Web and mobile Intelligence, Big Data
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 443 Documents
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Perancangan Aplikasi Deteksi Orisinalitas File Dokumen Menerapkan Algoritma Ripe-MD 128 Samsir Samsir
Journal of Computer System and Informatics (JoSYC) Vol 3 No 2 (2022): Februari 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v3i2.954

Abstract

Detection of the originality of this document file is carried out on text documents to find out changes in the contents of the text in the document and avoid plagiarism or plagiarism of the text. Plagiarism or plagiarism means imitating or imitating or stealing other people's writings and works which are later recognized as one's own writing with or without the permission of the author. Plagiarism of this document file is often applied by academics both at the school and university levels. To overcome the problem, a solution is needed to detect the authenticity of the document file. The process of detecting the originality of this document file uses the Ripe-MD 120 method, where the output is a set of hash values ​​obtained through that method. RIPE-MD was developed for the European Community RIPE project. This improvement and development was carried out because many cryptanalytic efforts had been carried out on RIPE MD-128 and based on the information obtained, RIPE MD-160 was created. RIPE MD-128, the resulting hash value only has a length of 128 bits which is able to detect the authenticity of an image document file.
Penerapan Metode MOORA dalam Penentuan Karyawan Terbaik Fitry AF Togatorop; Mesran Mesran
Journal of Computer System and Informatics (JoSYC) Vol 3 No 2 (2022): Februari 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v3i2.1282

Abstract

MOORA in the decision support system for determining the best employees performs a ranking with several stages. These stages are always carried out in the same way even though it is known that there are different input values. However, for the same input value, it will be difficult to get results in determining the ranking. The selected results will of course be carried out in an alternative order. From the research results, it is expected to determine the best employees by applying the MOORA method
Penerapan Algoritma Transformasi Walsh-Hadamard dalam Pemampatan File BMP Ainun Mardiah; Berto Nadeak
Journal of Computer System and Informatics (JoSYC) Vol 3 No 2 (2022): Februari 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v3i2.1283

Abstract

The size of the image file in the bmp format is relatively large, where the better the quality of the resulting image, the larger the pixel size required to record the image, the compression process is one of the alternatives that is needed to reduce the capacity of an image file, so that it is not too wasteful in using space storage. With the size of a data that has been reduced or bit reduced to an image file, when moving or sending an image file that has been bit done, the process of moving the file will be easier and faster. because the storage space media has enough space to store an image file that has scattered bits or the compression process of a file that has been moved. The compression technique in the application uses the Walsh Hadamard Transformation algorithm to produce a compressed image and change the initial size, image character content, and parameters for compression of Cr (Compression Ratio) in reducing file size.
Implementasi Algoritma Zhu-Takaoka Untuk Pencarian Nama Obat Pada Aplikasi Katalog Obat Berbasis Android Sony Sony
Journal of Computer System and Informatics (JoSYC) Vol 3 No 3 (2022): May 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v3i3.1284

Abstract

Medicine is an object that is currently needed by humans, there are many names of drugs with different benefits, making it difficult for many people to find information on the name of the drug and the benefits of the drug. Technology is needed to make it easier for someone to find information on drug names and the benefits of the drug, therefore the author will build an android-based drug catalog application. With this android-based drug catalog application users can easily search for drug names by entering the name of the drug to be searched in the search table, after which the name of the drug with the benefits of the drug will appear.
Penerapan Association Rule Menggunakan Frequent Pattern Growth Untuk Rekomendasi Produk Jersey Sepakbola Anwar Musaddad; Odi Nurdiawan; Gifthera Dwilestari
Journal of Computer System and Informatics (JoSYC) Vol 3 No 3 (2022): May 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v3i3.1390

Abstract

The phenomenon of the beginning of the year, what some football fans have been waiting for, is the publication of the latest jersey from their favorite team. When the new jersey was launched, football fans flocked to buy the jersey, but there were several shops available for the new jersey. This was experienced by the Eighteen Sport shop, in fulfilling the wishes of fans, there were obstacles to re-stock the jerseys that were most in demand. So many items that have not been sold. The focus of this research lies in managing jersey sales data in June, July and August, as well as high interest in the demand for club jerseys. The high demand for jerseys is influenced by the achievements of the club itself. This study uses the FP Growth algorithm with the aim of getting a recommendation pattern from the wishes of football fans. Based on the results of the support management, it was found that consumers by buying 1 jersey item will buy back 1 different jersey item as many as 15 patterns. Consumers by buying 2 jersey items will repurchase 1 different jersey item as many as 46 patterns. Consumers by buying 3 jersey items will repurchase 1 different jersey item as many as 37 patterns. Consumers by buying 4 jersey items will repurchase 1 different jersey item for 10 patterns. So that the pol data becomes the owner's recommendation to make a repeat purchase.
Klasifikasi Pemberian Bantuan UMKM Cirebon dengan Menggunakan Algoritma K-Nearest Neighbor Hira Wahyuni Azizah; Odi Nurdiawan; Gifthera Dwilestari; Kaslani Kaslani; Edi Tohidi
Journal of Computer System and Informatics (JoSYC) Vol 3 No 3 (2022): May 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v3i3.1392

Abstract

The Indonesian government in obtaining Real Time data on MSMEs who are entitled to assistance, accuracy in distributing MSME assistance, and accelerating Indonesia's economic growth through MSMEs, especially the Cirebon Regency area. There are several ways so that cash transfer assistance for micro-scale SMEs from the government is right on target, in this study the authors will use data mining techniques with the k-nearest neighbors method in classifying receiving assistance from SMEs. The data used in this study uses secondary data with attributes of Regency, District, Business Name, Product Name, Business License, Assets and Turnover. The application of the KNN algorithm uses the retrieval operator, cross validation, and in developing the model using the KNN algorithm operator, apply model and performance. The results of the accuracy are 98.46 % with details, namely the Prediction Results are Eligible and it turns out to be true as many as 339 Data. The Prediction Result is Eligible and it turns out to be true Not Eligible as much as 2 Data. Prediction results are not eligible and it turns out to be true as much as 4 data. Prediction results are not eligible and it turns out to be true, 42 data are not eligible. Recommendations for the pattern of knowledge obtained using the K-NN algorithm. Researchers provide recommendations that are feasible to be given assistance for MSMEs as many as 339 MSME participant data spread across the Cirebon district and included in the affected category. Then there are several MSME participants who cannot receive MSME assistance according to the application of the KNN algorithm, which is 42 data, and there are 2 data from participants who are proposed to receive MSME assistance. The hope of the research for participants who receive assistance from the government can survive in conditions like this covid 19
Prediksi Jumlah Kunjungan Pasien Menggunakan Simulasi Monte Carlo Rian Rafiska
Journal of Computer System and Informatics (JoSYC) Vol 3 No 3 (2022): May 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v3i3.1690

Abstract

Klinik adalah jenis fasilitas pelayanan kesehatan yang menyediakan pelayanan rawat jalan, rawat inap, dan gawat darurat kepada masyarakat. Klinik Utama Khusus Mata (KUKM)-Kita merupakan fasilitas kesehatan milik swasta yang memberikan pelayanan kesehatan khususnya dengan keluhan mata bagi masyarakat Kota Sungai Penuh dan Kabupaten Kerinci. Karena jumlah pasien yang datang setiap harinya tidak bisa diketahui, hal ini mengakibatkan pihak manajemen KUKM-Kita tidak bisa menyiapkan sumber daya yang optimal dalam memberikan pelayanan kepada masyarakat. Untuk mengatasi masalah ini, maka perlu dilakukan simulasi untuk memprediksi jumlah pasien yang akan berkunjung di masa yang akan datang. Metode yang digunakan dalam penelitian ini ialah metode simulasi Monte Carlo. Penelitian ini bertujuan untuk memberikan informasi yang dibutuhkan pihak KUKM-Kita dalam memprediksi jumlah kunjungan pasien kedepannya. Dalam penelitian ini data yang diolah ialah data jumlah kunjungan pasien pada tahun 2019 sampai 2021 di KUKM-Kita. Hasil dari penelitian ini adalah prediksi jumlah kunjungan pasien yang setiap tahunnya mengalami peningkatan. Dengan hasil ini pihak KUKM-Kita bisa munggunakan informasi yang didapatkan untuk menjadi rujukan dalam membuat keputusan dan kebijakan untuk memperbaiki pelayanan kedepannya.
Penerapan ML dengan Teknik Bayesian Regulation untuk Peramalan Usia Penduduk di Beberapa Negara Asia Ratih Puspadini; Anjar Wanto; Nur Arminarahmah
Journal of Computer System and Informatics (JoSYC) Vol 3 No 3 (2022): May 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v3i3.1692

Abstract

Knowing the age of life of the population in a country is useful for evaluating the performance of the government, whether the government is able to prosper the population in general, and improve health status in particular. The purpose of this paper is to forecast the age of the population in several major countries in Asia, so that the government has a benchmark in determining policies to further improve the welfare and health of the population in their respective countries. The forecasting method in this paper will use Machine learning algorithms with Bayesian Regulation techniques. The research data used is data on population expectations in several Asian countries sourced from the United Nations: "World Population Prospect: The 2010 Revision Population Database". This research is a development of research that has been done before, using the Cyclical order technique. Previous research used 5 architectural models (3-5-1, 3-8-1, 3-10-1, 3-5-8-1 and 3-5-10-1), with the best model being 3-5-10 -1 which results in an accuracy of 97%, MSE 0.0008358919, training time of 27 seconds and an error rate of 0.03. Meanwhile, this research only uses 3 modified architectural models (2-5-1, 2-10-1 and 2-5-10-1), with the best model being 2-5-1. The result is that this study is better than previous studies. The benchmark is seen from a smaller error rate (0.02), better accuracy (100%), to a faster training time (5 seconds). So it can be concluded, Bayesian Regulation technique works better than Cyclical order and the 2-5-1 architectural model will be used to make predictions
Penerapan Algoritma Naïve Bayes Untuk Diagnosa Hama Pada Tanaman Aglaonema SP dan Monstera Adansonii M Riandi Widiantoro; Salahudin Robo; Almukarrama Almukarrama
Journal of Computer System and Informatics (JoSYC) Vol 3 No 3 (2022): May 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v3i3.1693

Abstract

Aglaonema sp and Monstera Adansonii are the most popular ornamental plants during the COVID-19 pandemic. Aglaonema sp and Monstera Adansonii become the target of the keepers because the colors and patterns on the leaves are unique. Despite the high popularity of Aglaonema sp and Monstera adansonii, not many keepers know the problems faced by their plants. The least number of triggers is knowledge of the keepers in caring for their plants. Therefore, to help the community in maintaining Aglaonema sp and Monstera Adansonii plants, an expert or expert in the field of ornamental plants is takes. Due to the difficulty of finding an expert, a system that is able to keep knowledge from an expert is required. An expert system is part of an intelligence that uses a person's knowledge that is summarized and processed carefully to solve problems. One of the statistical data calculation methods is Naïve Bayes. The Naïve Bayes method is a computational technique for predicting probabilities by calculating how many possible sets by adding up the frequency and combined values ​​of the dataset. The software created is able to share understanding with the community about Aglaonema sp and monstera adansonii plants and what treatment should be given to their ornamental plants
Klasifikasi Citra Jenis Kapasitor Menggunakan Kombinasi Algoritma K-Nearest Neighbor dan Principal Component Analysis Rini Nuraini
Journal of Computer System and Informatics (JoSYC) Vol 3 No 3 (2022): May 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v3i3.1694

Abstract

To learn about electronic devices, one must know about the types of electronic components. Capacitors are one of several important electronic components. Capacitors are part of passive components that are able to store energy or electric charge at a temporary time. Capacitors or commonly called capacitors have many types. However, some people do not know about these types of capacitors. Especially for someone or a student who will learn about electronic components. The purpose of this study is to develop a digital image processing system for the classification of transistor types by applying the K-Nearest Neighbor (KNN) and Principal Component Analysis (PCA) methods. PCA serves to reduce and retain most of the relevant information from the original features according to the optimal criteria. Based on the results of feature extraction and data reduction performed by PCA, it is easier for the KNN algorithm to classify. KNN performs a classification based on the data closest to the object being processed. Based on the test results, the developed model is able to produce an average accuracy value of 82.50%. This means that PCA and KNN algorithms can be used in the process of classifying capacitor type images properly

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