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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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Pemilihan Penilaian Karyawan Menggunakan Metode Hybrid ROC-MOORA Sitti Nur Alam; Fauzi Fauzi; Firman Santoso; Saludin Saludin; Monanda Rio Meta
Journal of Computer System and Informatics (JoSYC) Vol 4 No 2 (2023): Februari 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i2.3133

Abstract

Apprentices are employees who work within the context of a real learning process in the workplace to hone skills and self-quality in achieving maturity in learning science in the world of education, apprentices are also commonly referred to as temporary employees who have a short period of time permitting work in a company , it is not uncommon for a company to appoint an apprentice immediately to become a permanent worker because it is considered capable of minimizing the time in the process of selecting new employees needed to fill employee positions required by a company, several companies also collaborate a lot with a university to accept participants educate them to be able to work in the company they want. In determining an apprentice to become a permanent employee of the company, of course, careful assessment and consideration is needed as is done in other employee selection processes, to eliminate subjective and unfair selection and to improve the quality of the company's assessment of target apprentices who will be appointed as permanent employees. need to build a decision-making system. This is widely applied by other leading companies. In this research, the application of a decision support system was carried out in determining the apprentice's assessment to be selected as a permanent employee of a company using the combination method by applying the weight of the data assessment using the ROC method and the MOORA method ranking method, the results obtained were 0.365 the highest point from the acquisition of the value obtained out of 10 apprentices, the highest score is data recommended by the system as interns who have the best potential to become permanent employees of the company.
Penerapan Metode Certainty Factor Dalam Mendiagnosa Penyakit PES Rima Tamara Aldisa
Journal of Computer System and Informatics (JoSYC) Vol 4 No 2 (2023): Februari 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i2.3139

Abstract

Plague is the oldest plague known to mankind and will continue to plague the world. Black Death is an infectious disease caused by the bite of Yersinia pestis, which breeds on rats. Human-to-human transmission occurs through droplets containing bubonic plague. Expert systems are a branch of artificial intelligence and a branch of knowledge that emerged with the development of computer science today. In this study, the expert system was implemented as a system for information or output to pursue certainty in diagnosing the type of bubonic plague felt by the patient based on the symptoms felt by the patient. Its use on the user's system must be combined with methods so that it runs correctly and optimally. In this study, the authors used the certainty factor (CF) method. CF is the internalization of uncertainty in professional thinking proposed by Shortliffe and Buchanan in 1975. Based on the results of the computational process using the CF method, information is generated that the patient suffers from multiple symptoms of bubonic plague, and the patient is diagnosed with pneumonic plague (P3) with an expression confidence level of 0.993 or 9.93%.
Protoype Sistem Penyiram Lahan Perkebunan Kangkung Otomatis Berbasis Internet of Things dengan Logika Fuzzy Sugeno Ismail Mahfuddin; Rakmat Kurniawan R; Aidil Halim Lubis
Journal of Computer System and Informatics (JoSYC) Vol 4 No 2 (2023): Februari 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i2.2668

Abstract

Watering is one of the jobs that are routinely carried out in plant maintenance which usually causes various problems. One of them is the absence of the same measure of water quantity when watering will result in the plants being treated can experience excess or lack of water, causing the plants to dry out or rot and die. So we need a tool that can help in terms of watering plants. The internet of things-based automatic watering machine for water spinach plantations is expected to be a system to assist farmers in watering especially kale that can detect moisture in the soil and temperature around the land and has scheduling options, automatic fuzzy and manual that can be controlled via the android application. which has been designed and can work based on the selected option. This tool is made using the Sugeno fuzzy logic method because this method is suitable for use in making decisions to find the values ​​of humidity and temperature that fluctuate and are less certain. Based on the results of the study, the average percentage difference in the humidity sensor is 0.016 % and the accuracy (accuracy) on the humidity sensor circuit is 99.98%, while the percentage difference in the temperature sensor is 0.02% and the accuracy (accuracy) on the LM35 temperature sensor circuit is 99.99%.
Sistem Pakar Diagnosa Penyakit Influenza (Flu) Menggunakan Metode Forward Chaining Indah Suci Purnamasari; Uce Indahyanti; Ika Ratna Indra Astutik
Journal of Computer System and Informatics (JoSYC) Vol 4 No 2 (2023): Februari 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i2.3078

Abstract

Expert system is a technology that is widely used in the health sector, one of which is for disease diagnosis. Influenza (Flu) is one of the respiratory diseases caused by a virus called the influenza virus. Diseases caused by climate change are usually Influenza (Flu) and cold diseases, which are often considered the same by society. The purpose of this study was to design an expert system application for the diagnosis of these two different diseases, namely flu and colds. The research data is sourced from data from the Ministry of Health of the Republic of Indonesia (KEMENKES). The design of this expert system application uses the forward chaining method with google appsheet and google sheet tools. The results showed that all the features of the application have worked properly after being tested using the black box testing method. This application also helps people be able to distinguish flu and cold diseases, it is shown through the results of an online survey that 91% of respondents need this expert system application.
Penerapan Metode Fuzzy Tsukamoto Dalam Memprediksi Permintaan Barang Dwi Melina; Diana Diana
Journal of Computer System and Informatics (JoSYC) Vol 4 No 3 (2023): May 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i3.3194

Abstract

Azthana Digital Media is a digital agency that works with a number of Indonesian vendors, including Pempek Mola, Pempek Kalani, and Eightsy Bag. Azthana oversees distribution and maintains warehousing for all three brands simultaneously. However, due to fluctuations in product demand, there are sometimes gaps in the supply of goods across all brands. So we need a method that can be implemented in inventory management and product development in the future. Forecasting strategies are useful tools for maintaining and expanding stock levels. In this study, researchers used the Fuzzy Tsukamoto technique built into a web-based inventory system to estimate consumer demand. Sales data, product purchases and goods production data are the three main inputs used to formulate demand forecasts. The results of this study can be concluded that the inventory system created can help the related team to find out the exact amount of stock available and to implement the Tsukamoto fuzzy calculations in predicting the demand for goods in the system that is running well as evidenced by the results of manual calculations and the system if the demand value is input equal to 355 with four fuzzy rules that are set together to produce a production value of requests for goods that must be ordered to suppliers of 522 packs.
Komparasi CNN dengan ResNet Untuk Klasifikasi Paling Akurat Tingkat Keganasan Diabetes Berdasarkan Citra Retinopathy Lalu Mutawalli; Mohammad Taufan Asri Zaen; Yuliadi Yuliadi
Journal of Computer System and Informatics (JoSYC) Vol 4 No 3 (2023): May 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i3.3248

Abstract

Diabetes becomes an infectious disease that has a very significant increase, it's increasing not only in old age or even suffered by a young age. Based on the Data and Information Center of the Ministry of Health of the Republic of Indonesia, the prevalence of diabetes is 9% in female genitals and 9.65% in male genitals and is estimated to increase to 19.9% with the addition of population age. Currently, the Machine Learning (Depp learning) approach is widely used in carrying out the calcification of medical image data. Retinopathy Diabetes image data can be used as material to build a classification model by utilizing the Convolutional Neural Network (CNN) algorithm and Residual Network (ResNet). The test results in the model developed in this study were the comparison showing the accuracy level of CNN 68.49% while the ResNet was 81.23%, in the CNN loss test 32.57% while the ResNet was 12.59%. In the Scenario of the application of Learning Rate 0.0005 also the ResNet is better than CNN, in the CNN Learning Rate Application Scenario producing an accuracy value of 68.49% while the ResNet adopts an accuracy value of 81.84% and on the CNN loss value of 20.14 while the 10.2% Resnet has a higher level of accuracy has a higher accuracy rate Compared to CNN and the application of learning rates it also affects in building a more accurate model in the case study of Retinopathy Diabetes.
Penerapan Algoritma K-Means Clustering untuk Mengetahui Pola Penerima Beasiswa Bank Indonesia (BI) Qurrata A'yuni; Alwis Nazir; Lestari Handayani; Iis Afrianty
Journal of Computer System and Informatics (JoSYC) Vol 4 No 3 (2023): May 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i3.3343

Abstract

Bank Indonesia Scholarships are a type of scholarship sourced from Bank Indonesia for students from selected State Universities, Private Universities, and Polytechnics. From the data on scholarship recipients who have passed the selection from 2020, 2021, 2022 universities in Riau, it is necessary to look for the behavior patterns of scholarship recipien because Bank Indonesia does not yet have a pattern. To find the pattem from scholarship recipients using the method of data mining with K-Means Clustering algorithm. The parameters used are 4, namely study program, semester, GPA, and level. The results of the study using RapidMiner showed that cluster 0 was dominated by students from the Commerce Shipping Management study program, who were in semester 5 and D3 level. Cluster 1 is dominated by students from the Accounting and Management study program, in semester 7, with GPA greater than or equal to 3.51, and S1 level. Cluster 2 is dominated by students from the Nursing study program, in semester 5, with GPA greater than or equal to 3.51, and D3 level. Cluster 3 is dominated by students from the International Relations study program, in semester 7, with GPA greater than or equal to 3.51, and S1 level. Cluster 4 is dominated by students from the Informatics Engineering study program, in semester 5, with GPA greater than or equal to 3.51, and S1 level. It show that the recipients of Bank Indonesia scholarships are dominated by students with high GPA scores or equal to 3.51. In addition, it is also dominated by students who are at the S1 level. Tests were carried out using DBI with k=5 resulting in a validity value of 0.121.
Analisa Sentimen Informasi Hoaks Pasca Pandemi Covid-19 dengan Text Mining Akhmad Rezki Purnajaya; Yonky Pernando
Journal of Computer System and Informatics (JoSYC) Vol 4 No 3 (2023): May 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i3.3358

Abstract

In this era of globalization, the delivery of information can be conveyed by any information media, this can also cause the spread of hoax information. This is very detrimental for recipients of information, especially information that is very important to receive and information related to the Covid or Corona virus that has hit the world and Indonesia. Based on data from the Gugus Tugas Percepatan Penanganan Covid-19, in the post-pandemic era 227 hoax information were still found that were identified. Therefore, in this study the authors conducted hoax information research, especially regarding the Covid-19 virus in the post-pandemic era by using the Text Mining method to find out information patterns that often appear in the post-Covid-19 pandemic. This paper will also show some results regarding the association of several words with the main word in hoax information in the post-Covid-19 pandemic era in the form of Term of Frequency, Word Cloud, Fruchterman Reingold Layout, and Circle Layout. The results of this study indicate that in the post-Covid-19 pandemic era, hoax information is frequently associated with ‘vaccines’ and ‘covid’, with 113 and 111 occurrences respectively. This is due to public skepticism regarding the safety and effectiveness of the Covid-19 vaccine, leading to the dissemination of hoaxes aimed at discouraging vaccination. Other commonly mentioned words in post-pandemic hoax information include ‘omicron’, ‘vaccinated’, ‘variant’, ‘pfizer’, ‘mRNA’, ‘virus’, and ‘vaccination’, albeit with lower frequencies
Sistem Pendukung Keputusan Penerima Beasiswa Murid Berprestasi dengan Metode SAW Nuorma Wahyuni; Erlin Setyaningsih; Adi Hermawansyah; Dila Seltika Canta; Dilla Putri Kinanti; Surmiati Surmiati; Sudarman Sudarman
Journal of Computer System and Informatics (JoSYC) Vol 4 No 3 (2023): May 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i3.3362

Abstract

This research is a Decision Making System research which purposes to find out the scholarship recipient candidate of the feat student through of the SAW (Simple Additive Weighting) method of the MTsN 1 Penajam Paser Utara. The purpose of this research is to provide of the convenience in the alternative solution in the determining scholarship of the feat student, and to apply of the SAW method in assessing of the scholarship recipient candidate . The Data collection techniques in this research were observation, interview, and literature study. The method is used The SAW. Then it requires the decision maker to determine the level for each the attribute, then the total of score for the alternative is obtained by adding up all the multiplication results between the rating (which can be compared across attributes) and the level of each attribute. The rating for each attribute must be dimension-free in the sense that it has gone through the previous of the normalization process. The basic concept is to find the total leveling of the performance rating for each alternative across all the criterias. The SAW method requires normalization of the decision matrix (X) to scale that can be compared with the existing rating. The sample population taken is from 60 students of MTsN 1 Penajam Paser Utara. From the result of determining the priority of proposed the feat scholarship recipient candidate is using the Simple Additive Weighting method, the student who deserves the best achievement scholarship is M. Indra Saputra who has the highest ranking with a score of 0.916 as the best alternative. The system built can help of the selector team to work in selecting outstanding scholarships and can speed up the selection process and reduce error in determining scholarship recipient.
Implementasi Algoritma A* (A-Star) dan Greedy Dalam Penentuan Routing Pada Wide Area Network (WAN) Alfry Aristo Jansen Sinlae; Rini Nuraini; Dedy Alamsyah; Sampurna Dadi Riskiono
Journal of Computer System and Informatics (JoSYC) Vol 4 No 3 (2023): May 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i3.3374

Abstract

The continuous development of the internet has led to changes in routing complexity. In the context of a wide area network (WAN), network flow optimization becomes a major issue in the selection of the fastest route, which involves routing protocols. Algorithms in routing protocols are designed to determine the shortest path. Therefore, studies are needed regarding how to build a routing algorithm that can be used to get the shortest path in each process. This study aims to reduce network workload and compare the computation involved in determining the shortest path using the Greedy algorithm and the A* algorithm. The simulation results show that the A* algorithm is superior to greedy. The measurement results show that the final cost of the Greedy algorithm is 44 and the A* algorithm is 38. Taking into account the heuristic value for each node, the A* algorithm is superior to the Greedy algorithm in determining the shortest path.

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