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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 31 Documents
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Search results for , issue "Vol 4 No 3 (2023): May 2023" : 31 Documents clear
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.
Impelementasi Metode MOORA Pada Sistem Pendukung Keputusan Pemilihan Pegawai Teladan Amat Damuri; Tuti Lisnawati; Wieke Tsanya Fariati; Rhaishudin Jafar Rumandan
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.v4i3.3389

Abstract

Employees are a human resource asset for a company in carrying out the operational activities of an organization or company in achieving the main goals of the organization or company. The purpose of this study is to select exemplary employees in the company using the MOORA method, so that the company will quickly evaluate exemplary employees once every 6 months. The results of the ranking of exemplary employees who get rank 1 are exemplary employees, namely Zaenal Yuswantoro with a total score of 0.179431073, for rank 2 exemplary employees, namely Yolanda Prasasti with a total score of 0.175703146, and 3rd rank exemplary employees, namely Ahmad Budianto with a total value of 0.174341166. The results of manual calculations and by using a web application based on the Laravel framework show no difference in the results of the grades and ratings of the employees being assessed
Penerapan Algoritma Apriori Pada E-commerce Elektronik Nur Iza; Alwis Nazir; Iwan Iskandar; Elvia Budianita; Pizaini Pizaini
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.v4i3.3403

Abstract

Because there are so many advantages to using e-commerce, it is now expanding quickly. E-commerce, particularly for electronic items, makes it simpler for customers to execute transactions without traveling. Because businesses (business actors) do not yet have a pattern and strategy for the products they sell, the use of e-commerce has not yet reached its full potential. As a result, sales occasionally suffer because the supply of products does not meet consumer needs, forcing consumers to leave without purchasing these products, which has an impact on transactions. sales firm. Businesses (businesspeople) must use data mining to implement data processing. For this reason, researchers use an application strategy that is appropriate in this situation: the a priori algorithm. Finding frequent itemsets that frequently show up in the data set with the strongest pattern is frequently done using the a priori algorithm. This algorithm's output can be used to assist management in making decisions. According to the study's findings, the rule "if you buy AA Batteries (4-pack), you will buy AAA Batteries (4-pack), "if you buy AA Batteries (4-pack), you will buy a USB-C Charging Cable," and "if you buy AA Batteries (4-pack) and AAA Batteries (4-pack), you will buy a USB-C Charging Cable" all have a support and confidence value of 100%.
Sistem Pakar Dalam Mendiagnosa Penyakit Tubercolosis dengan mengimplementasikan Metode Case Based Reasoning Aris Wijayanti; Fatimah Nur Arifah; Desfita Eka Putri; Muhammad Dwi Satriyanto; Sulfikar Sallu
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.v4i3.3409

Abstract

Health is one of the most valuable parts of human life. So healthy is the goal of every human being. Many things cause the decline in human health, such as hereditary genes, sensitive immunity and exposure to viruses or bacteria. One of the diseases caused by bacteria is tuberculosis (TB). Tuberculosis is a disease caused by exposure to a bacterium called Mycobacterium tuberculosis. There are two types of tuberculosis, namely pulmonary tuberculosis and extra pulmonary tuberculosis. Pulmonary tuberculosis can be defined as a disease that attacks the lungs and affects the lung parenchyma [4]. It's just that this type of disease does not attack other organs. While extrapulmonary tuberculosis is a tuberculosis disease in which this type of disease can attack other related organs such as the hilum, pleura and various other organs. the lack of funds for health checks makes it too late for many people to get treatment. Therefore, the development of technology should be utilized in handling this problem. One of the technologies that can be used in dealing with these problems is to use an expert system. An expert system is a system that is developed using the development of the knowledge that is owned by many experts and is used as a reference in developing the technology. In using an expert system, a method is needed that can help solve existing problems, therefore in this study the method used is the Case-Based Reasoning (CBR) method. The Case-Based Reasoning (CBR) method is the most suitable method for use in this study because the main function of this method is to diagnose disease. Based on the results of the calculation process using the Case-Based Reasoning method for each type of TB disease, the results obtained are for pulmonary tuberculosis to obtain a value of 85%, while for tuberculosis with extra pulmonary tuberculosis it is 62%. So based on the results obtained in this study it was determined that the sample was diagnosed with pulmonary tuberculosis. With a similarity of 85%.
Penerapan Algoritma Naïve Bayes Classifier Dalam Klasifikasi Status Gizi Balita dengan Pengujian K-Fold Cross Validation Nurainun Nurainun; Elin Haerani; Fadhilah Syafria; Lola Oktavia
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.v4i3.3414

Abstract

Nutritional status is a condition related to nutrition that can be measured and is the result of a balance between nutritional needs in the body and nutritional intake from food. In Indonesia, there are still many nutritional problems such as malnutrition and other nutritional problems. This research will use the Naïve Bayes Classifier algorithm with K-Fold Cross Validation testing. The data used is data on the nutritional status of toddlers in August 2022 at the Rambah Samo I Health Center. Attributes in this study include Gender, Birth Weight, Birth Height, Age at Measurement, Weight, Height, ZS BB/U, BB/U, ZS TB/U, and TB/U. Determination of the nutritional status of toddlers in this study was based on the BB/TB index which consisted of 6 classes, namely severely wasted, wasted, normal, possible risk of overweight, overweight, and obese. From the research conducted, it was found that the Naïve Bayes Classifier algorithm with K-Fold Cross Validation can correctly classify the nutritional status of toddlers. From data processing using 10-Fold Cross Validation on the Naïve Bayes Classifier algorithm, it is known that the highest accuracy value is 82.94% in the 5th iteration, while the lowest accuracy value is 65.88% in 6th iteration. With an average overall accuracy value of 75.47%. Meanwhile, the average precision value obtained is 81.36% and the average recall value is 75.47%.

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