Journal of Computer System and Informatics (JoSYC)
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
Articles
443 Documents
<![CDATA[Analisa Perbandingan Metode Teorema Bayes Dan Case Based Reasoning Diagnosa Penyakit Pada Tanaman Tomat ]]>
<![CDATA[Agus Iskandar]]>;
<![CDATA[Galih Rakasiwi]]>
<![CDATA[ Journal of Computer System and Informatics (JoSYC) Vol 5 No 1 (2023): November 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.47065/josyc.v5i1.4617
<![CDATA[Diseases in tomato plants have a significant impact on the agriculture industry as they can reduce crop yields and tomato quality. Therefore, this research aims to compare the Bayesian Theorem and Case-Based Reasoning (CBR) methods in diagnosing tomato plant diseases. The Bayesian Theorem is a statistical approach based on probability, while CBR uses knowledge from previous cases. This study includes an analysis of the performance of both methods in terms of diagnostic accuracy, result delivery speed, and resource efficiency. The research results have the potential to assist farmers and agricultural experts in choosing the most suitable method for diagnosing tomato plant diseases. Furthermore, the implementation of expert systems in agriculture can have a positive impact on tomato cultivation productivity and sustainability. This research aims to provide practical guidance for stakeholders in the agricultural field and contribute to sustainable agriculture improvement, with a specific focus on disease identification and management in tomato plants. The percentage values of the application of the Bayesian Theorem and Case-Based Reasoning methods show that Case-Based Reasoning has a lower success rate in diagnosing Fusarium Wilt and Bacterial Wilt compared to the Bayesian Theorem. However, Case-Based Reasoning excels in diagnosing Tomato Yellow Leaf Curl Virus (TYLCV), achieving a success rate of 100%, while the Bayesian Theorem reaches 63%.]]>
<![CDATA[Perbandingan Penggunaan Certainty Factor dan Pendekatan Dempster-Shafer dalam Sistem Expert untuk Mendiagnosis Kasus Cacar ]]>
<![CDATA[M. Mustaqim]]>;
<![CDATA[Agus Iskandar]]>
<![CDATA[ Journal of Computer System and Informatics (JoSYC) Vol 5 No 1 (2023): November 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.47065/josyc.v5i1.4618
<![CDATA[Varicella, another name for smallpox, is a viral infection that primarily affects children and can cause an itchy rash on the skin and fever. Smallpox should be diagnosed as soon as possible to stop the spread of the disease and provide appropriate treatment. The aim of this study was to compare the Dempster-Shafer and Certainty Factor (CF) approaches for diagnosing smallpox. The main aim of this study was to evaluate the effectiveness of both methods in detecting smallpox and to determine which is more accurate and reliable in the diagnosis process. The CF method is an approach in artificial intelligence that uses confidence factor values to describe an expert's level of confidence in an event or statement. Meanwhile, Dempster Shafer is a combined theory that can overcome uncertainty in decision making by modeling the level of confidence in various aspects. This research will outline the basic concepts of the Certainty Factor method and Dempster-Shafer Theory, as well as analyze their application when making a diagnosis of smallpox. The level of precision, dependability, and effectiveness of each technique will be compared. It is hoped that health professionals can improve smallpox diagnosis and make better clinical judgments with the help of the results of this study. The results of this research will help medical personnel and health practitioners make better decisions in diagnosing smallpox. Apart from that, this research can also help reduce diagnostic errors and speed up the treatment process. The calculation results from this research show that for Shingles, the Dempster Shafer approach produces a success rate of 86%, while the Certainty Factor method offers a success rate of 99%.]]>
<![CDATA[Seleksi Pemilihan Staff Account Receivable dengan Penerapan Sistem Pendukung Keputusan Kombinasi Metode WASPAS dan ROC ]]>
<![CDATA[Naufal Rifqi]]>;
<![CDATA[Agus Iskandar]]>
<![CDATA[ Journal of Computer System and Informatics (JoSYC) Vol 5 No 1 (2023): November 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.47065/josyc.v5i1.4619
<![CDATA[Appropriate Account Receivable staff must be qualified, have skills, and exhibit traits that are suitable for the duties and responsibilities associated with receivables management. Errors in staff selection can potentially create problems in the management of receivables, result in delays in the collection of funds, and pose a greater risk of loss to the company. Therefore, the selection and selection of qualified Account Receivable Staff is a very key factor in achieving optimal financial performance. Selection in the selection of Account Receivable staff has several criteria, namely Education, Experience, Technical Skills, Communication Skills and Negotiation Skills. In the midst of an increasingly complicated business environment and intense competition, the use of decision support systems (SPK) is becoming more relevant to assist in the optimal employee selection process, given the importance of objectivity and accuracy in the selection process by applying the ROC (Rank Order Centroid) and WASPAS (Weighted Aggregated Sum Product Assesement) methods which are utilized to provide weight values to the selection criteria, while WASPAS is used to verify the results of the selection decision. So that the best Account Receivable Staff selected is alternative A5 with the highest value of 3.8354 as the first rank.]]>
<![CDATA[Penerapan Metode EDAS dan ROC Dalam Rekomendasi Objek Wisata Pantai Terbaik ]]>
<![CDATA[Sari, Anggi Farika]]>;
<![CDATA[Sapira, Septia Nike bela]]>;
<![CDATA[Aulia Dewi, Elsa Adhista]]>;
<![CDATA[Pinem, Agusta Praba Ristadi]]>
<![CDATA[ Journal of Computer System and Informatics (JoSYC) Vol 5 No 2 (2024): February 2024 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.47065/josyc.v5i2.4765
<![CDATA[Indonesia's natural diversity, cultural heritage and history have given rise to attractive tourism destinations, including Central Java Province. Central Java offers a diversity of beaches, attracting millions of tourists every year. However, many tourists have difficulty choosing a beach tourist destination that suits their wishes. Decision Support Systems (DSS) are a solution with various methods, one of which is the Evaluation Method based on Distance from Average Solution (EDAS) which is currently used together with Rank Order Centroid (ROC) weighting. This method has been proven to be effective in complex decision situations. In this context, using 13 Alternative Beaches was taken by taking into account the highest number of visitors in each Regency/City in Central Java Province and applying criteria such as cleanliness, facilities, popularity, rating and ticket prices used for evaluation. This research aims to examine the relationship and integration of the ROC and EDAS weighting methods in recommendations for the best beach tourist attractions in Central Java. It is hoped that this study will be able to provide a better interpretation and obtain a ranking ranking of alternative beach tourist attractions in Central Java, thereby contributing to tourists making more accurate decisions according to the criteria in the context of selecting beach tourist locations. The results of the research show that Jatimalang Beach is the best alternative with the highest score of 1,000. Thus, Jatimalang Beach is declared as the best choice for the best tourist attraction.]]>
<![CDATA[Sistem Pendukung Keputusan Dalam Penilaian Kinerja Karyawan Rumah Sakit Menggunakan Metode Multi Factor Evaluation Process ]]>
<![CDATA[Anwarsyah, Anwarsyah]]>;
<![CDATA[Triyono, Gandung]]>
<![CDATA[ Journal of Computer System and Informatics (JoSYC) Vol 5 No 2 (2024): February 2024 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.47065/josyc.v5i2.4778
<![CDATA[Employees are a resource that is a supporting factor for a company or organization. Having employees who meet qualification standards can develop the company and increase company productivity. Employee performance assessments are carried out looking at the company's success in organizing employees and determining the level of employee loyalty and professional performance towards the company. Petukangan Hospital has a large number of employees ranging from health workers to management employees and others. Currently there is no system used to evaluate employee performance, so the assessment process takes a long time and is not timely and there is an element of subjectivity in the assessment. Therefore, we need a system that can help assess employee performance with the aim of the research as an alternative in systematically and objectively assessing employee performance according to the weights and criteria obtained by each employee. In this research, the method used is the Multi Factor Evaluation Process of a Decision Support System, where this method carries out an assessment by calculating weights and criteria. The aim of this research is to provide the best solution and tools for Petukangan Hospital in assessing employee performance, and this research is expected to have benefits that can become effective and efficient problem solving. This research has results obtained from testing in the form of a ranking system where employees with the highest total evaluation score is the employee with the best performance score. The calculation results show that the employee with the best performance and rank 1 is Employee 26 with a value of 0.8375.]]>
<![CDATA[Friends Recommendation on Social Networks using the Bayesian Personalized Ranking-Matrix Factorization ]]>
<![CDATA[Ali, Muhammad Haidir]]>;
<![CDATA[Baizal, Z. K. A.]]>
<![CDATA[ Journal of Computer System and Informatics (JoSYC) Vol 5 No 2 (2024): February 2024 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.47065/josyc.v5i2.4804
<![CDATA[In the digital landscape of social networking, the challenge of improving friend recommendation systems is pivotal for enhancing user interaction and fostering social connections. Addressing this challenge, the current study innovates by fusing Bayesian Personalized Ranking (BPR) with Matrix Factorization (MF), culminating in a novel BPR-MF model designed for the intricacies of social network relationships. The study harnesses a rich dataset from LastFM, comprising 27,806 interactions among 7,624 users, to analyze mutual follower patterns and augment the precision of friend recommendations. Through rigorous preprocessing and systematic evaluation of the BPR-MF model against different numbers of latent factors, the research uncovers that a configuration of 20 latent factors is most effective, achieving an RMSE of 0.156 and an AUC ROC of 0.800. This discovery addresses the critical problem of balancing computational complexity with prediction accuracy in recommendation models. It also demonstrates the necessity for a nuanced, data-driven approach to generate relevant social connections. The research sets a new direction for future studies aiming to capitalize on user interaction data to offer precise friend suggestions, all while upholding user privacy and avoiding reliance on personal data.]]>
<![CDATA[Implementasi Metode Dempster-Shafer Untuk Deteksi Kesehatan Mental Pada Mahasiswa Berbasis Web ]]>
<![CDATA[Jalaluddin, Alif]]>;
<![CDATA[Arumi, Endah Ratna]]>;
<![CDATA[Sasongko, Dimas]]>;
<![CDATA[Pinilih, Sambodo Sriadi]]>;
<![CDATA[Yudatama, Uky]]>;
<![CDATA[Arif Yudianto, Muhammad Resa]]>
<![CDATA[ Journal of Computer System and Informatics (JoSYC) Vol 5 No 2 (2024): February 2024 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.47065/josyc.v5i2.4830
<![CDATA[Mental health is a person's soul condition to budaptasi in its environment to feel happy or get the comfort of life, so as not to experience mental disorders. Often mental health is ignored by most people because it is different from physical health that can be seen directly with the eyes and can be identified easily. Lack of awareness of mental health in the life of the people of Indonesia and the assumption that a person who goes to psychologists is a person inseasonable, often the individual who actually undergoes mental health problems reluctant to get help from experts or deny that he does not have mental health problems. Limitations of time and costs are also one of the constraints of a student reluctant to get help from experts like psychologists. Therefore, a web-based expert system is built with a dempster-shafer method to use as detection on the student and allows the user to know whether the user has a tendency of the problem on its mental health or not before the official consultation is required from the expert. Testing Accuracy Comparison System between the results of the system and experts by using 100 correspondents from students at Muhammadiyah Magelang University (UNIMMA) 89% know mental health and 65% have experienced mental disorders. The results of the SRQ29 data used and were spread among campus students, this study has used 20 sample data and produces 70% expert suit compliance. From the results of expert suitability obtained from the calculation of the system by selecting symptoms and automatically the system will calculate the accuracy of the existing Belief Valident in every symptom. Then the system will take decisions based on the results of the largest calculation value.]]>
<![CDATA[Sistem Pakar Diagnosa Penyakit Angsa Menggunakan Metode Forward Chaining Berbasis Web ]]>
<![CDATA[Guko, William Yviis]]>;
<![CDATA[Eviyanti, Ade]]>;
<![CDATA[Hindarto, Hindarto]]>
<![CDATA[ Journal of Computer System and Informatics (JoSYC) Vol 5 No 2 (2024): February 2024 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.47065/josyc.v5i2.4835
<![CDATA[Geese have many benefits for human needs. Starting from meat, eggs, feathers, fat, and other uniqueness such as guarding other livestock if there are animals or strangers approaching their territory. However, in Indonesia, goose utilization is less desirable and only a few do it. This poses a probӏem for goose breeders due to the absence of knowӏedge about the diseases experienced and the handӏing soӏutions. An expert system is an artificiaӏ inteӏӏigence that supports expert decision-making. The forward chaining method provides conclusions through rules derived from existing facts. This Expert System for Diagnosing Swan Diseases Using the Web-Based Forward Chaining Method is designed to make it easier for farmers or users to consult about the diseases experienced and treatment solutions with 90% diagnostic results. This expert system is made based on a website that can be accessed easily and at any time. Based on black box testing, the results obtained show 100% system functionality, so this expert system application can be used.]]>
<![CDATA[Prediksi Harga Kelapa Sawit Menggunakan Metode Extreme Learning Machine ]]>
<![CDATA[Hariansyah, Jul]]>;
<![CDATA[Budianita, Elvia]]>;
<![CDATA[Jasril, Jasril]]>;
<![CDATA[Afrianty, Iis]]>
<![CDATA[ Journal of Computer System and Informatics (JoSYC) Vol 5 No 2 (2024): February 2024 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.47065/josyc.v5i2.4858
<![CDATA[Palm oil is one of the keys to the Indonesian economy and the main commodity for attracting foreign investment. The palm oil and palm kernel industry generates most of the foreign currency from palm oil. The price of palm oil often goes up and down every month resulting in instability in the income received by people who own oil palm plantations. The aim of predicting palm oil prices is to carry out appropriate planning or steps for palm oil business actors. One way to overcome this problem is to make predictions. One method that can make predictions is the Extreme Learning Machine (ELM). ELM is an artificial neural network method used to predict palm oil prices. The ELM method is a feedforward method with a single hidden layer which is better known as a single hidden layer feedforward neural network (SLFNs). In this research, the best implementation was 5 inputs with 20 neurons in the hidden layer with output in the form of palm oil price predictions. Based on the tests carried out, the research produced the smallest error rate of 0.0027111424247658633 using 20 neurons in the hidden layer so that the latest data prediction test results for 5 price rotations in September rotation 1 were 1400.314191, September rotation 2 were 1846.798921, September rotation 3 amounted to 1505.430419, September rotation 4 amounted to 2301.853412, September rotation 5 amounted to 2645.082489 in palm oil price predictions.]]>
<![CDATA[Evaluation of Salesperson Performance in the Sales Allowance Decision Support System Using the MARCOS and PIPRECIA Methods ]]>
<![CDATA[Hadad, Sitna Hajar]]>;
<![CDATA[R Metha, Abhishek]]>;
<![CDATA[Setiawansyah, Setiawansyah]]>;
<![CDATA[Sulistiani, Heni]]>
<![CDATA[ Journal of Computer System and Informatics (JoSYC) Vol 5 No 2 (2024): February 2024 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.47065/josyc.v5i2.4863
<![CDATA[Optimal salesperson performance is the main key to a company's success in achieving sales targets and business growth. A reliable salesperson is not only able to sell products or services, but also has the ability to build strong relationships with customers. The purpose of this study is to assess the performance of salesperson in providing sales allowances based on performance results carried out by applying a combination of MARCOS and PIPRECIA methods, so as to produce a recommendation for the final assessment of salesperson performance that will assist the company in providing sales benefits to salespersons. The combination of Pairwise Relative Criteria Importance Assessment (PIPRECIA) and Measurement of Alternatives and Ranking According to Compromise Solution (MARCOS) forms a powerful holistic approach to decision making. PRCIA facilitates the identification and assessment of the relative weights of each decision criterion, providing a solid foundation for assigning value to the relative importance between criteria. The results of the salesperson performance evaluation ranking above show the final results for rank 1 with a value of 4.3446 obtained by Rini, rank 2 with a value of 3.5369 obtained by Murniasih, rank 3 with a value of 3.1807 obtained by Hana Ferbi.]]>
