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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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Diagnosa Kecanduan Gadget Pada Anak Usia Dini dengan Metode Fuzzy Sugeno dan Fuzzy Mamdani Rama Setiawan; Agung Triayudi; Arie Gunawan
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.v4i2.3018

Abstract

The Tsukamoto fuzzy logic method is one method for problem solving control systems, which is good to implement with a system method that will use human knowledge that can be entered into the system on a computer to find and solve problems that usually require expertise or expertise. looking for a truth. The purpose of this study is to analyze and find methods that can be used in diagnosing gadget addiction in early childhood, and to compare two fuzzy methods that will be used as methods to diagnose gadget addiction in early childhood. The methods used in this study are expert system methods, namely fuzzy sugeno and fuzzy mamdani. The results showed that many children experience addiction to gadgets with a susceptibility to 1-4 hours of use time in one day. The level of addiction in boys is somewhat higher than in girls, the large number of children who are addicted to gadgets at a very early age to recognize and experience addiction to gadgets is the author's main goal to make this thesis if it can be used to monitor the level of gadget addiction in early childhood, research on the contribution of the method of applying the method the fuzzy sugeno and fuzzy mamdani algorithms in diagnosing gadget addiction in early childhood and the contribution to this method is the application of the fuzzy mamdani method and the fuzzy sugeno method to the fuzzy algorithm and the problem of this research is to determine the results of defuzzification of the data that has been obtained.
Analisis Perilaku Wisatawan Berdasarkan Data Ulasan di Website Tripadvisor Menggunakan CRISP-DM: Wisata Minat Khusus Pendakian Gunung Rinjani dan Gunung Bromo Yerik Afrianto Singgalen
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.v4i2.3042

Abstract

Traveller behavior needs to be comprehensively identified and analyzed to determine changes in tourism preference in Indonesia. One relevant approach to identifying traveler behavior is sentiment analysis through review data on the Tripadvisor website by text mining approach. This study aims to recommend a sentiment analysis model that is useful for managers of particular interest climbing tourist destinations on Mount Rinjani and Mount Bromo based on the type of visit alone (solo), with couples (couple), with friends, and with family (family). The research method used is Cross Industry Standard Process for Data Mining (CRISP-DM), with an algorithm adapted to managing tourist destinations for Mount Rinjani and Mount Bromo, namely attractions, roads and modes of transportation (accessibility), and accommodation. To overcome the problem of data balance in datasets, the calculation process of the Decision Tree (DT) algorithm and the Support Vector Machine (SVM) is connected to the Synthetic Minority Over-sampling Technique (SMOTE) operator in the Rapidminer application. The results of this study showed that the SVM algorithm showed better performance with an accuracy value of 97.67%, precision of 100%, recall of 95.34, and f-measure of 97.61% in the classification of 1075 text data of Mount Bromo and 326 review data of Mount Rinjani. In addition, in the context of Mount Rinjani, the top five words that often appear in tourist review data on Mount Rinjani are as follows: summit (272), Rinjani (259), trek (201), hike (170), mountain (159). On the other hand, the top five words that often appear in tourist review data on Mount Bromo are as follows: Bromo (1864), sunrise (1124), view (854), crater (758), and mount (577). Thus, it can be seen that tourists with the type of visit alone (solo), with couples (couple), with friends (friends), and with family (family) have a preference for the types of attractions in the form of summits, craters, natural beauty of mountains, hiking trails, types of transportation modes as well as supporting accommodation that needs to be prepared to keep the sustainability of tourism.
2024 Presidential Election Sentiment Analysis in News Media Using Support Vector Machine Bayu Muhammad Iqbal; Kemas Muslim Lhaksmana; Erwin Budi Setiawan
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.v4i2.3051

Abstract

The 2024 presidential election is an event for all Indonesian people to determine their best leader. The presidential and vice presidential candidates are also competing to give their best efforts so that they can be elected as President and Vice President. The news media also provide news related to the 2024 presidential election with various titles that can interest their readers. Not infrequently the titles raised contain words that have sentiments, both positive and negative. In order to facilitate the analysis of the sentiments of these news titles, it is necessary to build a system that can detect the sentiments of these titles. In this study, we built a sentiment analysis system using the Support Vector Machine (SVM) method on news headline data obtained from online news media to detect whether news headlines contain positive or negative sentiments. For feature exctraction we compare the effect of FastText word embedding with TF-IDF for feature extraction. In the SVM method, several experiments were carried out on the attributes of C, kernel, gamma, and the ratio of the test data. The results obtained are a FastText can outperform TF-IDF for feature extraction. Also, combination of Kernel, C, and gamma values that give the best accuracy score of rbf, 1, and auto respectively at a test data ratio of 90:10, with an accuracy score of 99%.
Optimizing LQ45 Stock Portfolio To Maximize Sharpe Ratio Value Using LSTM Tasya Salsabila; Deni Saepudin; Aniq Atiqi Rohmawati
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.v4i2.3065

Abstract

Investment is an investment activity within a certain period with the hope of getting a profit. Things that need to be considered by investors when investing are not just yields (return), but investors need to consider the purpose of the investment and the investment period. This study optimizes the formation of portfolios by utilizing the predicted value of stock prices using LSTM. The test used five daily stock indices from LQ45, namely BBCA, BBRI, TLKM, UNVR, and BMIR, from April 2010 – April 2020. The portfolio was built using the Genetic Algorithm and Equal-Weight (EW) method. Portfolio of Genetic Algorithm and Equal-Weight (EW) without predictions used as a benchmark. The experimental results show that using the LSTM prediction and Genetic Algorithm can produce an optimal portfolio with the highest Sharpe ratio value at 1.3950.
Sistem Pendukung Keputusan dalam Mendiagnosa Gejala TBC dengan Metode WASPAS dan CPI Akhmad Primulyana; Agung Triayudi; Arie Gunawan
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.v4i2.3068

Abstract

Mycobacterium bacteria is the cause of tuberculosis, an infectious disease that attacks the respiratory tract in humans and can easily spread through the air. In 2012, WHO data showed that tuberculosis is an infectious disease that causes the second largest health problem in the world. Tuberculosis is a disease that can attack other parts of the body as well as the lungs. The sooner a person finds out he has tuberculosis and gets tested, the more likely he will recover faster. There are many detection methods, but many are time consuming. A decision support system is needed using the WASPAS method and the CPI method which are capable of diagnosing tuberculosis. To overcome this problem. By forming a decision tree represented by rules, this decision support system implements Rank Order Centroids, one of the classification techniques in machine learning used in the data mining process. This study produces a system that is expected to make it easier for the general public to obtain timely and accurate information for diagnosing tuberculosis. A decision support system for diagnosing tuberculosis was developed as a result of this study. After being tested with 100 patient data, 50 as training data and 50 as testing data, the Confusion Matrix produces an accuracy value of 90%.
Perbandingan Metode Fuzzy Tsukamoto dengan Fuzzy Mamdani Untuk Mendeteksi Tingkat Kecanduan Media Sosial Pada Remaja Ariel Cahyono; Agung Triayudi; 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.v4i2.3069

Abstract

The level of social media use in Indonesia has increased every year. This is caused by several factors, one of which is the tendency to play social media so that you forget the time to do other activities such as studying. A system is needed that is able to detect whether someone is addicted to social media or not. The Tsukamoto fuzzy method is a method that can solve a problem by using a system on a computer in search of a truth and usually requires some expertise. While the fuzzy mamdani method has a function in finding a solution in solving the problem of social media addiction in today's youth. This comparison is done by the author to find the best answer from one of the methods used. This research was created in order to be able to detect the level of social media addiction in adolescents in the form of a web to inform adolescents to avoid the negative symptoms of social media addiction such as timelessness, lazy learning and being unable to stop oneself from controlling social media use. Then after testing with 25 adolescent data, the results obtained were 10 adolescents experiencing social media addiction problems and 15 adolescents not. It can be seen that the Tsukamoto method has a very addictive score of 0 to 20 for 10 teenagers and 15 teenagers with a non-addiction score of 80 to 100. Meanwhile, it is known that the Mamdani method has a very addictive score of 0 to 10 for 10 teenagers and 15 teenagers with a non-addicted score of 40 to 50.
Comparative Analysis of Max-Throughput and Proportional Fair Scheduling Algorithms in 5G Networks St. Nur Hikmah Damayanti; Siti Amatullah Karimah; Setyorini Setyorini
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.v4i2.3073

Abstract

Mobile network service use is growing, especially after the Covid-19 pandemic. To improve the quality of mobile network services, 5G comes as a network service ecosystem with low latency, which is 1ms, or about 10 times lower than 4G, making 5G able to provide more efficient access, especially in real-time network utilization. Maximum speed can be obtained by sharing limited bandwidth. The limited amount of available bandwidth causes the need for a Packet Scheduler, which aims to improve the efficiency and fairness of bandwidth usage. This research uses two packet schedulers comparing the Proportional Fair algorithm and the Max-Throughput algorithm using test scenarios for changes in the number of users and user speed. The resulting output value analyzes resource limits such as frequency, power, speed, and time in each scenario to allocate resources so that their use remains efficient with a Quality of Service that remains stable and maintained. In simulation testing using the 5G-air-simulator, the average value obtained in the delay is 1,394 ms, throughput is 0,636, and fairness index is 0,967.
Penerapan Metode WASPAS dalam Pemilihan Handphone Gaming Terbaik Sitti Nur Alam; Hendrikus Haipon; Septiana Ningtyas; Saludin Saludin; Kraugusteeliana Kraugusteeliana
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.v4i2.3087

Abstract

The technology that people are most interested in is mobile phones. Apart from being a tool for exchanging information and as a means of communication, mobile phones are also used as entertainment tools such as playing games. The large number of HP brands confuses potential buyers in determining which HP brand is good. To help the public in choosing the best HP Gaming brand, this can be done by using the SPK. SPK is a system where the procedure for working is to use a computer working procedure. In using SPK, must use the method. In this study the method used was the WASPAS method. The WASPAS method is a method that uses 2 steps, where the first step is to calculate normalization by carrying out the division operation. By implementing the WASPAS method, a value of 2.9710 is obtained as an alternative to A2 as the best HP Gaming brand with the Infix Zero 20 brand.
Analisis Sentimen Wisatawan terhadap Taman Nasional Bunaken dan Top 10 Hotel Rekomendasi Tripadvisor Menggunakan Algoritma SVM dan DT berbasis CRISP-DM Yerik Afrianto Singgalen
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.v4i2.3092

Abstract

It is necessary to analyze traveler sentiment towards Bunaken National Park and Tripadvisor's Top 10 Recommended Hotels to identify traveler satisfaction with the attractions, accommodation services, and transportation used. Considering this, this study uses the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework by testing the performance of the Decision Tree (DT) algorithm and the Support Vector Machine (SVM). CRISP-DM has six stages: business understanding, data understanding, data preparation, modeling, evaluation, and deployment. Based on the processing of 398 Bunaken National Park destination data and 1793 review data on the top 10 hotels recommended by Tripadvisor, the SVM algorithm performed better. In the context of Bunaken National Park destination data, the performance of the SVM algorithm using the SMOTE operator can produce 100% accuracy, precision, recall, f-measure, AUC, and t-Test values. In addition, in processing the top 10 hotel datasets recommended by Tripadvisor, the SVM algorithm using the SMOTE operator provides an accuracy value of 96.42%, a precision value of 100%, a recall value of 92.83%, an f-measure value of 96.27%, an AUC value of 100%, and a t-Test value of 96.4%. The results of identifying the five words that most often appear in tourist reviews for Bunaken Marine Park tourist destinations are 164 words fish, 165 words island, 193-word dive, 230 diving, and 280 words Bunaken. This indicates the driving factor for tourist visits to Bunaken Marine Park is the beauty of underwater nature, including the diversity of marine animal species, the natural beauty of the archipelago, and diving activities. In addition, the results of identifying the five words that most often appear in traveler reviews for Tripadvisor's top 10 recommended hotels are 1170 great words, 1222 bunaken words, 1550 resort words, 1613 diving words, and 1711 dive words. This indicates that the characteristics of tourists who have the motive of traveling to Bunaken National Tourism Park have the intention to use resort accommodations around Bunaken and have mobility and facilities to support diving activities. Thus, the output of this study can be used as a recommendation for accommodation service managers to prepare supporting facilities for tourists who want to visit Bunaken National Park.
Sistem Pendukung Keputusan Untuk Menentuan Desa Paling Maju dengan Menggunakan Metode MOORA Rifqi Naufal Fajrul Mubaroq; Evita Dwi Prasanti; Yuni Novita Br. Sihaloho; Edoardus Dwijo Wijayanto; Akhmad Fauzi
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.v4i2.3130

Abstract

Decision Support System (DSS) is an approach to support decision making using data, provides an easy interface, and can incorporate the thinking of decision makers. In this study, we take a case study that can be solved by using a decision support system, where the problem faced by the Government of the Sub-District of Sumbang is how to determine the most advanced village in the District of Sumbang, because to do a selection one must use the manual method and the assessment process takes a long time to get. results. Therefore, a decision support system is made that can assist the assessment process and where the decision support system is carried out using the moora method. Based on the results of calculations regarding research in determining the most advanced village in the Contributing Regency is the Contributing Village with a value of 0.3758. Where the village has very good road conditions and the facilities available in the village are also very good compared to other villages.

Page 21 of 45 | Total Record : 443

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