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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 23 Documents
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Search results for , issue "Vol 5 No 3 (2024): May 2024" : 23 Documents clear
Penerapan Model Waterfall dalam Pengembangan Perangkat Lunak Pemantauan Tanaman Anggur Berbasis Mobile Menggunakan IoT Kasliono, Kasliono; Ruslianto, Ikhwan; Erniajan, Yunita
Journal of Computer System and Informatics (JoSYC) Vol 5 No 3 (2024): May 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i3.5099

Abstract

Unfavorable tropical climatic conditions as well as the status of grapes as not a national priority commodity, have led to high production costs and low productivity in grape cultivation in the pontianak area. So this research has The purpose to conceptualize and develop an IoT-based Android application that allows observation of grape plants in the Greenhouse. Thus, it is hoped that this application can provide solutions for farmers in monitoring plant conditions in real-time, increasing productivity, and improving the quality of grape crops in the area. In previous research, The app is technically less user-friendly, not suitable for the average users, especially farmers. Key components include an Android app, a data processing system, and sensors measuring values like air temperature, humidity, and soil moisture.. The data processing system receives data from sensors and sends it to the Android app via the internet network.. The Android app allows users to view Greenhouse environmental statistics. The research was carried out in stages, beginning with hardware and software ideation and ending with real-world testing of the application. According to the research, the system's implementation is functional, nodes can send data and be displayed on mobile applications, and tests were conducted using the black box testing method, which yielded a "successful" statement on eight tests performed on the Android mobile application.
Rekomendasi Pemberian Kredit Pemilikan Rumah Menggunakan Kombinasi Metode VIKOR dan Pembobotan Entropy Irmansyah Lubis, Ahmadi; Siregar, Rosma
Journal of Computer System and Informatics (JoSYC) Vol 5 No 3 (2024): May 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i3.5118

Abstract

Home Ownership Credit (KPR) is the process of buying a house by way of credit or installments for a certain period of time and a determined interest rate. Problems that often arise in the process of granting mortgages are when providing an analysis of recommendations for the suitability of a house, such as credit analysis errors which often result in bad credit payments and disrupt the fund circulation system between credit payments and receivables. Billing. In addition, there is no filter in determining the eligibility of providing credit computerized, the system is equipped with a decision support system that can describe the supporting factors that are used as a calculation weight in making decisions on determining home ownership loans for those who deserve to receive them. To analyze the feasibility of providing home ownership loans, a decision support system is needed that can provide a good analysis to determine the creditworthiness of home ownership with the VIKOR method and the Entropy method. The Entropy method is applied to determine the weight of each criterion and the VIKOR method is used to rank alternatives. Based on the results of the study, the VIKOR method and the Entropy weighting method can provide recommendations for providing home ownership loans to eligible customers based on specified criteria. The ranking results were obtained by testing variations in the VIKOR index value with the best alternative result, namely A3 (3rd Alternative). And the Entropy method produces objective and proportional criteria weights and obtains valid criteria weights without having to give criteria weights manually or subjectively, so it is useful for determining the weight of criteria that need not be doubted about their validity.
Decision Support System for Best Honorary Teacher Performance Assessment Using a Combination of LOPCOW and MARCOS Putra, Ade Dwi; Arshad, Muhammad Waqas; Setiawansyah, Setiawansyah; Sintaro, Sanriomi
Journal of Computer System and Informatics (JoSYC) Vol 5 No 3 (2024): May 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i3.5127

Abstract

Teachers are the main pillars in the formation and development of future generations. They not only pass on knowledge, but also play an important role in guiding, inspiring, and shaping the character of students. The main problems in selecting the best honor teachers are limited resources and a less systematic evaluation process, lack of transparency and consistency in the selection process can also lead to dissatisfaction and injustice among honor teachers. Through the combination of LOPCOW and MARCOS, this research succeeded in producing a more accurate and accountable ranking in the selection of the Best Honorary Teacher. The LOPCOW approach provides a deep understanding of percentage changes against set criteria, while MARCOS assists in weighting compromise solutions that can optimally meet those criteria. Thus, the study provides a more holistic and detailed view of various aspects of teacher quality and performance, enabling better decision-making in selecting the Best Honorary Teachers who meet educational needs and advance student learning. The ranking results showed that the assessment results from the LOPCOW and MARCOS methods gave results, namely rank 1st with a final value of 0.3404446 obtained by SF Teachers, 2nd place with a final value of 0.3367384 obtained by LBS Teachers, and 3rd place with a final value of 0.3343083 obtained by ASB Teachers.
Penerapan Chatbot pada Aplikasi Web Tanya Jawab Tentang Fiqih Jual Beli Islam Menggunakan LangChain Nurhapiza, Nurhapiza; Harahap, Nazaruddin Safaat; Fikry, Muhammad; Affandes, Muhammad
Journal of Computer System and Informatics (JoSYC) Vol 5 No 3 (2024): May 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i3.5148

Abstract

Fiqh is the field that studies Islamic rules on how humans behave, both in speech and action. Islamic Fiqh of buying and selling is a branch of fiqh that concentrates on the laws and rules relating to transactions and social interactions that occur in the daily lives of Muslims. There are many sources of learning about the fiqh of buying and selling, including books and the internet. However, manual searches can take a long time and make it difficult for some people to gain in-depth understanding. The application of a chatbot to a question and answer web application can provide a solution to provide easier access. This research aims to provide an effective and efficient solution in understanding fiqh muamalah (Islamic buying and selling). This research develops a question and answer system about the fiqh of Islamic buying and selling to make it easier for users to understand, by utilizing a deep learning approach through technologies such as LangChain, OpenAI, Large Language Model, and ChatGPT 3.5 turbo. Implementation is done through a chatbot web application that provides an initial display and menu, allowing users to ask questions about the fiqh of Islamic buying and selling and see the answers and references. Testing was conducted by students of UIN Sultan Syarif Kasim Riau and an ustaz who has a good understanding of fiqh muamalah using ten questions that were tested through the question and answer web application as a guide. The test results showed an answer evaluation of 88.8% with a very suitable category regarding the correctness of the responses given.
Klasifikasi Penyakit Cacar Monyet Menggunakan Metode Support Vector Machine Anugrah, Wendy; Haerani, Elin; Yusra, Yusra; Oktavia, Lola
Journal of Computer System and Informatics (JoSYC) Vol 5 No 3 (2024): May 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i3.5149

Abstract

Monkey pox is a zoonotic disease caused by the monkey pox virus and this disease is very dangerous. Monkey pox can be detected in advance by using information contained in patient data and applying machine learning techniques. This study aims to classify monkey pox using the Support Vector Machine (SVM) method. This test is carried out using a confusion matrix by comparing the ratio of training data and test data with a ratio of 70:30, 80:20, 90:10 and using the RBF kernel. Based on the test results, the highest ratio results were obtained at 90:10 with the best accuracy value of 65% with SVM parameter testing, namely the value C= 10 and y (gamma)= 1. Based on the results of tests carried out using the Support Vector Machine method, the accuracy values ​​were quite good.
Comprehensive Analysis of Sentiment Classification and Toxicity Assessment in Cultural Documentary Videos Singgalen, Yerik Afrianto
Journal of Computer System and Informatics (JoSYC) Vol 5 No 3 (2024): May 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i3.5150

Abstract

This research explores sentiment classification and toxicity assessment in cultural documentary videos through a systematic analysis framework based on the Cross-Industry Standard Process for Data Mining (CRISP-DM). The study evaluates the sentiment polarity of viewer comments by utilizing a diverse array of machine-learning algorithms, including k-NN, DT, NBC, and SVM. It identifies toxic language patterns across multiple videos. Additionally, the research employs SMOTE to address class imbalance issues and enhance model performance. The results reveal high accuracy rates ranging from 72.24% to 96.79% in sentiment classification, indicating the effectiveness of the proposed methodology. Moreover, toxicity analysis unveils varying degrees of toxic language prevalence, with toxicity scores ranging from 0.01270 to 0.09334 across different videos. Despite these achievements, the study acknowledges the inherent limitations of toxicity scoring algorithms in capturing contextual nuances. Overall, this research contributes to understanding sentiment dynamics and toxicity trends in cultural documentary content and underscores the importance of employing advanced machine learning techniques within a structured analytical framework for insightful data interpretation and decision-making.
Comprehensive Analysis of Sentiment and Toxicity Dynamics in Tourist Vlog Reviews: A CRISP-DM Approach Singgalen, Yerik Afrianto
Journal of Computer System and Informatics (JoSYC) Vol 5 No 3 (2024): May 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i3.5154

Abstract

This research employs the CRISP-DM framework to analyze sentiment and toxicity dynamics in tourist vlog reviews thoroughly. The study delves into sentiment classification and toxicity identification nuances by leveraging machine learning algorithms such as k-NN, SVM, NBC, and DT with SMOTE. Utilizing a dataset comprising a substantial number of posts, the analysis reveals varying levels of accuracy across different algorithms. For instance, k-NN and SVM showcase promising accuracy rates of 85.90% and 86.27% in sentiment classification, while NBC and DT with SMOTE yield 72.52% and 71.14%, respectively. Furthermore, the research elucidates the limitations of toxicity analysis, with NBC demonstrating a precision of 64.96% and DT exhibiting lower recall rates. These findings highlight the importance of robust methodologies for understanding sentiment and toxicity dynamics in online content, particularly in tourist vlog reviews.
Perbandingan Performa Klasifikasi Terjemahan Al-Qur'an Menggunakan Metode Random Forest dan Long Short Term Memory Aftari, Dhea Putri; Safaat, Nazruddin; Agustian, Surya; Yusra, Yusra; Afrianty, Iis
Journal of Computer System and Informatics (JoSYC) Vol 5 No 3 (2024): May 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i3.5156

Abstract

This study focuses on the use of the Qur'an as the primary source of Islamic teachings, aiming to facilitate Muslims' understanding of its content. To achieve this, the classification of translated Qur'anic verses was conducted. Two methods that are rarely used for Qur'anic translation data are Random Forest (RF) and Long Short Term Memory (LSTM) due to their ability to process large and complex data. The data used in this study are translations of the Qur'an that have been classified into 15 topics by previous research, but this study will only focus on 6 topics. The objective of this research is to compare the performance of RF and LSTM in classifying Qur'anic translations into 6 different categories. The results show that in the preaching category, LSTM consistently outperformed RF, with an F1-Score of 57.3% and an accuracy of 96.8%, whereas RF achieved an F1-Score of 49.4% and an accuracy of 97.5%. These findings indicate that LSTM has better performance, especially with proper preprocessing, optimal parameter tuning, and balanced data. This study provides important insights into the development of classification models for Qur'anic translation texts, highlighting the importance of proper preprocessing and parameter tuning.
Sistem Pendukung Keputusan Penilaian Kinerja Tenaga Honor Panitia Pengawas Menggunakan Kombinasi Logarithmic Least Squares Weighting dan MABAC Mahendra, Ferdian Jerry; Setiawansyah, Setiawansyah
Journal of Computer System and Informatics (JoSYC) Vol 5 No 3 (2024): May 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i3.5158

Abstract

The performance of the honor staff, supervisory committee, division, staff handling violations, dispute resolution is vital in ensuring effectiveness and fairness in handling violations and dispute resolution within the organization. The main problems in evaluating the performance of supervisory committee personnel include subjectivity in the assessment, and lack of transparency in the appraisal process. Subjectivity can arise due to different perceptions of the party making the assessment, which can lead to unfairness in performance evaluation. Non-transparency in the appraisal process can also raise doubts and distrust of the fairness of the performance appraisal process of supervisory staff. DSS performance appraisal of honorary personnel of the supervisory committee using a combination of LLSW and MABAC is to develop a holistic and effective approach in evaluating the performance of honorary personnel in the supervisory committee. This research is to improve objectivity and fairness in performance appraisal, as well as enable decision makers to make more informed and informed decisions in honorary personnel management in the supervisory committee. The combination of LLSW (Logarithmic Least Squares Weighting) and MABAC (Multi-Attributive Border Approximation Area Comparison) can obtain more detailed and objective recommendations in the performance assessment of honor personnel. This process combines a statistical approach (LLSW) to determine attribute weights and a multi-attribute comparative analysis (MABAC) to obtain a final alternative ranking. The results of ranking 3 alternatives using a combination of LLSW and MABAC methods in assessing the performance of honor workers showed that the results for rank 1 were obtained by Yustina with a final function value of 0.152406, rank 2 was obtained by Andri with a final function value of 0.118662, and rank 3 was obtained by Sudrajat with a final function value of 0.094245.
Kombinasi Logarithmic Percentage Change-Driven Objective Weighting dan Complex Proportional Assessment Dalam Penentuan Supplier Perlengkapan Olahraga Pramuditya, Andri; Darwis, Dedi; Setiawansyah, Setiawansyah
Journal of Computer System and Informatics (JoSYC) Vol 5 No 3 (2024): May 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i3.5160

Abstract

Sports equipment suppliers are suppliers that provide a wide range of equipment, clothing, and accessories needed by athletes, sports teams, and fans to support their activities. One of the main problems in choosing a sports equipment supplier is consistent product quality. Companies that choose sports equipment suppliers need to ensure that the products they buy meet the expected quality standards. In addition, the issue of stock availability and reliable delivery times is also a concern, as the inability to get goods on time can interfere with sports activities or businesses that depend on such equipment. The combination of Logarithmic Percentage Change-Driven Objective Weighting (LOPCOW) and Complex Proportional Assessment (COPRAS) provides a solid and adaptive framework for selecting sports equipment suppliers that best suit existing needs and priorities. This approach helps decision makers to make more informed and targeted decisions, taking into account the overall impact of each supplier's choice in the sporting goods industry. The results of supplier determination recommendations show the results of the assessment of each supplier, based on calculations using a combination of LOPCOW and COPRAS for the first rank with a utility value of 100 obtained by TRB Suppliers. The results of applying the combination of LOPCOW and COPRAS methods in supplier determination can provide more holistic and accurate results, the combination of these two methods can provide a more complete and detailed view of optimal supplier selection, taking into account dynamic changes in relevant criteria and preferences.

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