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Jurnal Riset Informatika

jri
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Published by KresnaMedia Publisher

ISSN : 26561743 EISSN : 26561735 DOI : -

Core Subject : Science,

Computer Science & IT

Jurnal Riset Informatika, merupakan Jurnal yang diterbitkan oleh Kresnamedia Publisher. Jurnal Riset Informatika, berawal diperuntukan menampung paper-paper ilmiah yang dibuat oleh peneliti dan dosen-dosen program studi Sistem Informasi dan Teknik Informatika.

Arjuna Subject : -

Articles 432 Documents

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Hybrid Neural Network Approach for Tea Leaf Disease Detection Using Pelican and Mayfly Optimization Algorithms Al-Karawi, Saja Bilal Hafedh; Koyuncu, Hakan
Jurnal Riset Informatika Vol. 6 No. 2 (2024): March 2024
Publisher : Kresnamedia Publisher

This study addresses the problem of plant diseases and the difficulty of detecting them, and it presents a unique technique for the automatic detection of tea leaf diseases by combining neural networks and optimization techniques. Our research uses a curated database of tea plant leaf photographs that includes healthy and diseased specimens. The neural network (CNN) is trained and fine-tuned using optimization algorithms. To increase disease identification accuracy, we used a hybrid novel optimization algorithm called (POA-MA) which is Pelican Optimization Algorithm (POA), and Mayfly Optimization Algorithm (MA) for feature selection, followed by classification with Support Vector Machine (SVM). The suggested mechanism performance is evaluated using accuracy, MSE, F-score, recall, and sensitivity measures. The suggested CNN-POAMA hybrid model yielded 94.5%, 0.035, 0.91, 0.93, and 0.92, respectively. This study advances precision agriculture by establishing a strong framework for automated detection, allowing for early intervention, and eventually enhancing tea crop health.

IDENTIFICATION OF WATER TURBIDITY WITH TURBIDITY SENSOR BASED ON ARDUINO Hafdiarsya Saiyar; Mohammad Noviansyah
Jurnal Riset Informatika Vol 3 No 4 (2021): Period of September 2021
Publisher : Kresnamedia Publisher

Water is an important need for all living things, especially humans. Humans need water with quality that meets the physical, microbiological, chemical, and radiological requirements contained in the mandatory and additional parameters. The selection of these parameters is very important to meet the requirements of good water, namely tasteless, odorless, and colorless. Meanwhile, there are three parameters used for water identification, namely pH parameters, turbidity levels, and temperature parameters. From these problems, the authors examine the detection of water quality, especially water turbidity. The author tries to make a tool that can detect the level of turbidity of water with a turbidity sensor as a detector of the level of turbidity in the water, Arduino Uno as a processor for the data results that have been detected, and a 16x2 LCD as a display of turbidity level measurement results in the form of turbidity values and descriptions of the water being tested. The measurement range that can be detected by this tool is from 0 – 3000 NTU. The research method used is direct observation of the selected object, namely the author's home environment, and conducting library research related to the Arduino microcontroller. The purpose of this study was to determine and detect the level of water quality in the community. As one of the tools or alternatives for the community to find out or detect the level of water quality early.

COMPARATION OF DECISION TREE MODEL AND SUPPORT VERCTOR MACHINE IN SENTIMENT ANALYSIS OF REVIEW DATASET SAMSUNG SSD 850 EVO AT NEW EGG SHOP Muhammad Fahmi Julianto; Yesni Malau; Wahyutama Fitri Hidayat; Wawan Nugroho; Fintri Indriyani
Jurnal Riset Informatika Vol 3 No 4 (2021): Period of September 2021
Publisher : Kresnamedia Publisher

The development of information technology is currently growing very rapidly, including the impact on the hardware used. This can be exemplified in the use of hard drives that are starting to switch to SSDs. The process of selecting an SSD product to be used cannot be separated from the sources of information found on the internet. Through the internet, every user can provide reviews, both positive and negative reviews. With the many reviews regarding the review of the Samsung 850 Evo SSD on the NewEgg Store, the author uses it to be processed into information, which will have new knowledge. Based on that, the author makes research, in the form of opinion classification by analyzing sentiment through a text mining approach. In this study, two classification models were used, namely Decision Tree and Support Vector Machine. The results of this study are in the form of a comparison of the 2 models used based on the accuracy and AUC values. Based on research, the Support Vector Machine model is better than the Decision Tree model. This conclusion can be proven by the accuracy value of the Support Vector Machine model resulting in a value of 0.87 or 87% while the accuracy value of the Decision Tree model produces a value of 0.82 or 82%. In addition, the AUC value of the Support Vector Machine model produces a value of 0.87 and the Decision Tree mode produces a value of 0.82 or it can be said that the AUC value of the Support Vector Machine model is better than the Decision Tree model.

ANDROID SALES PREDICTION DURING PANDEMIC USING NAÏVE BAYES AND K-NN METHODS BASED ON PARTICLE SWARM OPTIMIZATION Endang Sri Palupi
Jurnal Riset Informatika Vol 4 No 1 (2021): Period of December 2021
Publisher : Kresnamedia Publisher

During the pandemic, most schools, campuses, and places of education conducted online teaching and learning activities. Many teaching and learning activities are carried out using the Zoom, Google, WebEx, or Microsoft Teams applications. All of this can be done through a PC or laptop, or using a cellphone, so the need for PCs and cellphones increases, both new and used goods. Even though during the pandemic the economic situation was declining, many companies suffered losses, resulting in a reduction in employees and causing a high unemployment rate, the need for Android phones remains high. In addition to online distance learning facilities, Android phones can also be used for online sales through e-commerce, market places, social media, and other digital platforms. Currently, Android phones have many choices and according to the funds we have, with various brands and specifications. Many brands issue android cellphone products with pretty good specifications and affordable prices, so that even though purchasing power has decreased due to the pandemic, sales of android cellphones are still high. In this study, the author predicts the highest sales of android cellphones using the Naïve Bayes method and the K-Nearest Neighbor method based on Particle Swarm Optimization accuracy of 81.33%.

Application of Social Network Analysis for Comparison and Ranking of Internet Service Providers Setiadi, Tedy; Mukharom, Gilang; Suhendra, Beni; Bima, Syauqi
Jurnal Riset Informatika Vol. 6 No. 2 (2024): March 2024
Publisher : Kresnamedia Publisher

In this digital era, the Internet has become a basic necessity in life. This has had a significant impact on the growth of internet service provider (ISP) companies in Indonesia. Comparison and ranking of ISPs is needed to make it easier for users to choose services according to their needs as well as to encourage healthy competition between ISPs in improving their services. The problem is ranking ISPs using conventional methods (surveys) to obtain primary data is expensive and takes a long time. On the other hand, Social Network Analysis (SNA) is a method that has been widely used to understand customer desires by extracting information from social media. This information is in the form of User Generated Content (UGC), namely track records left by customers on social media. This research aims to measure the ISP rankings of Indihome, Biznet and FirstMedia using UGC data. The research method used is to collect consumer tweet data rapidly, carry out preprocessing to eliminate irrelevant data and apply SNA, including network structure analysis in the form of visualization and network property analysis with the Gephi application, as well as network content analysis in the form of sentiment analysis and WordCloud analysis. The number of dominant network properties and sentiment analysis calculates ISP ranking. Apart from that, the results of this SNA are in the form of recommendations for ISPs to improve services to customers.

IMPLEMENTATION OF THE SIMPLE ADDITIVE WEIGHTING METHOD FOR EMPLOYEE PERFORMANCE ASSESSMENT Siti Aisyah
Jurnal Riset Informatika Vol 3 No 4 (2021): Period of September 2021
Publisher : Kresnamedia Publisher

In the process of evaluating employee performance, the company has established standard operating procedures. Of the many standards, it is difficult for management to give weight to each standard. Therefore, a decision-making system is needed to improve company performance and productivity. Human resources must be able to improve employee performance. Professional knowledge or ability. The current appraisal problem, including the employee performance appraisal process, is still using the traditional and not yet accurate method. The research was conducted using the simple additive weighting (SAW) method. The results of this study indicate that by using the SAW method, management is more likely to pay attention to employee performance evaluation, and is more organized and efficient in evaluating employee performance.

SENTIMENT ANALYSIS OF COVID-19 VACCINATION POSTS ON FACEBOOK IN INDONESIA WITH CROWDTANGLE Adita Rianto; Ahmad Rafie Pratama
Jurnal Riset Informatika Vol 3 No 4 (2021): Period of September 2021
Publisher : Kresnamedia Publisher

COVID-19 was declared a pandemic by the World Health Organization (WHO) in early 2020. The Indonesian government has taken steps to stop COVID-19 from spreading, one of which is vaccination. However, not everyone thinks vaccination is a good idea. Like in other countries, Indonesian people responded in different ways to COVID-19 vaccination posts on social media, be it from government officials or news portals. Public responses can be used to help the government make a better vaccination strategy to end the pandemic in Indonesia. Using the lexicon method in determining the sentiment in COVID-19 vaccination posts on Facebook, this research found that unlike news portals that tended to post a more balanced content (36% positive, 20% negative, and 44% neutral out of 23,623 posts, min score = -19, max score = 24, mean = 0.25, SD = 1.43), government accounts posted much more positive content, both in quality (min score = -15, max score = 40, mean score = 4.16, SD = 6.76 ) and quantity (69% positive) than they did the neutral (15%) and the negative content (16%) out of 723 posts. Subsequent analysis with Two-Way ANOVA tests discovered that COVID-19 vaccination posts by the news portals elicited more varied reactions from the public than government accounts that tended to elicit mostly positive reactions. Also, both the content sentiment of COVID-19 vaccination posts in Indonesia and the account types making those posts, as well as their interaction terms do have an impact on how the public responds to them.

DEVELOPING BLENDED LEARNING APPLICATION UTILIZING ARTICULATE STORY LINE 3.0 INTEGRATED WITH ANDROID BASED SYSTEM Efrizal Siregar; Nurianti Sitorus; Juwariah Juwariah
Jurnal Riset Informatika Vol 3 No 4 (2021): Period of September 2021
Publisher : Kresnamedia Publisher

The development of science and technology in the digital era of Four Point Zero has a great impact on the world of education. One of them is by utilizing e-learning applications in the learning process. However, the technology used in this learning is too dependent on the internet network. Therefore, the research aims to develop a media in the form of an Android-based e-learning application that can be used online and offline. This study uses a research and development design using the ADDIE model. To create and test these products, in this case an Android-based e-learning application. Procedure This research was carried out through 6 stages, namely needs analysis, application design stage, development, data analysis, evaluation, and development of a final product that is ready to be used. From the results of the material validation test and the feasibility of the developed application media, it is very feasible to use.

PUBLIC’S SENTIMENT ANALYSIS ON SHOPEE-FOOD SERVICE USING LEXICON-BASED AND SUPPORT VECTOR MACHINE Shafira Shalehanny; Agung Triayudi; Endah Tri Esti Handayani
Jurnal Riset Informatika Vol 4 No 1 (2021): Period of December 2021
Publisher : Kresnamedia Publisher

Technology field following how era keep evolving. Social media already on everyone’s daily life and being a place for writing their opinion, either review or response for product and service that already being used. Twitter are one of popular social media on Indonesia, according to Statista data it reach 17.55 million users. For online business sector, knowing sentiment score are really important to stepping up their business. The use of machine learning, NLP (Natural Processing Language), and text mining for knowing the real meaning of opinion words given by customer called sentiment analysis. Two methods are using for data testing, the first is Lexicon Based and the second is Support Vector Machine (SVM). Data source that used for sentiment analyst are from keyword ‘ShopeeFood’ and ‘syopifud’. The result of analysis giving accuracy score 87%, precision score 81%, recall score 75%, and f1-score 78%.

DESIGN OF WEB-BASED UYU STORE ATTENDANCE INFORMATION SYSTEM USING COLORING METHOD Christy Octavius; Deny Hidayatullah
Jurnal Riset Informatika Vol 4 No 1 (2021): Period of December 2021
Publisher : Kresnamedia Publisher

Attendance in the world of work is sometimes still done manually. At the Uyu shop, there are still problems that occur in recording and making attendance reports manually, such as mistakes in biodata, forgetting to record the date. Because the Uyu store still doesn't use a computerized employee or staff absence information system in managing data, so the information that can be processed is quite long and storage is not guaranteed safe. The purpose of this researcher is to create an information system that can manage attendance data for employees who work at the computerized Uyu Store and also implement a coloring method on attendance reports that generate reports based on the attendance coloring method according to employee attendance hours that are easy to understand. This method uses the coloring method as a solution to solving problems that can be solved in the greedy method, namely the color problem and the waterfall model as a system development process that uses UML design. The result of this research is that the system can operate attendance data collection as well as report employee data more efficiently and integrated.

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Contact Name
Tati Mardiana

Contact Email
jurnal.jri@kresnamediapublisher.com

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Journal Mail Official
jurnal.jri@kresnamediapublisher.com

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Location
Kota banjar,

Jawa barat

INDONESIA