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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 417 Documents

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Prediction of Library Book Borrowing Patterns Using The Random Forest Algorithm Ega Ranaldi Pebriansyah; Susanti; Rahmiati; Triyani Arita Fitri
Jurnal Riset Informatika Vol. 7 No. 4 (2025): September 2025
Publisher : Kresnamedia Publisher

Libraries play a crucial role in supporting the improvement of public literacy by providing reading materials tailored to users' needs and interests. One of the challenges faced by the Bukit Batu District Public Library is that the collection acquisition analysis process is not yet based on comprehensive borrowing patterns, potentially resulting in inaccurate results. This study aims to predict book borrowing patterns and classify collections into popular and unpopular categories using the Random Forest algorithm. Historical book borrowing data from 2019 to 2024 was used as the primary source in the model training and testing process. Testing was conducted with three data sharing ratios, namely 70:30, 80:20, and 90:10, which resulted in prediction accuracy of 89.19%, 88.69%, and 86.74%, respectively. Based on the analysis results, mathematics books were identified as the most popular collection with 146 borrowings, while social studies books were categorized as unpopular with 122 borrowings. These findings are expected to serve as a reference for libraries in formulating more effective, efficient, and data-based collection management strategies, thereby increasing the relevance and attractiveness of collections for users and supporting the optimization of library services.

IMPLEMENTATION OF THE RAD METHOD ON THE STUDENT REPORT CARD MANAGEMENT WEBSITE AT SMP ALAM AL-KARIM -, Aldo Febrian; Ahmad, Imam; Halim Faturohman, Ryan
Jurnal Riset Informatika Vol. 7 No. 3 (2025): Juni 2025
Publisher : Kresnamedia Publisher

Alam Al-Karim Junior High School (SMP) is a private educational institution located in Pinang Jaya Village, Kemiling District, Bandar Lampung City, Lampung Province. The academic information system implemented at this school is considered suboptimal, as it still relies on manual processes. This situation has led to several issues, particularly in recording teacher and student data, monitoring student attendance, and managing subject assessments. Therefore, the aim of this study is to develop a website-based academic information system utilizing the Rapid Application Development (RAD) method. The goal is to produce an application capable of providing the expected student report card information. The system testing was conducted through a survey using a Google Form questionnaire, which involved 11 respondents. The survey results indicated an average success rate of 14.7% based on response frequency. The implementation of a website-based report card management system has accelerated the presentation of academic information at SMP Alam Al-Karim, as evidenced by a 7.35% agreement frequency among respondents. Furthermore, data management processes have become more efficient, contributing to improved time efficiency and report generation effectiveness.

ON-SR UII: AN ONLINE SELF-REGULATED LEARNING WEB APPLICATION TO ASSIST INDEPENDENT COLLEGE LEARNERS Ahmad R. Pratama; Puji Rahayu; Andri Setiyadi; M. Fachry Azhar; M. Fajri Ashshiddiq
Jurnal Riset Informatika Vol 4 No 4 (2022): Period of September 2022
Publisher : Kresnamedia Publisher

Self-regulated Learning (SRL) is a learning method that puts a strong emphasis on the importance of self-learning skills. Unfortunately, many existing educational technologies employed by colleges and universities continue to place a premium on technical support for the learning process within the classroom that does not provide the same level of support for SRL. This study aims to close this gap by developing the ON-SR UII, a new SRL platform that can assist college students in their quest to become independent learners. Using the design thinking approach, ON-SR UII is developed as a responsive web app that can be accessed by college students through the Internet anywhere at any time at their own pace using any computing device of varying screen sizes. This article describes the process by which ON-SR UII was designed prior to its first prototype being developed, deployed, and evaluated by stakeholders for functionality, usability, and responsiveness. The encouraging results indicate that ON-SR UII has the potential to be widely implemented, allowing for the measurement of its implications in future research.

Design And Development Of A Ticket Booking Application Using Extreme Programming At Serayu Larangan Rifkiansyah, Hanif; Azrino Gustalika*, Muhamad
Jurnal Riset Informatika Vol. 7 No. 4 (2025): September 2025
Publisher : Kresnamedia Publisher

This research was conducted with the aim of developing a web-based tourist ticket booking service application system using the Extreme Programming (XP) development method that is able to facilitate the ticket transaction process both from the side of online buyers and tour managers at the counter. Serayu Larangan Tourism Village, Mrebet District, Purbalingga Regency has promising tourism potential. However, there is still no application that can support the running of the tourism business, such as in the process of selling and recording tickets. Therefore, a system is needed that can facilitate the management of the ticket sales and booking process and data collection of sales reports. This research begins with data collection carried out through the stages of observation, interviews, and literature studies. After the data is collected, system development is carried out using the Extreme Programming (XP) method which consists of four main stages which include planning, design, coding, and testing. From the results of system testing using the Black Box method for ten user features and fifteen admin features showed a 100% success rate. Then the results obtained from the User Acceptence Test (UAT) conducted by ten respondents showed an average percentage of acceptance rate of 87.6%.

Forecasting The Highest Number Of Hotel Visitors In Mojokerto Regency Using Arima Model Gading Putri Diniarti; Rizka Hadiwiyanti; Prasasti Karunia F. A
Jurnal Riset Informatika Vol. 7 No. 4 (2025): September 2025
Publisher : Kresnamedia Publisher

This study aims to forecast the number of hotel visitors in Mojokerto Regency using the Autoregressive Integrated Moving Average (ARIMA) model based on monthly data from 2022 to 2024 provided by the Department of Culture, Youth, Sports, and Tourism (Disbudporapar). The research focuses on three hotels with the highest number of visitors: Hotel Grand Whiz, Puri Indah Hotel, and Hotel Arrayana. The implementation was carried out using Python via the Google Colab platform, involving several analytical stages including data stationarity testing (ADF), differencing, identification of ARIMA parameters (p, d, q) using ACF and PACF plots, automatic model estimation with auto ARIMA, and residual diagnostics. Model performance was evaluated using MSE, RMSE, and MAPE. The results show that ARIMA performed best on Puri Indah Hotel data with a MAPE of 9.65%, indicating high accuracy, while performance was lowest for Hotel Arrayana with a MAPE of 32.31%. Visualization of the predictions revealed that ARIMA works effectively for stable patterns but is less adaptive to volatile trends. The implementation of ARIMA proves to be a useful tool in supporting data-driven decision-making for tourism planning and hotel operational strategy in Mojokerto Regency

COMPARISON OF CLASSIFICATION ALGORITHMS FOR ANALYSIS SENTIMENT OF FORMULA E IMPLEMENTATION IN INDONESIA Fachri Amsury; Nanang Ruhyana; Tati Mardiana
Jurnal Riset Informatika Vol 4 No 3 (2022): Period of June 2022
Publisher : Kresnamedia Publisher

The Formula E racing series has become one of the world's most prestigious competitions. In 2022, Indonesia hosted the famous Formula E race. The event possesses the potential for economic benefits for Indonesia worth 78 million euros through the arrival of 35,000 spectators. Indonesians are enthusiastic about Formula E since it allows their nation to encourage tourists and gain international prominence. However, some people do not support this event. Since they regard that amid the COVID-19 pandemic, it is preferable for the government to focus on people affected by the pandemic rather than support a Formula E event. This study compares the Support Vector Machine and Naive Bayes algorithms in classifying public opinion in the Formula E race. This study gets its information from user comments on social media platforms, especially Twitter. The stages start with text preprocessing and include cleaning, case folding, tokenization, filtering, and stemming. Proceed with weighting using the TF-IDF approach. Data testing uses a confusion matrix to evaluate the classification results by testing accuracy, precision, and recall. Categorizing public opinion using the SVM algorithm has an accuracy of 82 percent, a precision of 97.86 percent, and a recall of 77.90 percent. On the other hand, the accuracy of the Naive Bayes technique is more limited, at 87.54 percent. Society's opinion on Twitter shows positive sentiment towards implementing Formula E.

IMPLEMENTATION OF K-MEANS ALGORITHM FOR CLUSTERING OF COVID-19 VACCINATION IN EAST JAVA WITH ORANGE Michael Sitorus; Cornelia Antonieta Da Costa; Cyntia Larasati
Jurnal Riset Informatika Vol 4 No 3 (2022): Period of June 2022
Publisher : Kresnamedia Publisher

Entering the era of the Covid-19 pandemic, the government has intensively implemented a vaccination program to date. The Covid-19 vaccination program aims to boost the immune system, reduce the risk of transmission, and reduce the severe impact of the virus to achieve group immunity. In its implementation, the Covid-19 vaccination is regulated by the regional government in each province with a policy that requires the Covid-19 vaccination to be vaccinated twice for everyone who meets certain criteria. This study aims to cluster the implementation of vaccination in all areas of East Java province in 2021. The method used in conducting this clustering is the K-Means algorithm. From the results of the study, the results of the division or clustering of regions into three clusters were C1 for the area with the lowest vaccination, namely Pasuruan Regency, C2 for the area with moderate vaccination, namely Kediri City, and C3 for the highest vaccination area, namely Surabaya City. The clustering results obtained based on the K-Means algorithm can be used as input for the East Java Provincial government in evaluating the implementation of the Covid-19 vaccination.

SENTIMENT ANALYSIS OF INTERNET SERVICE PROVIDERS USING NAÏVE BAYES BASED ON PARTICLE SWARM OPTIMIZATION Anugrah Anugrah; Teguh Iman Hermanto; Ismi Kaniawulan
Jurnal Riset Informatika Vol 4 No 4 (2022): Period of September 2022
Publisher : Kresnamedia Publisher

Twitter is a social media application that is widely used. Where as many as 18.45 million users in Indonesia, Twitter users can send and read messages with a maximum of 280 characters displayed. Many opinions and reviews uploaded by users via tweets on social media are experienced in everyday life. Lately, comments about internet service providers in the covid-19 pandemic have been widely reviewed by Twitter users. Problems about internet providers through words often uploaded include internet provider complaints related to network quality, package prices, user satisfaction, and others. This study aims to classify Twitter users' tweets against internet service providers in Indonesia by analyzing the sentiments of 3 internet service providers, namely with the keywords Biznet, first media, and Indihome, using the Naïve Bayes algorithm and optimization with Particle Swarm Optimization. This research is also helpful in helping to become a measure where prospective new users will see the quality of an internet service provider in Indonesia through tweets and then divide the opinion into positive and negative. The results of Biznet's research using Naïve Bayes produce an accuracy of 77.94%, and after optimization, it becomes 81.62%. First media using Naïve Bayes produces 91.39% accuracy, and after optimization, it becomes 92.88%. Indihome using Naïve Bayes produces an accuracy of 85.78%, and after optimization, it becomes 87.48%. It can be concluded that the Naïve Bayes algorithm is a good algorithm for classification, and optimization using Particle Swarm Optimization has an effect on increasing accuracy results

FORECASTING OYSTER MUSHROOM SALES USING THE DOUBLE EXPONENTIAL SMOOTHING METHOD AT KUB RUMAH MUSHROOM BERSAMA Winda Wulandari; Havid Syafwan; Muhammad Ihsan
Jurnal Riset Informatika Vol 4 No 4 (2022): Period of September 2022
Publisher : Kresnamedia Publisher

The amount of oyster mushroom production is often not by consumer orders due to a lack of attention to the mushroom stock in the Mushroom House KUB. The purpose of this study is to apply double exponential smoothing (DES) to predict future sales of oyster mushrooms so that consumer needs are met. This research method uses quantitative methods. The data source comes from data on sales of oyster mushrooms from June 2021-May to 2022. The data is analyzed using double exponential smoothing based on alpha and MAPE values. The results showed that an alpha of 0.6 with a MAPE value of 6.23% was the alpha with the smallest MAPE. This study concluded that the double exponential smoothing method could accurately predict future oyster mushroom sales.

Prototype of an Automatic Height and Weight Measurement System Based on Z-Scores for Determining the Nutritional Status of Toddlers Fayza, Maylaf; Harahap, Robby Kurniawan; Setiawan, Foni Agus
Jurnal Riset Informatika Vol. 7 No. 4 (2025): September 2025
Publisher : Kresnamedia Publisher

Monitoring the nutritional status of children aged 24-60 months is a crucial aspect of ensuring their growth and development. The commonly used manual methods often have limitations in terms of accuracy and efficiency. This study aims to design and develop a prototype of an automated height and weight measurement system based on Z-Score to accurately and efficiently determine the nutritional status of children. The system is developed using the ESP8266 microcontroller as the control center, integrating an RFID module for child identification, an ultrasonic sensor for height measurement, and a load cell for weight measurement. The measurement data is then processed to generate a Z-Score value, which is displayed on an LCD screen. Based on the test results, the system demonstrates a measurement accuracy of 99.60% for children's height and weight. Additionally, the nutritional status assessment aligns with WHO standards. This system is expected to enhance the effectiveness and efficiency of nutritional monitoring for toddlers.

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Tati Mardiana

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Kota banjar,

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