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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.

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Articles 19 Documents

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Search results for , issue "Vol. 7 No. 4 (2025): September 2025" : 19 Documents clear

Social Network and Sentiment Analysis for Enhancing Social CRM in Indonesian Educational Technology Platforms Khairunnisa, Rifaa; Siregar*, Johannes Hamonangan
Jurnal Riset Informatika Vol. 7 No. 4 (2025): September 2025
Publisher : Kresnamedia Publisher

The rapid advancement of digital technology has significantly transformed the education sector, including in Indonesia. According to the 2024 report by Badan Pusat Statistik (BPS), e-learning is among the primary reasons Indonesians access the internet. This trend has positioned educational technology (EdTech) platforms such as Ruangguru, Pahamify, and Zenius as key players in the country’s e-learning ecosystem. Simultaneously, social media has become a space where users actively express their experiences regarding the services they use. This study aims to examine user interaction dynamics and public sentiment toward these three EdTech platforms through an integrated approach combining Social Network Analysis (SNA) and Lexicon-Based Sentiment Analysis. Data were collected from platform X and preprocessed for analysis. Network analysis used Gephi to evaluate structural properties and centrality measures, while sentiment analysis used a combination of the InSet lexicon and user-generated vocabulary. To further capture discussion themes, topic modeling using the BERTopic algorithm was also applied to categorize dominant topics from user conversations. The results show that each platform exhibits different social network characteristics. Zenius demonstrates efficient information flow, Ruangguru displays tightly connected user interactions, and Pahamify presents a more dispersed structure. Overall, the sentiment analysis showed that Ruangguru and Zenius had relatively higher proportions of positive sentiment, with 44.6% and 41.4%, respectively. These findings highlight how integrating SNA and sentiment analysis can form a strong foundation for developing Social CRM strategies to enhance the quality of digital education services in Indonesia.

Factor Analysis of E-Learning Acceptance in SMK Sore Tulungagung Using Technology Acceptance Model (TAM) Indah, Rhohmah; Maya Safitri, Eristya; Puspa Rinjeni, Tri
Jurnal Riset Informatika Vol. 7 No. 4 (2025): September 2025
Publisher : Kresnamedia Publisher

Although the use of E-Learning has been expanded as a modern learning solution, its implementation at SMK SORE Tulungagung still faces obstacles such as low student participation, difficulty in accessing E-Learning features, and delays in submitting assignments. This indicates that there are obstacles in the acceptance of learning technology by students. This study aims to analyze the factors that influence the acceptance of E-Learning using the Technology Acceptance Model (TAM) framework with the main variables: Perceived Usefulness (PU), Perceived Ease of Use (PEOU), Attitude Toward Using (ATU), Behavioral Intention to Use (BIU), and Actual Use (AU). The method used is quantitative with a predictive approach, data was obtained by distributing questionnaires to students majoring in Computer and Network Engineering, Data analysis was carried out using validity, reliability, and structural modeling (SEM-PLS) tests. The results showed that PU and PEOU significantly influenced students' attitudes and intentions in using E-Learning. In addition, BIU contributed to the use of the actual system and external factors such as complexity and voluntariness were also analyzed to determine the indirect effect on technology acceptance.

Active Learning Query by Committee Labeling Method to Increase Accuracy and Efficiency of Sentiment Analysis Classification Dipa Anasta Iskandar; R. Mohamad Atok
Jurnal Riset Informatika Vol. 7 No. 4 (2025): September 2025
Publisher : Kresnamedia Publisher

This study proposes the Query by Committee (QBC) labeling method to improve the accuracy of classification models—specifically XLM-RoBERTa—and to increase labeling efficiency compared to manual, supervised labeling, which generally requires more time and resources. The dataset consists of unannotated healthcare-industry application reviews scraped from Google Play. Six distinct labeling strategies were applied as input for fine-tuning XLM-RoBERTa models under identical hyperparameter settings. The six labeling approaches were evaluated namely Rating-based labeling, Lexicon-based labeling, QBC for Rating-Vader labeling, QBC for Rating-Pseudo labeling, QBC for Vader-Pseudo labeling, and QBC triplet for Rating-Pseudo-Vader labeling. Each labeled dataset was split using stratified random sampling, and class weights were set to “auto” during training to address label imbalance. All models were subsequently tested on the IndoNLU SmSA test dataset, with performance compared in terms of accuracy, precision, recall, and F1-score. Results indicate that the triplet QBC approach (combining Rating, VADER, and Pseudo labeling) outperformed all other methods, achieving an accuracy of 91.4%, a precision of 91.28%, a recall of 91.4%, and an F1-score of 91.21%. These findings demonstrate that the QBC labeling method can serve as an effective and efficient alternative to manual annotation for similar classification tasks

Integration of OCR Technology with ETL Processes for Automating Data Pipeline of Financial Disbursement Documents at BPS Sukabumi Regency Muhammad Raihan Izharul Haq; Gina Purnama Insany; Somantri
Jurnal Riset Informatika Vol. 7 No. 4 (2025): September 2025
Publisher : Kresnamedia Publisher

In the digital era, managing archival data poses challenges for many institutions, including Badan Pusat Statistik (BPS) of Sukabumi Regency, especially when dealing with unstructured PDF documents. This study develops a data pipeline by effectively integrating Optical Character Recognition (OCR) technology with Extract, Transform, Load (ETL) processes. Unstructured data from financial disbursement documents, such as SPM and SP2D, were automatically extracted with high accuracy, achieving an average of 98.52% for SPM using a combination of OCR and PDFPlumber, and 100% for SP2D extracted using PDFPlumber. Extraction results were stored in a data warehouse, then transformed using Apache Spark and loaded into data marts. ETL process was automated using Apache Airflow, which operated reliably according to dependencies. The processed data were presented through an interactive Looker Studio dashboard in real-time, supporting efficient archive management and more informed decision-making. This study not only provides a solution to existing archival management problems but also opens opportunities for further development in the application of big data technologies and business process automation in public sector.

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.

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

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.

Sales Analysis Using Apriori Algorithm Roja' Putri Cintani; Fitriati, Desti
Jurnal Riset Informatika Vol. 7 No. 4 (2025): September 2025
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v7i4.351

PT JR Pangan Semesta is a company that produces fast food in the form of Donuts and Sweet Bread under the Deroti brand. The sales and promotion methods that have been carried out have weaknesses because the company has difficulty ensuring the right amount of bread production, so there is often excess or lack of stock. In addition, the promotional strategy used has not included the concept of bundling, so the maximum promotional potential has not been fully explored. To overcome these problems, the use of data mining methods is proposed, one of which is the Apriori Association Rule algorithm. Apriori algorithm is used to find consistent sales patterns and find strong product relationships by analyzing sales transaction data. In this study, sales patterns were analyzed at PT JR Pangan Semesta with a minimum support value of 16% and a minimum confidence value of 60%. The analysis results show that there are three products that are often purchased together by consumers, namely Fried Bread, Deroti Donuts, and Eco Donuts. The three products form one valid association rule, so that the rule can be used as a reference for developing efficient production methods for bread and donuts and implementing sales strategies in the form of bundling products to maximize profits.

Classification Of Kredivo Application Reviews Based On User Satisfaction Aspects With The SVM Method Hasanah, Haprilianh; Tukino; Shofa Shofia Hilabi
Jurnal Riset Informatika Vol. 7 No. 4 (2025): September 2025
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v7i4.390

The development of the fintech sector in Indonesia has encouraged the creation of various digital payment applications, one of which is Kredivo which provides instant credit and installments without a credit card. In this study, we analyzed and classified Kredivo application user reviews based on satisfaction attributes using the Support Vector Machine (SVM) method. Review data was collected from the Google Play Store and pre-processed using text preprocessing, InSet dictionary-based sentiment tagging, TF-IDF feature extraction, and training-test data splitting in an 80:20 ratio. Based on the analysis, most Kredivo user reviews were observed to have positive sentiment of 38.70%, negative sentiment of 26.90%, and neutral of 34.40%. The SVM model developed for Kredivo review sentiment labeling works with positive, negative, and neutral. Word cloud visualization recognizes the most important words with positive tones such as "mantap", "baik", "cepat", "mudah", and "transaksi", as well as the most important words with negative tones such as "hapus", "bayar", "bulan", "meminjam", and "tidak". The results of this study can be feedback for Kredivo developers and other fintech platforms to improve services based on user needs and demands, as well as strengthen business strategies according to customer satisfaction levels.

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Tati Mardiana

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jurnal.jri@kresnamediapublisher.com

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jurnal.jri@kresnamediapublisher.com

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Kota banjar,

Jawa barat

INDONESIA