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Journal of Practical Computer Science (JPCS)
Published by Universitas Pelita Bangsa
ISSN : -     EISSN : 28098137     DOI : https://doi.org/10.37366/jpcs
Core Subject : Science, Engineering,
Computer Science & IT Engineering
Journal of Practical Computer Science (JPCS) sebagai media kajian ilmiah dari hasil penelitian, pemikiran dan kajian dan implementasi berkaitan dengan bidang Ilmu Komputer Praktis. Fokus dan ruang lingkup Journal of Practical Computer Science (JPCS) meliputi: - Rekayasa Perangkat Lunak - Kecerdasan Buatan - Data Mining - Machine Learning - Internet of Things - Jaringan Komputer - Keamanan Informasi - Topik kajian lain yang relevan
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 48 Documents
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Perancangan Sistem Prediksi Penyakit pada Tanaman Padi Berbasis Image Processing Menggunakan Algoritma VGG-16 Transfer Learning dan K-Means Segmentation Hidayat, Jose Julian; Setyowati, Cindy; Werdana, Aditya Pratama
Journal of Practical Computer Science Vol. 5 No. 1 (2025): Mei 2025
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jpcs.v5i1.5759

Abstract

Early diagnosis of foliar diseases is essential for improving crop yields as diseases in rice plants can significantly affect agricultural production. By using Transfer Learning techniques on an enhanced VGG-16 model along with K-Means segmentation, this study suggests a deep learning-based approach for rice leaf disease diagnosis. Due to its outstanding ability to extract features from digital photos, VGG-16 was chosen to capture important information about the leaf surface that may indicate the presence of disease. To separate contaminated regions from the background and enable more precise and effective identification, K-Means segmentation was used as a preprocessing step. The dataset used in this experiment contains a wide variety of photos of different categories of diseases on rice plants. According to the experimental data, this approach can identify the type of disease on the leaves very accurately the accuracy can exceed 90%. By concentrating on key regions of the image, K-Means improves the detection performance. When compared to conventional methods, these results show how this combination strategy can improve the accuracy of rice leaf disease diagnosis. The use of this system is expected to help agronomists and farmers to monitor plant health efficiently, thereby increasing agricultural yields. In this study, the VGG-16 method and K-Means segmentation were combined to create a rarely used image-based automatic diagnosis system simultaneously on rice plants. This method has been shown to have higher accuracy than previous methods.
Analisis Blackbox Testing dan User Acceptance Testing terhadap Sistem Informasi Posyandu Dondang Fahrullah, Fahrullah; Haerullah, Haerullah; Ridhawani, Achmad
Journal of Practical Computer Science Vol. 5 No. 1 (2025): Mei 2025
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jpcs.v5i1.5780

Abstract

Posyandu (Integrated Service Post) is one form of Community-Based Health Effort that plays an important role in basic community health services. Information processing activities at Posyandu Dondang are still done manually (written by hand), so it is necessary to develop a website-based Posyandu information system to make it easier for Posyandu cadres to manage data, make reports, and provide information to the community more effectively and efficiently. This study aims to test the website-based Posyandu Dondang information system using the User Acceptance Testing (UAT) method. This system was developed to facilitate data management and services at Posyandu with four main user groups: admins, parents, midwives, and officers. Testing was carried out using the UAT method involving 21 respondents and using a Likert scale to measure the level of user acceptance. Based on the results of the analysis, the results of the system functionality test showed that most of the features were running well, although there were still some features that needed improvement such as the profile menu, settings, and activities, while the User Acceptance Testing (UAT) / user acceptance rate was 92.06%, which indicates that the system is in the "Very Good" category
Perancangan UI/UX Pada Website Tinggal Order Dengan Figma Menggunakan Metode User Centered Design Fahrullah, Haerullah; Fahrullah, Fahrullah; Rivaldy, Tico
Journal of Practical Computer Science Vol. 5 No. 1 (2025): Mei 2025
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jpcs.v5i1.5805

Abstract

This research aims to analyse the User Interface (UI) and User Experience (UX) of the website profile shop ‘Tinggal Order’ using the User-Centered Design (UCD) method. UCD is a design approach that places the user at the centre of the entire design process, with a primary focus on user needs, preferences, and involvement. This method is used to ensure that the resulting website not only fulfils business needs but also provides an optimal user experience. This research involves the stages of identifying user needs, prototyping, and UI/UX evaluation through testing with end users. The results showed that the application of UCD was able to improve the ease of use (usability), user satisfaction, and interaction effectiveness on the ‘Tinggal Order’ website. The usability results obtained an average of 84.886, with the grade A category. This figure can be said to be very good, which means that the design made can be accepted by potential users. While the resulting prototype can help provide information to the general public about news and information about the ‘Tinggal Order’ store.
Dampak Pemanfaatan Teknologi Business Intelligence untuk Optimalisasi Strategi Penjualan dengan Metode OLAP di Warmindo X Setyawan, Adhita Arif; Darmawan, Eki Dudi; Adji, Widwi Handari
Journal of Practical Computer Science Vol. 5 No. 1 (2025): Mei 2025
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jpcs.v5i1.5816

Abstract

This research was conducted simulatively on an MSME business called Warmindo X which was used as a case study to test the application of OLAP in a Business Intelligence system. The purpose of this research is to develop a data warehouse and information dashboard system based on Tableau technology, by utilizing the utilizing the OLAP method to support strategic decision making and increase sales effectiveness at Warmindo X. improve sales effectiveness at Warmindo X. BI implementation implementation is carried out using Pentaho Data Integration for the ETL (Extract, Transform, Load) and Tableau for dashboard visualization. The ETL process is used to collect, process, and integrate sales data obtained from the Point of Sales (POS) system. obtained from the Point of Sales (POS) system in Excel format. The data is data is then processed into the data warehouse using a star schema that makes it easier to process the data. (star schema) which facilitates multidimensional analysis. Through the OLAP method, sales data sales data is analyzed based on various dimensions such as product, time, and sales. The results of data visualization in the form of dashboards allow Warmindo to quickly monitor sales performance and make more effective decisions. decisions more effectively. The dashboard provides information on best-selling products, product categories, and sales trends over time. product categories, and sales trends over time. The results showed that with the implementation of Tableau and OLAP, Warmindo X can improve operational efficiency, accelerate the analysis process, and support decision making to strengthen sales strategy and competitiveness in business
Penerapan Lexicon Based Untuk Analisis Sentimen pada Game PUBG dengan Ekstraksi Fitur TF-IDF Anisa, Nor
Journal of Practical Computer Science Vol. 5 No. 1 (2025): Mei 2025
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jpcs.v5i1.5826

Abstract

This study conducts sentiment analysis on user reviews of PUBG (PlayerUnknown's Battlegrounds) to understand players' perceptions of their gaming experience. The main issue addressed is the need for a deeper understanding of player satisfaction and dissatisfaction through available review data. The objective of this research is to identify sentiment tendencies—positive, neutral, or negative—and the specific aspects of the game that receive the most user feedback. The methodology combines a lexicon-based sentiment analysis approach with Term Frequency-Inverse Document Frequency (TF-IDF) feature extraction. The lexicon-based technique is used to classify words with positive or negative connotations, while TF-IDF highlights the most influential terms in the user review corpus. Results from various testing scenarios show that this combined method improves sentiment classification accuracy. The analysis reveals that the majority of reviews express positive sentiment, with a smaller portion being neutral or negative. Furthermore, the approach successfully identifies the most praised and criticized features of the game. These findings offer valuable insights for game developers to evaluate and improve game elements that directly impact player satisfaction and retention
Alpha Beta Testing pada Media Pembelajaran Dasar Agama di Lingkungan Tempat Pembelajaran Al-Quran Khasanah, Fata Nidaul; Prasojo, Prasojo; Untari, Dhian Tyas; Setiyadi, Didik
Journal of Practical Computer Science Vol. 5 No. 1 (2025): Mei 2025
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jpcs.v5i1.5909

Abstract

The rapid development of technology today has significantly influenced educational processes, both formal and non-formal. It has also impacted learning materials and the methods used to deliver them during the teaching and learning process. However, not all educational institutions are able to take advantage of this technological advancement—one example is the Qur'anic Education Center (Tempat Pendidikan Al-Qur’an, or TPA). TPA is a non-formal educational institution in which the learning process predominantly relies on traditional lecture-based methods delivered by instructors. This often results in low student attention and limited understanding of the learning material. To address this issue, an interactive learning media application was designed to support the introduction of basic Islamic religious knowledge. The aim of this research is to test the functionality of the developed learning media application in order to minimize anomalies and ensure usability. One of the suitable software testing approaches used in this context is user acceptance testing. The testing methods implemented in this study include alpha testing and beta testing. The alpha testing results indicate that the application functions as expected for each tested case scenario. Furthermore, the beta testing results showed an average survey score of 82% across the criteria of usability, ease of learning, ease of use, and user satisfaction
Analisis RIsiko Keamanan Teknologi Infromasi Pada Instansi Pemerintahan Purbalingga Aprilia, Kharisma; Maghfira, Rahajeng Sasi; Aji, Ranggi Praharaningtyas; Saputra, Dhanar Intan Surya
Journal of Practical Computer Science Vol. 5 No. 2 (2025): November 2025
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jpcs.v5i2.5960

Abstract

Digital transformation within the governmental sector has accelerated the wide use of information systems for the support of public services and administrative efficiency. However, this development has also introduced serious challenges of information security that are often overlooked by local governments. The purpose of this research is to identify and assess the risk of IT security at Kabupaten Purbalingga’s Department of Communication and Information . The research is to be conducted using the qualitative descriptive approach based on the OCTAVE-S method. Data collection will involve direct observation of IT infrastructure and a thorough interview with the technical personnel responsible for information systems. From the analysis conducted, it can be concluded that DINKOMINFO has serious threats such as defacement attacks, DDoS, and internal vulnerabilities due to the use of weak credentials. Without a strong security policy, these weaknesses will only become more widespread, not much different from the current resource limitations. Therefore, the best solution that can be implemented in the long term is the implementation of a Security Operation Center or SOC, adaptive security policies, and cybersecurity awareness and training. Keyword: Information Security, OCTAVE-S, Local Government, DINKOMINFO, Cyber ​​Risk.
Human Development Index Classification in Central Java Using the K-Nearest Neighbors Method for Data-Driven Policy Making Vulandari, Retno Tri; Harjanto, Sri
Journal of Practical Computer Science Vol. 5 No. 2 (2025): November 2025
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jpcs.v5i2.5996

Abstract

Human development in Central Java continues to show positive progress, as reflected in the consistent increase of the Human Development Index (HDI) across the province. The HDI serves as a key indicator for assessing the success of initiatives aimed at improving the overall quality of life. It measures how well residents are able to access the benefits of development, including long and healthy lives, education, knowledge, and a decent standard of living. The HDI is influenced by four primary components: life expectancy, expected years of schooling, mean years of schooling, and per capita expenditure. Currently, the Central Bureau of Statistics determines HDI values for each regency and city in Central Java using a specific calculation formula. In this study, we aim to classify these regions into three categories based on their HDI levels: very high, high, and moderate estimate areas. To perform this classification, we applied the K-Nearest Neighbors (KNN) algorithm—an effective, non-parametric method that classifies data points based on the majority class among their nearest neighbors in the feature space. KNN is well-suited for classification tasks involving complex, real-world data, offering both accuracy and interpretability. The classification of the 2024 HDI data using KNN resulted in three distinct groups: Cluster 1 (moderate estimate) includes 18 regions: Cilacap, Banyumas, Purbalingga, Banjarnegara, Kebumen, Wonosobo, Magelang, Wonogiri, Grobogan, Blora, Rembang, Temanggung, Kendal, Batang, Pekalongan, Pemalang, Tegal, and Brebes. Cluster 2 (high estimate) consists of 13 regions: Purworejo, Boyolali, Klaten, Sukoharjo, Karanganyar, Sragen, Pati, Kudus, Jepara, Demak, Semarang Regency, Kota Pekalongan, and Kota Tegal. Cluster 3 (very high estimate) comprises 4 urban areas: Kota Magelang, Kota Surakarta, Kota Salatiga, and Kota Semarang. This classification provides valuable insights into regional development disparities and can support evidence-based planning and policy-making.
Optimalisasi Keterlibatan Konsumen melalui Augmented Reality dalam Pemasaran Digital: Kasus Aplikasi IKEA Place Setyawan, Adhita Arif; Amanda, Fadila; A.S, Muhammad Prakarsa
Journal of Practical Computer Science Vol. 4 No. 2 (2024): November 2024
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jpcs.v4i2.6069

Abstract

The development of digital technology has brought significant changes in the way companies build relationships with their consumers. One innovation that is increasingly popular in the world of digital marketing is the use of Augmented Reality (AR) technology. This study aims to analyze how AR can be used to optimize customer engagement through interactive and immersive experiences. This study uses a descriptive qualitative approach with literature study methods, observation of IKEA Place app features, and semi-structured interviews with a number of active app users. IKEA Place was chosen as a case study because it is one of the pioneers in the application of AR in marketing furniture products. The results showed that AR technology in the application was able to increase consumer confidence in the product, facilitate visualization before purchase, and create a fun and personalized experience. In addition, the emotional engagement built through AR interactions also encourages long-term consumer loyalty. This finding indicates that AR is not only a visual aid, but also an effective experiential marketing strategy. The contribution of this research lies in the focus of analyzing consumer emotional engagement through AR interaction, which has not been widely reviewed in previous studies. The main difference from other studies is the specific selection of the IKEA Place case study, as well as the data triangulation approach (literature, observation, and interviews) to describe the user experience holistically. This research not only highlights the technology, but emphasizes the role of AR in building long-term relationships with consumers through meaningful and personalized experiences. This research provides recommendations for digital businesses to adopt AR to create added value and competitive differentiation in the digital economy era.
Penerapan Model Regresi Linear Untuk Memprediksi Overall Rating Kiper (GK) Dalam EA FC 25 Julianto, Faiza Muhammad; Tawakal, Iqbal; Mu'minin, Amirul; Anam, Misbakhul
Journal of Practical Computer Science Vol. 4 No. 2 (2024): November 2024
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jpcs.v4i2.6070

Abstract

Player performance prediction in digital soccer games is a growing research topic, especially in supporting data-driven evaluation. In this study, the Overall Rating (OVR) of Goalkeeper (GK) players in EA FC 25 game is predicted using Linear Regression model. The main objective of this study is to evaluate the model's ability to predict OVR based on goalkeeper-specific attributes. The methodology used includes data collection, pre-processing, feature selection, model building, and model performance evaluation using Root Mean Squared Error (RMSE), R-squared (R²), and Mean Absolute Error (MAE) metrics. The evaluation results show that the model has an R-squared value of 0.99, RMSE of 0.72 and MAE of 0.57, indicating that the model is able to provide predictions with low error and high accuracy. These findings suggest that linear regression is effective in modeling the relationship between goalkeeper attributes and Overall Rating scores in the context of EA FC 25 game

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