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Jurnal Informatika: Jurnal Pengembangan IT
Published by Politeknik Harapan Bersama Tegal
ISSN : 24775126     EISSN : 25489356     DOI : https://doi.org/10.30591
Core Subject : Science,
Computer Science & IT
The scope encompasses the Informatics Engineering, Computer Engineering and information Systems., but not limited to, the following scope: 1. Information Systems Information management e-Government E-business and e-Commerce Spatial Information Systems Geographical Information Systems IT Governance and Audits IT Service Management IT Project Management Information System Development Research Methods of Information Systems Software Quality Assurance 2. Computer Engineering Intelligent Systems Network Protocol and Management Robotic Computer Security Information Security and Privacy Information Forensics Network Security Protection Systems 3. Informatics Engineering Software Engineering Soft Computing Data Mining Information Retrieval Multimedia Technology Mobile Computing Artificial Intelligence Games Programming Computer Vision Image Processing, Embedded System Augmented/ Virtual Reality Image Processing Speech Recognition
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 17 Documents
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Search results for , issue "Vol 10, No 4 (2025)" : 17 Documents clear
Sistem Presensi Otomatis Menggunakan Pengenalan Wajah Berbasis Deep Learning dan Real-Time Database Nugraha, I Putu Elba Duta; Sukadarmika, Gede
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 4 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i4.8792

Abstract

The attendance system is a crucial component in the operations of any organization. However, most existing attendance systems still require significant time or manual intervention from users. This study aims to develop a deep learning-based face recognition application with a real-time database to record attendance automatically. This approach is expected to make the attendance process more accurate, faster, and more convenient compared to traditional attendance methods. The study employs a quantitative method through primary data analysis from laboratory testing using dummy data. This testing aims to measure the accuracy of the face recognition system in automatically recording attendance. A face recognition application prototype has been successfully developed with real-time database integration using the Python programming language. The test results show that the application can recognize all faces in the database with a very high accuracy level. The system performance metrics indicate an accuracy of 99.1%, precision of 98.7%, recall of 98.7%, and F1-score of 98.7%. Additionally, the model has been implemented on an NVIDIA Jetson Nano mini-processor, demonstrating efficient operation on low-power hardware and real-time face recognition with optimal processing speed.
Perbandingan Cosine Similarity dan Weighted Jaccard Similarity dalam Pengembangan Mesin Pencari Perpustakaan Digital Pamput, Jessicha Putrianingsih; Muthmainnah, Aindri Rizky; Surianto, Dewi Fatmarani; Fadilah, Nur
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 4 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i4.8773

Abstract

This study addressed the problem of low relevance in search results within the digital library system of the Department of Informatics and Computer Engineering (JTIK), Universitas Negeri Makassar. The purpose of this research was to improve the accuracy and relevance of search outcomes, enabling users, particularly students, to access academic materials and research references more efficiently. A search engine system was developed using a term-weighting method based on term frequency and document distribution. The system incorporated similarity measurement techniques to evaluate the degree of match between user queries and document content. An experimental approach was applied, which involved observation, data collection, text preprocessing, implementation of term weighting, and the comparison of cosine similarity and Weighted Jaccard similarity for ranking search results. The The evaluation was conducted using the Precision@K metric and a paired t-test to measure the significance of performance differences between methods. The test results showed that Weighted Jaccard obtained an average Precision@K value of 0.933, slightly higher than Cosine Similarity with an average of 0.9. However, Cosine Similarity produced a higher average similarity value. In addition, system testing was conducted in two stages, namely assessing user satisfaction with search results and assessing system performance. These findings confirmed that the combination of term-weighting and cosine similarity effectively enhanced the relevance and performance of digital library search systems.
Evolutionary Fuzzy Rule-Based Classification System dalam Analisis Sentimen terhadap Danantara Wijaya, Egi Putu; Rifqo, Muhammad Husni
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 4 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i4.8845

Abstract

In order to improve the Indonesian economy, the government launched Danantara, a Sovereign Wealth Fund that serves to manage data owned in investment instruments such as stocks, bonds or property where the profits from this are returned to the state into the APBN, besides that Danantara aims to stabilize the economy and drive national development. However, with the huge amount of money being managed and its vital purpose, the existence of danantara has been the subject of much debate. Some people support the existence of danantara because it can help raise the Indonesian economy, but others reject the existence of danantara because they are afraid of being a place for corruption if there is mismanagement of large funds and can disrupt the current Indonesian economy. For this reason, the research aims to analyze public sentiment using the Evolutionary Fuzzy Rule-Based Classification System which has an approach to fuzzy rules that can overcome the level of ambiguity in sentiment analysis. The stages carried out in this research start from data collection using the webscraping method on platform x, data cleaning, data pre-processing, data labeling, classification of Evolutionary Fuzzy Rule-Based Classification System and at the end of the evaluation stage. The results obtained in this study are the accuracy and recall rates of 69%, then precision 72% and f1-score 70%. This shows that the Evolutionary Fuzzy Rule-Based Classification System model is less suitable in analyzing and classifying public sentiment regarding the existence of danantara.
Penerapan Metode SAW dalam Penentuan Mata Pelajaran Pilihan Siswa Kelas XI pada MAN 1 Brebes Saputro, Risky Wisnu; edi, sarwo; Perdana, Willy Yudha; Nugroho, Kristiawan; Ardhianto, Eka
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 4 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i4.9248

Abstract

The subject selection process for eleventh-grade students at Madrasah Aliyah Negeri 1 Brebes faces challenges including misalignment between student interests and academic abilities, and imbalanced teacher-to-subject ratios across Natural Sciences, Social Sciences, and Religious Studies. This study develops a decision support system using the Simple Additive Weighting (SAW) method to provide objective recommendations that consider both academic performance and student preferences. A quantitative descriptive analytical approach was applied with data from 30 tenth-grade students, incorporating four criteria: Natural Sciences scores, Social Sciences scores, Religious Studies scores, and student interests, weighted 0.25, 0.25, 0.10, and 0.40 respectively. The SAW implementation included decision matrix construction, normalization, weighted preference calculation, and recommendation determination. Results showed optimal distribution with 19 students recommended for Natural Sciences, 7 for Social Sciences, and 4 for Religious Studies, achieving 96.67% accuracy in aligning preferences while optimizing academic potential. The system preserved preferences for all students initially interested in Social Sciences and Religious Studies, while reassigning two Natural Sciences–interested students to Social Sciences based on superior performance. Top-performing students identified were Mohammad Abian for Natural Sciences (0.9802), Julia for Social Sciences (0.87243), and a student with 0.75995 for Religious Studies. The SAW method proves effective in addressing multi-criteria decision-making while ensuring transparency, objectivity, and balanced resource use in Islamic secondary education.
Analisis Pengaruh SMOTE terhadap Kinerja Model KNN untuk Prediksi Risiko Stroke Paramita, Cinantya; Simbolon, Calvin Samuel; Pamungkas, Azriel Sebastian; Triono, Justin Matthew; Widi Utomo, Emanuel Pinesthi; Subhiyakto, Egia Rosi
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 4 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i4.8809

Abstract

Penelitian ini membahas masalah ketidakseimbangan data dalam klasifikasi risiko stroke, di mana kasus non-stroke secara signifikan lebih rendah daripada kasus stroke. Ketidakseimbangan kelas cenderung menimbulkan bias terhadap kelas mayoritas, yang menyebabkan berkurangnya efektivitas klasifikasi. Untuk mengatasi hal ini, SMOTE (Synthetic Minority Over-sampling Technique) digunakan untuk mengatasi ketidakseimbangan kelas dalam dataset dan algoritma K-Nearest Neighbor (KNN) digunakan untuk klasifikasi. Dataset mengalami preprocessing, aplikasi SMOTE, dan algoritma KNN dilatih dan dievaluasi menggunakan metrik standar termasuk akurasi, presisi, recall, dan F1-score. Penerapan SMOTE bersama dengan KNN menghasilkan peningkatan yang signifikan dalam hasil klasifikasi, mencapai akurasi 91,87%, presisi 94,27%, recall 89,20%, dan F1-score 91,66%. Temuan ini menegaskan bahwa pendekatan yang diimplementasikan berkinerja baik dalam mendeteksi risiko stroke meskipun ada set data yang tidak seimbang. Tujuan dari penelitian ini adalah untuk menginformasikan kemajuan teknologi deteksi dini stroke yang lebih kuat dan mendukung peningkatan dalam penyediaan layanan kesehatan.
Prediksi Tinggi Gelombang Laut di Perairan Semarang – Demak dengan Menggunakan Random Forest dan XGBoost Erutjahjo, Ganis; Supriyanto, Aji
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 4 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i4.9315

Abstract

English Climate change and regional oceanographic activities have contributed to increasing significant wave height (SWH) and sea level rise (SLR) along the northern coast of Central Java (Semarang-Demak). This study aims to analyze and predict SWH and SLR using two artificial intelligence methods: Random Forest (RF) and Extreme Gradient Boosting (XGBoost). The dataset includes meteorological and oceanographic parameters from 2019 to 2024. Model performance was evaluated using accuracy metrics such as RMSE, MAE, MAPE, and the coefficient of determination (R²). The results show that XGBoost outperforms RF in predicting both target variables. XGBoost achieved R² values of 0.9989 for SWH and 0.9921 for SLR, with MAPE scores of 1.6% and 1.1%, respectively. The most influential factor for SWH prediction was the historical significant wave height (hs), while the average daily sea level elevation had the highest impact on SLR prediction. Comparison plots between actual and predicted values indicate that both models effectively captured seasonal trends, particularly in identifying wave peaks in early months and sea level increases during mid-year.The 2025 forecast suggests rising SWH patterns from January to March and peak SLR values around June. These findings are expected to support coastal adaptation policies in response to climate change and to inform the design of more resilient marine infrastructure in the future.
The Impact of Image Pre-processing for Tuberculosis Prediction System Based on Chest X-ray Images Kurniawan, Rudi; Badriyah, Tessy; Apriandy, Kevin Ilham; Syarif, Iwan
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 4 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i4.9086

Abstract

With the rapid development of automated detection system using deep learning techniques on Chest X-ray (CXR) image datasets to the subjective assessment performed by healthcare professionals. Preprocessing is critical in medical image analysis as it helps highlight important anatomical features while suppressing irrelevant information, thus enabling the model to focus on meaningful patterns. In this paper, we investigate the impact of image preprocessing techniques on the performance of a tuberculosis prediction system based on CXR images using a deep learning approach. We used the “Tuberculosis Chest X-rays (Shenzhen)” dataset, which contains 1,344 CXR images (672 TB cases and 672 normal cases). We propose a five-step preprocessing pipeline consisting of resizing, heavy sharpen filtering, CLAHE (Contrast Limited Adaptive Histogram Equalization), horizontal flip augmentation, and data normalization. The findings indicate that the model utilising preprocessing markedly surpasses the one lacking it, attaining an accuracy, precision, recall, and F1-score of 71%, in contrast to 51%, 50%, 50%, and 36% without preprocessing, respectively.  This study enhances the existing research on the application of deep learning in medical diagnostics and emphasises the significance of preprocessing for attaining dependable, high-performance systems.
Text Summarization Umpan Balik Pengguna Website SiBayar Pondok Pesantren Sabilurrosyad dengan Metode Bi-LSTM Hassan, Sayyed Aamir; Supriyono, Supriyono; Abidin, Zainal
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 4 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i4.8846

Abstract

The SiBayar website is being developed by the Sabilurrosyad Islamic Boarding School to facilitate its administration and management. To improve the functionality of the website, user feedback is needed on the existing features. However, managing and analyzing a large amount of user feedback manually can be a very time-consuming process. Therefore, an automated approach such as text summarization is needed to summarize and analyze the data. This study aims to generate an automated summary of user feedback on the SiBayar website of the Sabilurrosyad Islamic Boarding School using the Bi-Directional Long Short-Term Memory (Bi-LSTM) method, focusing on identifying the best parameters through hyperparameter tuning and evaluating the accuracy in full. The results of the hyperparameter tuning test show that the configuration that provides the best performance is the one using the Nadam algorithm optimization, the number of layers 1 and batch size 1, and the variational dropout with a dropout rate of 0.5. The model summary quality evaluation was performed using the ROUGE metric which showed that the Bi-LSTM model achieved a ROUGE-1 score of 0.6221, a ROUGE-2 score of 0.5462, and a ROUGE-L score of 0.660. Overall, Bi-LSTM model in this study has good performance in summarizing text, but the suitability of word pairs and sequences still needs to be improved for more optimal results.
Implementasi Algoritma Binary Space Partitioning Untuk Procedural Map Generation Dalam Gim Rosyid, Harits Ar; Prasetyo, Ahmad Adi
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 4 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i4.8629

Abstract

The popularity of games as an interactive entertainment medium continues to grow, with 2D maps playing a vital role in enhancing user experience. Manual map creation is time-intensive, particularly as game worlds become increasingly complex. Procedural Content Generation (PCG) offers a solution by automating map creation, improving replayability, and reducing designer workload. This research explores the use of the Binary Space Partitioning (BSP) algorithm for procedural dungeon map generation, incorporating random connections between rooms to create more exploratory and dynamic maps. The process includes three stages: developing a dungeon map generator, implementing BSP with random room connectors, and validating the generated maps to ensure navigability. Space Syntax analysis, including Visibility Graph Analysis (VGA) and Axial Line Analysis, is applied to evaluate the quality of the maps in terms of connectivity, visibility, and integration. Results show that BSP-generated maps with random connections offer dynamic layouts, while Space Syntax measures reveal that smaller minimum room sizes result in lower integration and connectivity but increase interaction hotspots. This study demonstrates the potential of BSP in generating varied game maps and the utility of Space Syntax for assessing their spatial properties.
Perancangan Aplikasi Web Asisten Dosen dengan Metode Design Thinking Chung, Cecillia; Lauro, Manatap Dolok
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 4 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i4.8883

Abstract

Teaching assistants (TAs) play a crucial role in supporting practical learning processes. However, TA management often encounters challenges in class and teaching time allocation, TA attendance recapitulation, and end-of-semester evaluations. To address these issues, a system that facilitates the management of practical sessions involving TAs is necessary. This web application system is designed to streamline task management, class scheduling, material collection, attendance tracking, and TA evaluations at the end of each semester. Furthermore, supporting features such as an integrated dashboard and automated notifications can enhance the delivery of practical services to students. This research employs the Design Thinking methodology, an innovative, user-centered design approach, to develop solutions that meet user needs. Through the stages of empathize, define, ideate, prototype, and test, the resulting web application not only simplifies practical management but also improves the user experience for both lecturers and TAs. Based on a questionnaire administered to 20 teaching assistants, usability testing of the web application using the System Usability Scale (SUS) method yielded an average score of 77.25, which falls under the 'good' category. Thus, this web application is expected to serve as an innovative solution that fosters a more flexible and integrated teaching and learning environment.

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