Article Per Year (5 Year)
p-Index From 2021 - 2026
2.386
P-Index
This Author published in this journals
All Journal Panrita Abdi - Jurnal Pengabdian pada Masyarakat SISFOTENIKA JMM (Jurnal Masyarakat Mandiri) JURNAL TEKNOLOGI DAN OPEN SOURCE Jurnal Teknologi Informasi dan Multimedia JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Sains Komputer dan Teknologi Informasi International Journal of Engineering, Science and Information Technology JITSI : Jurnal Ilmiah Teknologi Sistem Informasi International Journal of Social and Education (INJOSEDU)
Siti Nurhayati
Universitas Yapis Papua
Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

Published : 15 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 15 Documents
Search

 1   2 
Penerapan Metode WASPAS Untuk Penentuan Penerima Beasiswa Salahudin Robo; Siti Nurhayati; Muh. Riandi Widiyantoro; Maulana Ayub Ahmad
Journal of Information System Research (JOSH) Vol 4 No 4 (2023): Juli 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v4i4.3662

Abstract

The need for funds or costs in education is important, one of those needs is scholarships, scholarships themselves are obtained based on several needs, one of which is that people can receive it if they are poor and there are difficulties in financing education. In that case, a system is needed that can help receiving scholarships. In that case, a decision support system for determining scholarship recipients was created using the Weighted Aggregated Sum Product Assessment method. The system used in this method is to provide several benchmarks as absolute values, after receiving a fixed value, the final result will be made in the form of a ranking arrangement of the data that has been made. The results of this study can assist in determining acceptance of the scholarship
THE ROLE OF THE INTERNET OF THINGS (IOT) IN CONNECTING DEVICES IN SMART HOMES: A LITERATURE REVIEW ON INTEGRATION, EFFICIENCY, AND SECURITY Siti Nurhayati; Suhana binti Sarkawi
INJOSEDU: International Journal of Social and Education Vol. 2 No. 9 (2025): International Journal of Social and Education (INJOSEDU)
Publisher : Adisam Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The development of Internet of Things (IoT) technology has opened up enormous opportunities for interconnecting various devices in smart homes, creating an integrated and efficient ecosystem. This study conducted a literature review to understand the role of IoT in connecting smart home devices, focusing on two main aspects: device integration and efficiency, and system security. The literature analysis shows that the integration of IoT devices enables centralised control and system automation, which improves comfort and energy efficiency. However, security challenges are a major concern due to the potential risks of hacking and privacy violations that could endanger residents. Therefore, the implementation of layered security methods is essential to ensure the protection of data and IoT device systems. In conclusion, IoT plays a significant role in creating smart homes that are not only intelligent and energy-efficient but also safe to use.
Model Klasifikasi Diabetes Menggunakan XGBoost Dengan Optimasi Seleksi Fitur Dan Hyperparameter Berbasis PSO Sheila putri aprilianti; Andrian Sah; Siti Nurhayati; Rasna; Jusmawati
JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Vol 7 No 2 (2026)
Publisher : SOTVI - Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/jitsi.7.2.620

Abstract

The rising global burden of diabetes mellitus has increased the need for accurate, technology-based early detection systems. This study develops a diabetes classification model using Extreme Gradient Boosting (XGBoost) optimized through a two-stage Particle Swarm Optimization (PSO) scheme: Binary PSO (BPSO) for feature selection and Global Best PSO (GBPSO) for hyperparameter tuning. Data were obtained from the Kaggle Diabetes Prediction Dataset (100,000 records; eight clinical attributes: gender, age, hypertension, heart disease, smoking history, BMI, HbA1c level, and blood glucose level). The extreme class imbalance (91.5% normal vs 8.5% diabetes) was addressed using the SMOTETomek hybrid technique. BPSO retained all eight features as the optimal combination (best cost 0.0329; F1-weighted 96.71%), while GBPSO produced the best hyperparameter configuration (n_estimators=416, learning_rate=0.237, max_depth=3, min_child_weight=3; best cost 0.0308, converging at the 11th iteration). The final model achieved 97.15% test-set accuracy, a ROC-AUC of 0.9779, and a diabetes-class precision of 0.93. The model was deployed as a Streamlit-based web system classifying patients into three risk categories: Not Indicated, Early Risk Indicated, and Diabetes Indicated. Preliminary validation on five real patient records from an anonymized partner hospital in Jayapura City showed classification results fully consistent with patients' clinical status (5 of 5 correct), indicating potential clinical applicability, although larger-scale testing is still required. These findings demonstrate that integrating XGBoost with a two-stage PSO optimization scheme produces an accurate and clinically applicable diabetes classification model.
Building a Web Crawler for Text Data Indexing on Online Newspaper Web Jamaludin Hakim; Andrian Sah; Siti Nurhayati; Wahyu Ciptaningrum; Damar Suryo Sasono
International Journal of Engineering, Science and Information Technology Vol 4, No 4 (2024)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v4i4.677

Abstract

The Internet has become a vast repository of information, often filled with distractions that can hinder the user experience. News content, for example, is usually interspersed with advertisements that interrupt the flow of reading. In addition, the fast pace of news publication is also a challenge, with potentially more than 50 new articles appearing in 20 minutes. This high-speed data flow is valuable for various applications, including Social Media Analytics Services. In this context, the speed and efficiency of data acquisition (crawling) and processing (scraping) are critical. These processes must be optimized to ensure comprehensive data collection without gaps, focusing on the latest information. To meet this need, we propose developing an application capable of capturing news data in its entirety, minimizing the risk of missing important information. At the core of this solution is a web crawler- a sophisticated program designed to automatically browse the hyperlink structure of the web, systematically downloading linked pages to local storage. This crawling methodology is often the basis for web mining initiatives and search engine development. Since web information is distributed across billions of pages hosted on millions of servers worldwide, our application utilizes the PHP programming language to capture and process this data effectively. The main goal is to present pure news content to users without any irrelevant elements. We use a Data Flow Diagram (DFD) to model the system architecture and data flow. This approach provides a clear visualization of how web users can navigate through hyperlinks to efficiently access the desired news information. By implementing this system, we aim to improve the user experience of consuming news content, facilitate more effective data analysis, and contribute to the broader web information search and processing field.
Heigh Detection System Using Russel and Rao Method Jamaludin Hakim; Mursalim Tonggiroh; Siti Nurhayati; M. Ali Nur Hidayat; Andrian Sah
International Journal of Engineering, Science and Information Technology Vol 4, No 4 (2024)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v4i4.671

Abstract

Height detection is an exciting area of research with broad applications in fields such as construction, healthcare, and robotics, where measurements are still often done manually. This research aims to automate the height calculation process by developing a height detection system using image processing techniques, which offers improved accuracy and efficiency. The system that will be built works by capturing images of objects through a webcam and using the Russel Rao cluster analysis method to calculate height later. Borland Delphi 07 was chosen as the programming language because of its ability to handle image-processing tasks. This research draws on a thorough literature review of various books and articles, with the system operating in stages, starting with converting images to grayscale to simplify the data for more accessible analysis and then followed by applying Russel Rao's method for height measurement. However, the system is sensitive to environmental factors around the object. The system will perform best when there are no other objects near the target because when there are other objects nearby, it can cause the measurement line to shift and interfere with the results. The detection system requires a controlled environment with no foreign objects nearby for optimal performance. Despite these limitations, Russel Rao's analysis method achieved an accurate detection accuracy of approximately 65%, with three out of eight sample tests yielding correct measurements. While this shows room for improvement if more relevant research is to be done in the future, this system will build a strong foundation for further development in this field. Future enhancements could focus on refining the algorithm to increase detection accuracy, make the system more resilient in dynamic or cluttered environments, and expand its potential applications in various fields.
Co-Authors Andrian Sah Damar Suryo Sasono Dewi Kusumawati Dian Pertiwi Emha Taufiq Luthfi Emilda Suharto Fitriyanti Andi Masse Imamul Hakim Irianto Irianto Jamaludin Hakim Jusmawati Jusmawati Jusmawati Kusrini M. Ali Nur Hidayat Maulana Ayub Ahmad Muhamad Taher Jufri Muhammad Riandi Widiyantoro Mursalim Tonggiroh Nur Aini Rasna Reni Rochmawati Ristiani Yunus Robo, Salahudin Ros Lina Septinus Bonay Sheila putri aprilianti Suhana binti Sarkawi Suhardi Suhardi Sumartono, Sumartono Wahyu Ciptaningrum