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All Journal International Journal of Electrical and Computer Engineering MANAJEMEN HUTAN TROPIKA Journal of Tropical Forest Management Jurnal Simetris Mediator Jurnal Teknologi Informasi dan Ilmu Komputer KOMUNIKA Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING Dinamisia: Jurnal Pengabdian Kepada Masyarakat PROSIDING KOMUNIKASI JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) EDUMATIC: Jurnal Pendidikan Informatika Jurnal Sistem informasi dan informatika (SIMIKA) Jurnal Ilmu Teknik dan Komputer Dinasti International Journal of Economics, Finance & Accounting (DIJEFA) International Journal of Educational Research and Social Sciences (IJERSC) International Journal of Community Service International Journal of Qualitative Research Electronic Journal of Education, Social Economics and Technology International Journal of Health, Engineering and Technology West Science Business and Management Bulletin of Social Studies and Community Development Indonesian Journal of Community Services Laporan Upaya Nyata Inovasi Ilmu Komputer (LUNIK) Siber International Journal of Education Technology Journal of Public Relations and Digital Communication (JPRDC) JPM (Jurnal Pengabdian Masyarakat) Ruwa Jurai Nemui Nyimah
Ida Nurhaida
Universitas Lampung
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary Other

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Global Synergy, Local Impact : Optimizing Information Retrieval In Lampung Community Libraries Through Information Literacy Training Program By Lampung University And Charles Sturt University Windah, Andi; Nurhaida, Ida; Putra, Purwanto; Purnamayanti, Arnila; Maryani, Eri
International Journal Of Community Service Vol. 5 No. 2 (2025): May 2025 (Indonesia - Malaysia - Timor-Leste)
Publisher : CV. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51601/ijcs.v5i2.849

Abstract

International cooperation in community service is becoming increasingly crucial in the era of globalization. The D3 Library Study Program, FISIP Unila, in collaboration with the School of Information and Communication Studies-Charles Sturt University, carried out Community Service in International Cooperation (PKMKI) with a focus on improving information literacy for community library managers in Lampung Province. In an era of abundant information, the ability to search for accurate and relevant information is becoming increasingly important. However, many individuals have difficulty navigating the vast ocean of information. This service aims to overcome this problem by providing training on advanced information search techniques, especially through Google Advanced Search Operators. The methods used in this service include literature studies, field observations, interviews, and Focus Group Discussions (FGD) with community library managers. The results of this service are expected to improve the ability of library managers to provide better information services to the community. The outputs produced include a final service report, financial report, video documentation, and information literacy training modules.
LSTM-Based NLP Approach for Spelling Error Detection and Correction in Scientific Writing Indonesian Language Halim, Yeru Dwi Pratama; Nurhaida, Ida
Electronic Journal of Education, Social Economics and Technology Vol 5, No 1 (2024)
Publisher : SAINTIS Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33122/ejeset.v5i1.309

Abstract

Scientific writing requires precision and clarity to uphold credibility and effective communication. Errors such as spelling mistakes and typos can compromise the quality and reliability of scientific texts. This study proposes a Long Short-Term Memory (LSTM)-based approach to detect and correct spelling errors, enhancing text accuracy and readability. The dataset comprises 45,698 standard words, supplemented with typo variations to improve model performance. Data is sourced from the Indonesian Dictionary (KBBI) and undergoes normalization and preprocessing to capture diverse error patterns. The model’s performance is evaluated using a confusion matrix, achieving 93% accuracy and high precision, recall, and F1-score metrics. These results demonstrate that the proposed NLP-based LSTM model offers an effective and reliable solution for identifying and correcting spelling errors. This approach significantly enhances the quality of scientific writing, ensuring more transparent and credible communication.
Web-Based Face Recognition System for Attendance Management Pratiwi, Chelomitha Arsy; Nurhaida, Ida
Electronic Journal of Education, Social Economics and Technology Vol 5, No 2 (2024)
Publisher : SAINTIS Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33122/ejeset.v5i2.291

Abstract

Studi ini berfokus pada pengembangan aplikasi absensi berbasis web yang memanfaatkan teknologi pengenalan wajah untuk mengatasi keterbatasan sistem absensi manual, seperti inefisiensi, kesalahan, dan kerentanan terhadap penipuan. Sistem yang diusulkan menggunakan algoritma Scale-Invariant Feature Transform (SIFT) untuk mengekstraksi fitur wajah, memastikan pengenalan yang akurat dalam berbagai kondisi. Set data terdiri dari 537 gambar wajah yang diberi anotasi, diproses terlebih dahulu melalui pengubahan ukuran dan konversi skala abu-abu untuk meningkatkan ekstraksi fitur. Pelatihan model, yang diimplementasikan dengan YOLOv8, mencapai akurasi 97,05%, presisi rata-rata rata-rata (mAP) 0,975, dan skor F1 0,95, yang menunjukkan keandalan deteksi dan pengenalan wajah yang tinggi. Aplikasi ini terintegrasi dengan REST API, yang memungkinkan verifikasi absensi waktu nyata dengan mencocokkan gambar wajah yang diambil dengan basis data terpusat. Meskipun sistem menghadapi tantangan dalam mengenali profil samping dan kondisi cahaya redup, sistem ini secara signifikan meningkatkan manajemen absensi dengan mengotomatiskan proses, meminimalkan kesalahan, dan meningkatkan keamanan data. Peningkatan di masa mendatang dapat menggabungkan teknik pembelajaran mendalam dan integrasi yang lebih luas dengan sistem manajemen personalia untuk mengoptimalkan kinerja, skalabilitas, dan efisiensi operasional.
Signature Originality Verification Using A Deep Learning Approach Saputra, Muhammad Azi; Nurhaida, Ida
Electronic Journal of Education, Social Economics and Technology Vol 5, No 1 (2024)
Publisher : SAINTIS Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33122/ejeset.v5i1.310

Abstract

The rapid advancement of digital technology has heightened the need for reliable methods to verify signature authenticity, a critical aspect of document and transaction security. This study uses a deep learning approach to develop a mobile application to verify the originality of paper and digital media signatures. The dataset comprises 1,060 signature images, including authentic and forged categories for both media types. The system employs the EfficientNetV2M model, trained with augmented data, to enhance robustness. Model evaluation demonstrates strong performance with an accuracy of 82.07%, a global precision of 81.31%, a global recall of 83.25%, and a global F1-score of 82.18%. The model is implemented in an Android-based mobile application, providing an intuitive interface for users to upload and verify signatures in real time. These results underscore the potential of EfficientNetV2M for mitigating signature fraud across various domains while highlighting areas for improvement, particularly in classifying paper-based signatures. Future work will focus on expanding the dataset and refining feature extraction techniques to enhance classification performance.
Analisis Sentimen berbasis Deep Learning Terhadap Kesetaraan Gender di Bidang STEM: Perspektif dan Implikasinya Mariam, Siti; Nurhaida, Ida
Jurnal Pendidikan Informatika (EDUMATIC) Vol 9 No 1 (2025): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v9i1.29071

Abstract

Women's participation in Science, Technology, Engineering, and Mathematics (STEM) is still low due to discrimination, gender stereotypes, and lack of access to equal career opportunities. This research analyzes public sentiment about gender equality in STEM fields using the Knowledge Discovery in Database (KDD) approach with the Long Short-Term Memory (LSTM) algorithm. The data consists of 1,200 tweets (2018-2024) collected through web crawling and processed using KDD techniques such as preprocessing, transformation, data mining and evaluation. The resulting LSTM model showed 86.25% accuracy, 88.18% precision, 82.20% recall, and 85.00% F1-score. Sentiment analysis showed support and appreciation for women in STEM (positive sentiment) and criticism of gender discrimination and stereotypes (negative sentiment). This study faced challenges in the form of data imbalance and the model's difficulty in understanding the Indonesian context. Our findings confirm the importance of policies that support gender equality and inclusive work environments. This research is expected to improve people's perception of gender equality and increase the representation of women in STEM fields, especially in Indonesia.
Aplikasi Artificial intelligence untuk Klasifikasi Lengkungan Kaki: Solusi berbasis Radiografi Haris, Abdul; Nurhaida, Ida
Jurnal Pendidikan Informatika (EDUMATIC) Vol 9 No 1 (2025): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v9i1.29098

Abstract

Identifying foot arch types is crucial for maintaining health and comfort. Flat foot arches can cause pain and discomfort, potentially interfering with activities such as sports. This research aims to develop an Artificial intelligence (AI)-based application to detect normal and flat foot arch types through X-ray images. The YOLOv8 model with bounding box is converted to TensorFlow Lite format to be integrated into a mobile platform through Android Studio. The application uses a waterfall model without maintenance, starting from the analysis of x-ray dataset needs, development and testing of the YOLOv8 model, conversion to TensorFlow Lite, design, black box testing, and application on Android devices. This application can only identify x-ray photos of the soles of the feet looking right and left. Confusion matrix application testing with 150 epochs shows performance with recall 86.2%, precision 77.1%, accuracy 83.3%, mAP50 94.9%, and mAP50-95 76.2%. Black box testing on mobile devices using datasets augmented with 45° horizontal shear and 90° rotation resulted in maximum identification accuracy compared to traditional methods such as the wet foot test. Traditional methods print the soles of the feet with an identification process that requires precision of the patient's standing position. This app detects flatfoot early, improving comfort in daily activities and sports.
The Effect of Financial Innovation, Risk Management, and Monetary Policy on the Stability of Fintech Startup Companies in Jakarta Ali, Husain; Sirat, Abdul Hadi; Nurhaida, Ida
West Science Business and Management Vol. 2 No. 04 (2024): West Science Business and Management
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsbm.v2i04.1556

Abstract

This study investigates the effects of financial innovation, risk management, and monetary policy on the stability of fintech startup companies in Jakarta. Using a quantitative approach, data were collected from 35 fintech startups through structured questionnaires with responses measured on a Likert scale of 1-5. Data analysis was conducted using SPSS version 25, employing correlation and multiple regression analysis. The results reveal that financial innovation is the most significant predictor of fintech stability, followed by risk management and monetary policy. The combined influence of these factors explains 74% of the variance in fintech stability. These findings underscore the importance of integrating innovation with robust risk management practices and aligning operations with macroeconomic trends for sustained stability. This research provides valuable insights for fintech stakeholders and policymakers to foster resilience and growth in the rapidly evolving financial ecosystem.
Fostering Sustainable Digital Leadership in Educational Organization, Systematic Literature Review using NVIVO and PRISMA Giovanni, Netaniel; Ali, Hapzi; Nurhaida, Ida
Dinasti International Journal of Economics, Finance & Accounting Vol. 5 No. 3 (2024): Dinasti International Journal of Economics, Finance & Accounting (July - August
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dijefa.v5i3.2853

Abstract

This research identifies the role of digital leadership in educational organizations. The analysis uses qualitative analysis. The research method used is SLR (Systematic Literature Review) with the PRISMA protocol through stages supported by the Publish or Perish and NVIVO applications. All supporting publications were searched through Publish or Perish and Dimension Database. The article search results found 543 related studies in 2020-2024, then filtered through the PRISMA protocol to 35 articles selected to answer the research questions. The results of the article are: 1) Sustainable digital leadership involves several essential aspects: agility, resilience, and adaptability. 2) There are 10 sustainable digital leadership competencies that digital leaders need to have: Focus on Vision, Repetitiveness, Communication and Collaboration, Flexibility, Resourcefulness, Risk-Taking and Recovery, Critical Thinking, Culture of Learning, Responsiveness, and Creativity and Innovation. 3) Future leaders must prioritize understanding digital change and assessing digital leadership competencies. This competency development can take the form of training, talent development, support from experts, and digital leadership assessments. 4) Essential to provide financial resources, infrastructure, work environment, and access to the latest learning technology. 5) The most vital aspect of digital leadership is how leaders collaborate and empower to realize the vision, implement change, and create a creative and innovative educational organizational environment.
Online Health Navigation: Study Case of @leonavictoria_ahligizi’s Instagram's Impact on Information Fulfilment for Stunting Prevention Reza Gustifa, Adinda; Windah, Andi; Tina, Kartika; Nurhaida, Ida; Aryanti, Nina Yudha
International Journal of Health Engineering and Technology Vol. 2 No. 6 (2024): IJHET MARCH 2024
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55227/ijhet.v2i6.196

Abstract

This study investigates the impact of Instagram content on maternal attitudes and practices pertaining to child nutrition and the prevention of stunting. The study utilizes case study approach to analyze the Instagram account @leonavictoria_ahligizi on Milhinhos's theoretical framework. The research assesses the content of the account in terms of its relevance, accuracy, value, understandability, discoverability, and consistency. The analysis is contingent upon Instagram's capacity to address a variety of informational requirements, including cognitive, affective, personal integration, social integration, and tension release. The findings illustrate a statistically significant influence of Instagram in improving the dietary practices of mothers of preventing stunting in children. The findings analysis, utilizing SmartPLS 4. 0, revealed a significant association between Instagram content and users' understanding and dietary habits, as evidenced by a path coefficient of 0. 729 This suggests a substantial impact on the satisfaction of information needs. The demographic data indicates that the majority of the participants are well-educated mothers between the ages of 25 and 34, who are actively involved in consuming the content with the aim of enhancing their children's dietary habits. The material presented on @leonavictoria_ahligizi not only serves to increase knowledge and understanding but also facilitates the practical application of nutritional regimens essential for the early developmental phases of children. This highlights the significant importance of customized, trustworthy, and practical social media material in addressing child stunting and advancing public health by promoting informed dietary habits. The incorporation of social media platforms into health education initiatives signifies a substantial advancement in efforts to combat worldwide malnutrition and improve the health outcomes of communities.
THE INFLUENCE OF SOCIAL MEDIA MUKBANG CONTENTS TOWARDS ADOLESCENT FOOD CONSUMPTION BEHAVIOR Olova, Khansa Ranbia Audreyzovna; Windah, Andi; Riza, Ahmad; Nurhaida, Ida
Journal of Public Relations and Digital Communication (JPRDC) Vol 2, No 2 (2024): Journal of Public Relations and Digital Communication (JPRDC)
Publisher : Universitas Sang Bumi Ruwa Jurai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24967/jprdc.v2i2.3386

Abstract

How individuals eat has an impact on their health and well-being. To maintain their well-being, individuals must control their mindset and social environment. The prevalence of eating broadcasts on YouTube, where content creators consume large amounts of food without revealing nutritional information, continues to be a popular trend that hypothetically affects people's eating habits. The study aims to assess the influence of social media influencers on unhealthy food habits, using Planned Behavior Theory as a framework. This study used a method of survey and collecting quantitative data. This study examined the research site of the University of Lampung. The data analysis was done descriptively. According to the regression formula, Y = 16. 615 + 0677X - Constant term = 16. In summary, with a trust value of 0, 615 indicates a positively oriented regression coefficient X, which represents the magnitude of influence of the X variable on the Y variable. The t-test showed X had a significant impact of 40. 1% on Y 59 remaining. 9% of variation in the Y variable attributed to unexamined factors. The study showed that how much a person's food consumption behavior is affected by watching an eating broadcast depends on their intentions. Consuming the frequency, duration, and attention levels of the broadcast significantly affects and improves unhealthy consumption behavior in adolescents.
Co-Authors ., Karomani Abdul Haris Ahmad Riza Ahmad Riza Faizal, Ahmad Riza Akhmad Riza Faizal Akmal Junaidi Ali, Husain Andi Windah Andi Windah* Andi, Windah Arif Sugiono Arnila Purnamayanti Aryanti Nina Yudha Asep Sukohar Ayumi, Vina Azis, Diky Luqman Christine, Wulandari Darojat, Agus Dhamanti, Inge Djauharie, Arlyandi S Djuadi, Noverman Faisal, Fairo Mahaputranda Fikri, Muhammad Huri Fitri Yakub Giovanni, Netaniel Halim, Yeru Dwi Pratama Hapzi Ali Hazni, Elvira Hestin Oktiani Hidayat, Januar Putra Ichsan Ichsan Khansa, Devanna Alandra Khaqqi, Fitriyana Nuril Kurnia Muludi Lathifah Alfat, Lathifah Maryani, Eri Mediansyah, Aulian Negara, Komang Putra Satria Nina Yudha Aryanti Olova, Khansa Ranbia Audreyzovna Pairulsyah Pairulsyah Pratiwi, Chelomitha Arsy Putra, Purwanto Ramadityo, Kafka Reza Gustifa, Adinda Samsul, Bakri Saputra, Muhammad Azi Sirat, Abdul Hadi SITI MARIAM Slamet Riyadi Sugeng P Hariyanto Sugeng Prayitno , Harianto Sugiyanta Sugiyanta Sugiyanto, Puspandari Setyowati Suharyani Suharyani Tina, Kartika Tjahjono, Benny Yudha Aryanti, Nina