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All Journal Pendas : Jurnah Ilmiah Pendidikan Dasar ILKOM Jurnal Ilmiah Jurnal Peduli Masyarakat Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Teknik Informatika (JUTIF) MEDIC MEdical Dedication International Journal of Social Service and Research Shihatuna : Jurnal Pengabdian Kesehatan Masyarakat Prosiding Seminar Nasional Program Pengabdian Masyarakat Pharmaceutical Sciences and Research (PSR) Jurnal Karya Abdi Masyarakat Jurnal Ilmiah Ilmu Terapan Universitas Jambi Electronic Journal Scientific of Environmental Health And Diseases Riset Informasi Kesehatan Jurnal Pengabdian Harapan Ibu (JPHI) Journal of Pharmaceutical and Sciences. Jurnal Medicare Jurnal Kefarmasian Indonesia Jurnal Ilmu Pendidikan dan Bahasa Jurnal Abdimas Kesehatan Aksi Kita: Jurnal Pengabdian Kepada Masyarakat International Journal of Language and Culture Indonesia Berdampak: Jurnal Pengabdian Kepada Masyarakat Jurnal Ilmiah Detubuya Kajen: Jurnal Penelitian dan Pengembangan Pembangunan
Fitrianingsih Fitrianingsih
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Cloud Computing-Based U-Net Integration for Post-Landslide Satellite Image Segmentation Pratiwi , Swelandiah Endah; Asnur, Paranita; Fitrianingsih, Fitrianingsih; Senjaya, Remi; Nurdin, Muhammad Sahal
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 2 (2026): JUTIF Volume 7, Number 2, April 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.2.5617

Abstract

Landslides are geological disasters that cause severe impacts on human life, infrastructure, and ecosystems, highlighting the need for post-disaster mapping methods that are fast, accurate, and scalable. This study aims to develop a post-landslide satellite image segmentation framework based on U-Net integrated with cloud computing to support large-scale and operational disaster mapping. While U-Net has been widely applied for landslide analysis, most existing studies focus on local-scale assessments or susceptibility mapping and lack integration with cloud-based pipelines and multi-source data for post-disaster operations. The novelty of this research lies not in modifying the U-Net architecture, but in integrating multi-source geospatial data, system workflow, and scalable cloud deployment. The proposed framework utilises a global multi-source dataset consisting of RGB imagery, Normalized Difference Vegetation Index (NDVI), slope, and elevation to enhance robustness and generalisation across diverse geomorphological conditions. Experimental results show stable model convergence with a final loss of 0.0357, an F1-score exceeding 0.75, and an AUC-PR of 0.8391. Evaluation on the testing dataset achieves a precision of 0.7692, recall of 0.7519, F1-score of 0.7604, and Intersection over Union of 0.6135. Qualitative analysis demonstrates strong spatial agreement between predicted segmentation and ground truth, with minor deviations mainly along complex slope boundaries. From an Informatics perspective, this study contributes by operationalizing deep learning through cloud computing to enable scalable computation, parallel processing, and system-level deployment, while providing object-level estimates of landslide events and affected areas to support disaster response and risk mitigation.
Early Detection Education for TB–HIV Among Mosque Congregants During the Ramadan Safari Program in the Jajag Primary Health Center Catchment Area, Banyuwangi Suhita, Byba Melda; Animo, Dora Ayu Prima; Fitrianingsih, Diah
Shihatuna : Jurnal Pengabdian Kesehatan Masyarakat Vol 6 No 1 (2026): April
Publisher : FKM UIN Sumatera Utara Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/shihatuna.v6i1.28925

Abstract

Low awareness of early detection has serious impacts. Individually, a delay in diagnosing TB can cause the disease to become severe and infect those closest to you, while HIV that is detected late will progress to the deadly AIDS stage.. One of them is in the community working area of the Jajag Health Center which is located in Gambiran District, Banyuwangi Regency. This community service activity aims to increase the congregation's knowledge and awareness regarding Tuberculosis (TB) and Human Immunodeficiency Virus (HIV), especially regarding early symptoms, transmission methods, and the importance of early detection, which is held during the fasting month through the Ramadhan Safari activity. This community service activity utilizes a community-based health education approach, implemented through a combination of outreach, participatory discussions, and voluntary screening services. The program successfully increased participants' knowledge of the symptoms, transmission, and importance of early detection of infectious diseases. The implementation of these activities also demonstrated that approaches through religious communities are effective in reaching communities that previously had limited access to health information. In addition to providing knowledge, these activities have begun to encourage changes in public attitudes toward health screening and foster collective awareness of the importance of disease prevention
Sentiment Analysis of Distance Learning Using the K-Nearest Neighbor Method Maharani, Ni Wayan Devina; Fitrianingsih, Fitrianingsih
International Journal of Social Service and Research Vol. 6 No. 4 (2026): International Journal of Social Service and Research
Publisher : Ridwan Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/ijssr.v6i4.1378

Abstract

During the pandemic, the Indonesian government issued a Distance Learning (PJJ) policy to reduce the spread of COVID-19. Many people expressed opinions about the pros and cons of the implementation of distance learning policies through social media, one of which is Twitter. These opinions can then be processed by conducting sentiment analysis. In this study, researcher will implement the K-Nearest Neighbor method to conduct sentiment analysis on Twitter regarding distance learning. The initial stage of the research is collecting tweets from Twitter as many as 1014 data. The next stage is labeling the dataset manually, which is then followed by the preprocessing stage which consists of data cleaning, case folding, tokenization, normalization, stopword removal and stemming. The dataset is further divided into two, namely train data and test data using an 8:2 ratio, where 80% is used as train data and 20% is used as test data. The K-Nearest Neighbor model is then built with several different hyperparameters. The KNN model evaluated using test data. The calculation of the accuracy value between the prediction sentiment and the actual sentiment of the test data is done using confusion matrix. The results of data classification using the K-Nearest Neighbor method with the most optimal hyperparameter resulted in an accuracy of 74.38%. The results of the study are expected to be able to classify positive and negative sentiment within sentences with the best accuracy so that the results of this study can help the government regarding distance learning policies during the pandemic.
Co-Authors ., Elisma Agusriani, Agusriani Agustin, Ovi Amelia Amalia Nasution, Riska Aminuyati Andini Sulfitrana Andriani, Annisa Animo, Dora Ayu Prima Arni Nur Laili Azizah, Lailan Azzahra, Afifah Banun Saptaningsih, Agusdini Buhari Buhari Byba Melda Suhita Chytra Bertdiana Ersa Daaris, Yuli Yanti Dewi, Dinda Arum Carolina Diah Tri Utami Diah Tri Utami Dody Pernadi Dody Pernadi Elisma Elisma Elisma Elisma Em Yunir, Em Emay Mastiani Ersa, Chytra Bertdiana Fadli Ma’mun Pancar Farida Titik Kristanti Fatnur Sani K Hamilatussa'diyah, Hamilatussa'diyah Ikram Ikram Indriyani, Desti Irayani, Tri M. Ridwan Tahir, M. Ridwan M. Rifqi Efendi Maharani, Ni Wayan Devina Maharini , Indri Maharini, Indri Maman Suherman maulana, Ade Hilman Maulana, Emil Mia Prajuwita Muhammad Fadillah Muhammad Syukri Nasruloh, Ujang Neldi, Vina Novia Tri Astuti Nufi, Erma Pratiwi Nugraha, Rahmat Mulya Nurdin, Muhammad Sahal Nurfadilah Nurfadilah Paranita Asnur Patriya, Eka Pondawinata, Marizki Pratiwi , Swelandiah Endah Puspa Dwi Pratiwi Putu Nara Kusuma Prasanjaya Rahman Rahman Rani Sauriasari, Rani Rela Sonia Remi Senjaya Restu Libriani Revis Asra Rini Arianty Runtao, Zha Sadli, Nurul Kamilah Sani K, Fathnur Sania, Gina Santi Perawati, Santi Sari, Wa Ode Saktila Mayang Setiaji, Dini Anggraeni Saputri Sonia, Rela Susetianingtias, Diana Tri Syamsurizal Syamsurizal - - Tutik Ekasari Uce Lestari Usman, Minarti Utami, Diah Tri Wirdayanti Wirdayanti Yamin Yaddi Yuliandani, Yuliandani Yuliawati Yuliawati Yuliawati Yuliawati , Yuliawati Yuliawati Yuliawati Yusnelti Yusnelti Yusnelti Yusnelti Yusup, Aldian