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Karakteristik Morfologi dan Pemanfaatan Bambu Duri (Bambusa blumea) di Wilayah Pesisir Desa Jambo Timu, Kecamatan Blang Mangat, Kota Lhokseumawe Fathiya, Nir; Qariza, Maulin Hayatun; Nazhifah, Sri Azizah; Diah, Husna
Jurnal Jeumpa Vol 9 No 2 (2022): Jurnal Jeumpa
Publisher : Department of Biology Education, Faculty of Teacher Training and Education, Samudra University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33059/jj.v9i2.6314

Abstract

Bambu merupakan salah satu jenis tumbuhan yang telah banyak dimanfaatkan oleh masyarakat secara turun-temurun karena memiliki beragam khasiat dan harganya relatif murah. Salah satu jenis bambu yang ditemukan melimpah di wilayah Indonesia adalah bambu duri (Bambusa blumea). Tujuan penelitian adalah untuk menyediakan informasi tentang karakteristik morfologi dan pemanfaatan bambu duri di wilayah pesisir Desa Jambo Timu, Kota Lhokseumawe. Metode penelitian berupa Participatory Rural Appraisal (PRA) dan dianalisis secara deskriptif. Hasil penelitian menunjukkan bahwa bambu duri di Desa Jambo Timu memiliki karakteristik morfologi di antaranya: daun (bangun daun berbentuk lanset, pangkal daun tumpul, ujung daun meruncing, tepi daun merata, pertulangan daun sejajar, dan permukaan daun berbulu), buluh dan ranting (berwarna hijau, namun ada perbedaan dalam tingkatan warna dan memiliki duri), dan tunas (berwarna jingga dan tertutup dengan bulu-bulu halus cokelat). Bambu duri digunakan sebagai obat tradisional, pupuk, perkakas rumah tangga, kerajinan, dan bahan konstruksi. Bagian-bagian bambu duri yang dimanfaatkan oleh warga Desa Jambo Timu adalah buluh bambu, daun bambu, dan tunas bambu. Persentase bagian bambu duri terbanyak digunakan adalah buluh bambu yaitu sebesar 72%. Sedangkan daun bambu dan tunas bambu dimanfaatkan warga sebesar 14%.
THE FEASIBILITY OF FUSING SATELLITE IMAGERIES FOR HIGH-FREQUENCY SEA LEVEL MONITORING Putri, Andriani; Nazhifah, Sri Azizah; Ridho, Abdurrahman; Maghfirah, Hayatun; Mutia, Cut; Niani, Cukri Rahmi; Sanusi, Sanusi
CYBERSPACE: Jurnal Pendidikan Teknologi Informasi Vol 8, No 1 (2024)
Publisher : UIN Ar-Raniry

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22373/cj.v8i1.23504

Abstract

Enhancing the capacity to monitor swift environmental shifts at finer scales requires satellite image that offers high spatial and temporal resolution. However, no individual satellite can offer images meeting both criteria simultaneously. To tackle this challenge, spatial temporal fusion algorithms have been developed to derive fine-scale and time-series images. Conversely, effective monitoring of water levels is crucial for preventing natural disaster, such as flood and tsunami mitigation. Yet, monitoring these natural changes regularly poses challenges for remote sensing satellites, given their limitations in either spatial or temporal resolution. For instance, the spatial resolution of 30 meters of Landsat 8 provides imagery with a but lacks the temporal resolution needed to capture dynamic events. On the contrary, the Himawari 8 has the capability to monitor the entire hemisphere every 10 minutes. However, its inadequate resolution affects the precision of sea water change mapping.  This research seeks to utilize Landsat OLI and Himawari-8 images jointly for tracking sea level variation patterns. Our approach involves calculating a water index from both Landsat and Himawari images, then using an image fusion algorithm to merge these indices. Next, we identify water coverage by applying a specific threshold on the water index. The comparison of water percentages with reference water height observations has delivered encouraging outcomes.
Performance Assessment of Machine Learning and Transformer Models for Indonesian Multi-Label Hate Speech Detection Bagestra, Ricky; Misbullah, Alim; Zulfan, Zulfan; Rasudin, Rasudin; Farsiah, Laina; Nazhifah, Sri Azizah
Infolitika Journal of Data Science Vol. 2 No. 2 (2024): November 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijds.v2i2.235

Abstract

Hate speech, characterized by language that incites discrimination, hostility, or violence against individuals or groups based on attributes such as race, religion, or gender, has become a critical issue on social media platforms. In Indonesia, unique linguistic complexities, such as slang, informal expressions, and code-switching, complicate its detection. This study evaluates the performance of Support Vector Machine (SVM), Naive Bayes, and IndoBERT models for multi-label hate speech detection on a dataset of 13,169 annotated Indonesian tweets. The results show that IndoBERT outperforms SVM and Naive Bayes across all metrics, achieving an accuracy of 93%, F1-score of 91%, precision of 91%, and recall of 91%. IndoBERT's contextual embeddings effectively capture nuanced relationships and complex linguistic patterns, offering superior performance in comparison to traditional methods. The study addresses dataset imbalance using BERT-based data augmentation, leading to significant metric improvements, particularly for SVM and Naive Bayes. Preprocessing steps proved essential in standardizing the dataset for effective model training. This research underscores IndoBERT's potential for advancing hate speech detection in non-English, low-resource languages. The findings contribute to the development of scalable, language-specific solutions for managing harmful online content, promoting safer and more inclusive digital environments.
FUSING SATELLITE DATA TO MONITOR SEA LEVEL CHANGES: A DEM-BASED NEAREST NEIGHBOR APPROACH Putri, Andriani; Nazhifah, Sri Azizah; Ridho, Abdurrahman; Maghfirah, Hayatun; Mutia, Cut; Niani, Cukri Rahmi
CYBERSPACE: Jurnal Pendidikan Teknologi Informasi Vol 8, No 2 (2024)
Publisher : UIN Ar-Raniry

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22373/cj.v8i2.26369

Abstract

High spatial and temporal resolution satellite imagery is essential for monitoring rapid environmental changes at finer scales. However, no single satellite currently provides images with both high spatial and temporal resolution. To overcome this limitation, spatiotemporal image fusion algorithms have been developed to generate images with improved spatial and temporal detail. Water level monitoring is also crucial for managing natural hazards like floods and tsunamis, but remote sensing satellites face challenges in continuous monitoring due to either low spatial or temporal resolution. For instance, while Landsat 8, with a spatial resolution of 30 meters, has been used for water level detection, it cannot capture fast-changing events because of its low temporal resolution. Conversely, the Advanced Himawari Imager (AHI) 8 offers observations every 10 minutes but has a coarse spatial resolution, limiting its ability to map sea level changes accurately. This study focuses on integrating Landsat and AHI imagery to monitor local and dynamic sea level changes. The process involves calibrating images from the study area to surface reflectance and co-registering them. The Normalized Difference Water Index (NDWI) is calculated from both Landsat and Himawari-8 images, serving as input for image fusion. In the previous study, the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) is used for image fusion. In this study we use the application of Spatial Temporal Adaptive Algorithm for Mapping Reflectance Change (STAARCH) for the image fusion step. Since traditional methods are influenced by land cover changes, this study proposes a method called DEM-based Nearest Neighbor to select appropriate land cover maps for image fusion. Evaluation results demonstrate that this approach can produce accurate water coverage maps with both high spatial and temporal resolution.
Comparison of Support Vector Machine and Random Forest Methods on Sentinel-2A Imagery for Land Cover Identification in Banda Aceh City Using Google Earth Engine Safira; Amiren, Muslim; Nazhifah, Sri Azizah; Rusdi, Muhammad; Nizamuddin; Misbullah, Alim
The Indonesian Journal of Computer Science Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i6.4510

Abstract

Land cover is a physical feature of the earth that illustrates the relationship between natural processes and social processes. Over time, there has been a lot of land conversion, where initially open land is now built-up land. This is due to the large-scale development in Banda Aceh City. Therefore, this study aims to compare the performance of two classification methods, namely using Support Vector Machine (SVM) and Random Forest in identifying land cover in Banda Aceh City using Sentinel-2A imagery via the Google Earth Engine platform. As for data recording, it starts from January 1 to December 31, 2023. There are 4 classes used in this study, namely vegetation, water bodies, built-up land, and open land. The classification results show that the Support Vector Machine and Random Forest methods have been successfully applied to identifying land cover in Banda Aceh City using Sentinel-2A imagery. The accuracy results show that the Support Vector Machine method has a higher accuracy value of 90.5% compared to the Random Forest method of 85.7%.
ANALYSIS OF LAND SURFACE TEMPERATURE IN THE KRUENG ACEH WATERSHED USING GOOGLE EARTH ENGINE Khairunnisa, Yulia; Nazhifah, Sri Azizah; Amiren, Muslim; Syahreza, Saumi; Rusdi, Muhammad; Saputra, Kurnia; Putri, Andriani; Sukiakhy, Kikye Martiwi
CYBERSPACE: Jurnal Pendidikan Teknologi Informasi Vol 9, No 1 (2025)
Publisher : UIN Ar-Raniry

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22373/cj.v9i1.29076

Abstract

The constantly changing land surface temperature has implications for agricultural productivity and human health, therefore it is important to observe the land surface temperature to provide information about the characteristics and patterns of a region. The purpose of this research is to determine the changes and spatial patterns of land surface temperature distribution in the Krueng Aceh Watershed in 2013, 2018, and 2023. The method employed in this study involves utilizing the Google Earth Engine platform and MODIS imagery. Land surface temperature data from MODIS imagery is processed using JavaScript programming language, and the results are analyzed to obtain the distribution of land surface temperature. The study results indicate that the land surface temperature in the Krueng Aceh Watershed was 29,11℃ in 2013, increase to 29,5℃ in 2018, and then decreased to 29,19℃ in 2023. The Krueng Aceh Watershed in 2013, 2018, and 2023 exhibits similar spatial patterns and distributions of land surface temperature, with areas in Banda Aceh City experiencing higher temperatures compared to those in Aceh Besar District, which exhibit varying temperatures.
Sebaran Gerai Vaksinasi Covid-19 Di Kota Banda Aceh Berbasis WebGIS Mawaddah, Jihan; Nazhifah, Sri Azizah; Muzaillin, Muzaillin; Putri, Andriani
J-SIGN (Journal of Informatics, Information System, and Artificial Intelligence) Vol 1, No 01 (2023): May
Publisher : Department of Informatics, Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/j-sign.v1i01.31761

Abstract

Perkembangan teknologi informasi memudahkan siapa saja untuk berbagi dan mendapatkan informasi yang salah tentang vaksinasi COVID-19. Informasi terkait vaksinasi COVID-19 seperti capaian vaksinasi per kecamatan dan desa dalam bentuk peta, sebaran lokasi vaksinasi dan jalur menuju lokasi vaksinasi serta formulir pendaftaran vaksinasi dapat disampaikan melalui WebGIS. Pengembangan WebGIS ini menggunakan Laravel sebagai framework, Leaflet sebagai library dan MariaDB sebagai basis datanya. Informasi capaian liburan dibagi menjadi 3 kelas warna sesuai capaian vaksinasi yang divisualisasikan dalam bentuk peta tematik. Selain itu, informasi capaian vaksinasi COVID-19 juga tersedia dalam bentuk grafik dan diagram. WebGIS ini telah menguji usability pada 30 user dengan menggunakan 30 pertanyaan dari metode USE Questionnaire yang dibagi menjadi 4 bagian yaitu usability, ease of use, ease of learning dan satisfaction. Hasil pengujian WebGIS ini memperoleh skor 88, 67%, artinya WebGIS ini termasuk dalam kategori sangat layak.
Uji Kelayakan Sistem Informasi Berbasis Web Pada Kasus Penyakit Mulut dan Kuku Nazhifah, Sri Azizah; Basri, Fazil; Muslim, Muslim; Putri, Andrini
The Indonesian Journal of Computer Science Vol. 13 No. 3 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i3.3967

Abstract

Foot and Mouth Disease (FMD) is a viral infection in animals that is contagious and acute. However, public access to information and visualization of the spread of FMD and vaccination in Nagan Raya District is still limited. The reporting of FMD cases by the public still relies on village authorities, leading to inaccuracies in information and field validation constraints. Additionally, difficulties in registering livestock vaccinations are caused by inaccuracies in data and livestock location, hindering the Animal Husbandry Department in providing doses and determining the route to these locations. Therefore, this research aims to build a WebGIS that includes visualization of FMD spread, FMD case reporting, and vaccination registration. This WebGIS is developed using Laravel and Leaflet, tested with validation, reliability, and usability questionnaires. Users include the general public, the Animal Husbandry Department, and medical professionals. The results show that the WebGIS has an 89.3% feasibility percentage and is highly suitable. It can facilitate access to FMD information and visualization and streamline reporting and vaccination registration.