UIN (Universitas Islam Negeri) Sunan Kalijaga, Yogyakarta: E-Journal Fakultas Sains dan Teknologi
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    703 research outputs found

    Keanekaragaman Kupu-Kupu (Lepidoptera: Rhopalocera) di Kawasan Ekowisata Dusun Kaliurang Timur, Yogyakarta

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    Butterflies act as bioindicators and pollinators of the environment. Ecotourism development poses a threat to butterfly life due to high human activity and land degradation. This study aims to determine the diversity of butterflies (Rhopalocera), diversity index, evenness index, dominance index, similarity index, and abiotic parameters at each sampling location. The data was collected  at Tlogo Putri, settlements, and Tankaman Natural Park, whose location selection was based on purposive sampling and using the point count method. Based on the research obtained 55 species with a total of 294 individuals, diversity index (TP: 2.88; P: 2.51; TNP: 2.66), evenness index (TP: 0.86; P: 0.75; TNP: 0.84), dominance index (TP: 0.08; P: 0.14; TNP: 0.09), species similarity index (TP & P: 46.42; TP & TNP: 27.45). Abiotic parameters in the ecotourism area of Kaliurang Timur Hamlet are altitude of 814-889 meters above sea level, temperature of 26-28°C, air humidity of 10-45%, light intensity of 7571-4877x10 lux, wind speed of 0-1 m/s, and rainfall of 0-20. The conclusion of this study is that 55 species of Rhopalocera order were found, the diversity index is moderate, the evenness index is high, the dominance index and the similarity index are low at each sampling location. Abiotic parameters measured were in the normal range for Rhopalocera life in the ecotourism area of Kaliurang Timur Hamlet

    Analisis Bukti Digital Pada Media Penyimpanan Flash Disk Menggunakan Metode National Institute Of Standards And Technology (NIST)

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    Dalam perkembangan teknologi digital yang semakin pesat, analisis bukti digital menjadi semakin penting dalam mendukung penegakan hukum dan mengamankan ranah keamanan siber. Proses analisis bukti digital melibatkan pemeriksaan terhadap berbagai informasi digital yang ditemukan dalam investigasi kejahatan atau kasus hukum. Bukti digital tersebut dapat berupa file, pesan teks, email, rekaman panggilan, atau data lainnya yang terdapat dalam perangkat digital seperti komputer, ponsel, dan tablet. Penelitian ini membahas tentang bagaimana memperoleh, mengambil, melestarikan, dan menyajikan data atau informasi tentang jejak aktivitas kasus cybercrime yang terdapat pada media penyimpanan flash disk yang telah dihapus dan bertujuan untuk mendukung penyelidikan terhadap pelaku kejahatan dengan menerapkan prinsip-prinsip forensik digital. Pada penelitian ini menggunakan metode National Institute of Standards dan Technology (NIST) dan menggunakan FTK Imager sebagai tool forensic dan Autopsy sebagai tools analisis dan juga recovery data serta HashGenerator untuk mengecek hasil hash dari tiap-tiap file. Dari hasil analisis yang telah dilakukan, didapatkan file-file yang telah dihapus oleh pelaku dengan perlakuan yang berbeda-beda pada media penyimpanan flash disk menggunakan tools forensik FTK Imager, Autopsy, dan juga HashGenerator, dimana tool Autopsy berhasil mendapatkan metadata file-file yang dihapus pada tanggal yang sama dengan tanggal pelaporan. Perbedaan dari masing-masing perlakuan penghapusan terdapat terdapat pada perlakuan ketiga yaitu dengan perintah quick format dimana nama file yang terhapus berubah menjadi nama file yang berbeda seperti nama file aslinya. Selain itu size dan nilai hash pada semua file pada tiap-tiap perlakuan tidak menunjukkan adanya perubahan pada nilai hash MD5-nya yang menandakan bahwa file-file tersebut tidak ditemukan adanya perubahan. Kata kunci: kejahatan siber, bukti digital, NIST, digital forensik, flash disk,  forensic tools. ------------------------------------------------------------ In the rapid advancement of digital technology, the analysis of digital evidence has become increasingly vital in supporting law enforcement and securing the realm of cybersecurity. The process involves scrutinizing various digital information found in criminal investigations or legal cases. Digital evidence can encompass files, text messages, emails, call recordings, or other data within digital devices such as computers, phones, and tablets. This research delves into the acquisition, retrieval, preservation, and presentation of data or information related to traces of cybercrime activities found on deleted flash disk storage media. The aim is to support investigations into criminal perpetrators by applying principles of digital forensics. The study utilized the National Institute of Standards and Technology (NIST) methodology, employing FTK Imager as a forensic tool, Autopsy for analysis and data recovery, and HashGenerator to verify the hash results of each file. From the analysis conducted, various files deleted by the perpetrator were discovered on the flash disk storage media, subjected to different treatments using forensic tools FTK Imager, Autopsy, and HashGenerator. Autopsy successfully retrieved metadata of the deleted files on the same date as the reporting date. Notable differences were observed among the deletion methods. Particularly, in the third method involving quick format, the deleted filenames were altered to different names similar to their original names. Additionally, the size and hash values of all files for each deletion method showed no alterations in their MD5 hash values, indicating that no changes had occurred to these files. Keywords: Cybercrime, Digital Evidence, NIST, Digital Forensics, Flash Disk,  Forensic Tool

    Analisis Bibliometrika: 4 Dekade Penelitian Cyber Weapon dalam Peperangan Modern

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    Dibalik serangan siber terdapat metode baru dalam peperangan modern, yaitu pemanfaatan cyber weapon. Artikel ini menggunakan analisis bibliometrika untuk memetakan tren dan kesenjangan dalam studi tentang cyber warfare, dengan data yang diambil dari sistem indeks Scopus. Dokumen yang digunakan adalah daftar indeks artikel dari Scopus sebanyak 565 artikel. Hasil analisis menunjukkan peningkatan signifikan dalam publikasi terkait cyber weapon sejak tahun 2018, Amerika Serikat sebagai negara kontributor terbesar yang diikuti oleh negara-negara lain seperti India, Britania Raya, Cina, dan Korea Selatan. Selain itu, penelitian ini mengidentifikasi tiga kluster utama: ancaman siber terhadap infrastruktur kritis, strategi pertahanan siber, dan peran spionase dalam serangan siber. Artikel ini juga menyoroti pentingnya pemetaan penelitian untuk mengembangkan strategi mitigasi yang lebih efektif terhadap ancaman cyber weapon dan meningkatkan kesadaran global tentang perang siber. Penelitian lebih lanjut diperlukan untuk mengeksplorasi peran kecerdasan buatan dalam taktik cyber weapon yang terus berkembang, serta untuk memahami dampak sosial dan ekonomi dari serangan siber. Kata kunci: cyber warfare, cyber weapon, analisis bibliometrika, serangan siber, pertahanan siber -------------------------------------- Behind cyber attacks is a new method in modern warfare, namely the utilization of cyber weapons. This article uses bibliometric analysis to map trends and gaps in the study of cyber warfare, with data taken from the Scopus index system. The document used is the index list of 565 articles from Scopus. The results of the analysis showed a significant increase in cyber weapon-related publications since 2018, with the United States as the main contributor, followed by countries such as India, the United Kingdom, China, and South Korea. Additionally, the research identified three main clusters: cyber threats to critical infrastructure, cyber defense strategies, and the role of espionage in cyber attacks. The article also highlights the importance of research mapping to develop more effective mitigation strategies against cyber weapon threats and raise global awareness of cyber warfare. Further research is needed to explore the role of artificial intelligence in evolving cyber weapon tactics, as well as to understand the social and economic impacts of cyber attacks. Keywords: cyber warfare, cyber weapon, bibliometrics analysis, cyber attack, cyber defens

    Sentiment Analysis of TIMNAS Indonesia's Participation in the Asian Cup U23 2024 on X Using Naive Bayes and SVM

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    This study aims to analyze the sentiment of the Indonesian public regarding the participation of the Indonesian National Team in the 2024 U-23 Asian Cup through the social media platform X. Sentiment analysis is crucial for understanding public perception and its impact on support for the national team. The research methodology involves collecting user comments on X related to the team's performance during the tournament, followed by data cleaning. The dataset is manually labeled, with 80% used as training data for algorithmic model training and the remaining 20% as test data, classified using Naive Bayes and Support Vector Machine algorithms. The analysis results indicate that the SVM algorithm achieves a higher % accuracy rate of 95% compared to Naive Bayes, which achieves 87%. The majority of the 3367 opinions analyzed express positive or satisfactory sentiments towards the national team's participation. However, there are fewer negative sentiments, highlighting areas requiring team management's attention. This study provides valuable insights into public perception of the Indonesian National Team. Furthermore, these findings can inform policymakers and team managers' decision-making to enhance the team's quality and performance in the future

    Design and Development of an Edugame Arabic for Learning Media

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    Learning media provides significant advantages to students by improving their learning experience through the use of multimedia applications, resulting in a more engaging and fascinating learning environment while reducing the monotony associated with traditional manual learning techniques. Digital learning material, provides a platform for interesting learning activities, encouraging a delightful and cost-effective learning experience. The impact of learning media is especially noticeable in the subject of the Arabic language. Arabic is traditionally regarded as a difficult language, and many students dislike this language course. However, the Edugame Arabic was created to overcome this issue. Using the GDLC process, which includes phases of initialization, pre-production, production, testing, and publishing. This game-learning application was evaluated through a testing phase that included groups of school students who were actively involved in Arabic language lessons. Edugame Arabic has successfully been installed and runs smoothly on various Android smartphones. Moreover, the game's offline capability allows users to continue their learning without an internet connection. The questionnaire responds, with users strongly agreeing that the app has an appealing design, an intriguing game premise, good material delivery, and considerable aid in learning Arabic. Furthermore, users generally acknowledged that the Edugame is simple to use and helps with vocabulary learning

    Deep Learning dalam Prediksi Kebiasaan Merokok di Inggris Guna Mendukung Kebijakan Kesehatan Masyarakat yang Lebih Efektif

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    Smoking is a common practice throughout the world, where a person smokes and inhales the smoke produced from burning tobacco or other tobacco products. This action has become a significant global health issue because of the various health risks. This activity is often considered an addictive habit because nicotine, the psychoactive compound in tobacco, can cause physical and psychological dependence. This research applies Deep Learning methods to predict data on smoking habits in the UK. The dataset used in this research includes information about gender, age, marital status, highest level of education, nationality, ethnicity, income, and region. Through this research using Deep Learning methods, we can examine a complex data set that describes Smoking Habits in the UK. Based on trials with a dataset of 1,691 items, an accuracy of 78% was obtained. This research can provide important insights into the effectiveness of anti-smoking policies that have been implemented and help plan further actions to reduce the prevalence of smoking and its negative impact on society

    Development of Geographic Information Systems in Mapping Village-Owned Enterprises in Sleman Regency

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    The population increase in the Special Region of Yogyakarta poses challenges, including developing Village-owned Enterprises or BUM Desa in Sleman Regency to enhance rural community welfare. BUM Desa data management currently relies on manual spreadsheets and lacks a dynamic data storage system, hindering access to accurate information. This study employed the Scrum methodology, gathering data through literature reviews, interviews, and observations to assess the current state of BUM Desa. A product backlog guided the development of a web-based GIS application through sprint planning, resulting in an application that maps BUM Desa locations in the Sleman Regency based on coordinates and provides detailed development classifications. This application enhances data management and decision-making for BUM Desa development, simplifies government data management, and improves public access to BUM Desa locations. Black box testing confirmed its functionality, with 100% validity. End-user computing Satisfaction (EUCS) surveys indicated high user satisfaction, emphasizing the application's usability and alignment with user expectations in providing accurate and accessible BUM Desa information

    Comparison of Single Exponential Smoothing and Double Moving Average Algorithms to Forecast Beef Production

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    Beef is considered a high-value commodity as it is an important source of protein. Interest in beef continues to rise. Beef production has risen sharply in the past decade, but declined by 7,240.68 tons in 2020 amid coronavirus lockdowns. After that, in 2021, production reached 16,381.81 tons and continued to increase in 2022 and 2023. A precise method is required to forecast beef production. One way to predict beef production in Jakarta is using the Single Exponential Smoothing and Double Moving Average methods. The two algorithms are compared to get the lowest error rate. The methodology used in this research is the SEMMA (Sample, Explore, Modify, Model, and Assess) methodology. According to SAS Institute Inc., there are five stages in developing a system using the SEMMA methodology. After analyzing using MAPE, it is found that the algorithm with the smallest error value is the Single Exponential Smoothing algorithm with a percentage in the monthly period of 16% while for the annual period, it is 27% compared to other algorithms. The forecasting is quite accurate because the MAPE value for each algorithm used has an error of less than 31%

    Pendekatan Sinergis Antara Ajaran Islam Dengan Analisis Data Kategorik Berdasarkan Q.S. Al-Hujurat Ayat 13

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    According to this research, understanding and addressing complex social issues is crucial. This article emphasises the differences between religion and science and how they affect how we understand the social world, particularly Muslim communities with different views on Western civilisation. The thirteenth verse of Surah Al-Hujurat in the Qur'an is analysed along with categorical data analysis techniques to investigate the issue of prejudice in society. This paper aims to enhance our understanding of the moral principles contained in religious teachings and how to overcome prejudice in society through the incorporation of these principles. The research method combines the interpretation of Qur'anic verses with statistical concepts, resulting in a deeper understanding of the issues. In conclusion, this article demonstrates the importance of interdisciplinary integration in understanding and addressing complex social issues

    Faktor Penyebab Artefak pada Hasil Radiograf (Soft File) Digital Radiografi di RSUD Dr. Moewardi Surakarta

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    Artifact is a structure or appearance that deviates from what should normally be seen on a radiograph (Walz-Flannigan, 2018). Artifacts can originate from various sources such as the Imaging Plate (IP), X-Ray machine, user errors, and foreign objects. All of these factors mentioned can be sources of artifacts. The aim of this research is to identify the factors and the most significant factor causing artifacts in radiographic results. This study employs a qualitative research approach utilizing a survey method. The research was conducted from June to July 2023 at RSUD Dr. Moewardi Surakarta. Data collection methods included direct observation, documentation, and interviews. The study involved 4 radiographers and 2 radiology specialist doctors as respondents. Subsequently, the collected data were processed, tabulated, and presented in the form of pie charts to draw conclusions. The research results indicate that the primary causes of artifacts in the Radiology Department at RSUD Dr. Moewardi Surakarta are: 1. Foreign objects, 2. Imaging Plate (IP), and 3. X-Ray machine. This is supported by the respective percentages of artifacts found: foreign objects 77%, Imaging Plate (IP) 19%, and X-Ray machine 4%

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    UIN (Universitas Islam Negeri) Sunan Kalijaga, Yogyakarta: E-Journal Fakultas Sains dan Teknologi is based in Indonesia
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