UIN (Universitas Islam Negeri) Sunan Kalijaga, Yogyakarta: E-Journal Fakultas Sains dan Teknologi
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Preparation and Alkaline Activation of Cellulose Extracted from Salacca zalacca Midrib for [AuCl₄]⁻ Adsorption
No full textCellulose from salacca (Salacca zalacca) midrib waste shows potential as an adsorbent for metal ions. In this study, cellulose was extracted through drying, grinding, delignification with 5% NaOH, and alkaline activation, followed by Fourier Transform Infrared (FTIR) characterization. Adsorption experiments were conducted by contacting 5 g of activated cellulose with 30 mL of 50 ppm [AuCl₄]⁻ solution at pH 1–4. The remaining Au concentration was measured using AAS to determine adsorption efficiency. The results show very high adsorption percentages: 99.70% (pH 1), 99.28% (pH 2), 97.98% (pH 3), and 97.72% (pH 4). Pearson correlation analysis yielded a significance value of 0.034 and a correlation coefficient of 0.966, indicating that pH influences adsorption and that adsorption efficiency decreases slightly with increasing pH. Overall, alkaline-activated cellulose from salacca midrib is highly effective for Au(III) adsorption, particularly under strongly acidic conditions
Extreme Gradient Boosting Model with SMOTE for Heart Disease Classification
No full textHeart disease is one of the leading causes of death worldwide. According to data from the World Health Organisation (WHO), the number of victims who die from heart disease reaches 17.5 million people every year. However, the method of diagnosing heart disease in patients is still not optimal in determining the proper treatment. Along with technology development, various models of machine learning algorithms and data processing techniques have been developed to find models that can produce the best precision in classifying heart disease. This research aims to create a machine learning algorithm model for categorizing heart disease, thereby enhancing the effectiveness of diagnosis and facilitating the determination of appropriate treatment for patients. This research also aims to overcome the limitations of accuracy in existing diagnosis methods by identifying models that can provide the best results in processing and analyzing health data, particularly in terms of heart disease classification. In this study, the XGBoost model was identified as the most superior, with an accuracy of 99%. These results demonstrate that the XGBoost model achieves a higher accuracy rate than previous methods, making it a promising solution for enhancing the accuracy of future heart disease diagnosis and classification
Analisis Forensik Digital Aplikasi Signal Desktop Pada Windows 11 Menggunakan Metodologi Forensik Digital Berbasis ISO/IEC 27037:2012 Dan ISO/IEC 27042:2015
No full textAplikasi Signal merupakan aplikasi pesan singkat yang dikenal dengan tingkat keamanan dan privasi yang tinggi. Meskipun demikian, keunggulan aplikasi ini sering dimanfaatkan oleh pelaku kejahatan untuk menyembunyikan atau menghilangkan barang bukti digital terutama pada platform Windows. Penelitian ini akan melakukan analisis forensik digital aplikasi Signal Desktop untuk menemukan bukti digital pada platform Windows 11 menggunakan metode ISO/IEC 27037:2012 dan ISO/IEC 27042:2015. FTK Imager dan Autopsy digunakan sebagai alat bantu forensik. Analisis forensik akan dilakukan dengan tiga skenario yang telah ditetapkan. Hasil penelitian menunjukkan bahwa artefak digital seperti teks, video, gambar dan file pdf dapat ditemukan dengan metode forensik yang sesuai, namun penghapusan data dan proses pencopotan aplikasi berdampak pada hasil artefak digital yang ditemukan. Penelitian ini juga membuktikan bahwa ISO/IEC 27037:2012 dan ISO/IEC 27042:2015 dapat digunakan untuk mengumpulkan, menganalisis, dan menginterpretasikan bukti digital secara sistematis.
Kata kunci: Forensik Digital, Signal Desktop, Windows 11, ISO/IEC 27037:2012, ISO/IEC 27042:2015, FTK Imager, Autopsy
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Digital Forensic Analysis Of Desktop Signal Applications On Windows 11 Using Digital Forensic Methodology Based On ISO/IEC 27037:2012 And ISO/IEC 27042:2015
The Signal application is an instant messaging platform well-known for its high level of security and privacy through the use of end-to-end encryption. However, these advantages are often exploited by criminals to conceal or erase digital evidence, especially on the Windows platform. Previous studies have demonstrated the effectiveness of forensic methods on Signal Messenger mobile devices using various tools and frameworks, but research on Signal Desktop artifacts in the latest operating systems remains limited. This study explores digital artifacts of Signal Desktop on Windows 11 to identify potential digital evidence that can be recovered. The methodology applies ISO/IEC 27037:2012 for the identification, collection, acquisition, and preservation of evidence, and ISO/IEC 27042:2015 for the analysis, interpretation, and reporting stages. The forensic tools employed are FTK Imager for data acquisition and Autopsy for artifact analysis. The experiment was conducted using three scenarios: normal usage without deletion, deletion of messages and files, and application uninstallation. The results show that digital artifacts such as text messages, images, videos, and PDF files can be retrieved in normal usage. In the deletion scenario, images, videos, and PDF files were recoverable as deleted files, whereas text messages were unrecoverable. In the uninstallation scenario, most artifacts were no longer accessible. These findings confirm that ISO/IEC 27037:2012 and ISO/IEC 27042:2015 provide a systematic and reliable framework for acquiring, preserving, and analyzing digital evidence in the context of Signal Desktop..
Keywords: Digital Forensics, Signal Desktop, Windows 11, ISO/IEC 27037:2012, ISO/IEC 27042:2015, FTK Imager, Autops
Analisis Cluster untuk Pengelompokan Kemampuan Penguasaan ICT Menggunakan K-Means dan Autoencoder
No full textInformation and Communication Technology (ICT) skills are essential in today’s digital age. However, numerous new students possess varying levels of ICT proficiency and may lack the necessary skills expected by universities. ICT training is essential for enhancing students’ ICT skills. Nevertheless, delivering the same training to all students proves to be less effective. Therefore, grouping students’ ICT skills is crucial to ensure that the training provided aligns with the fundamental abilities of the students. Cluster analysis is a common method for grouping data. This study employs k-Means and an autoencoder for cluster analysis, with the autoencoder utilized to reduce data dimensions and k-Means to perform the clustering process. The Elbow method is utilized to identify the ideal number of clusters. The optimal number of clusters determined was three. Model evaluation was conducted using the Silhouette coefficient and the Davies-Bouldin Index (DBI). The evaluation results revealed that the combination of k-Means and autoencoder yields superior performance compared to using k-Means alone, as evidenced by a higher Silhouette value and a lower DBI value
Image-Based Malware Multiclass Classification Using Vision Transformer Architecture: Multiclass Klasifikasi Malware Berbasis Gambar Menggunakan Vision Transformer Architecture
No full textPerkembangan malware yang semakin canggih telah menjadi ancaman serius bagi keamanan siber global, mengakibatkan kerugian finansial yang signifikan. Metode deteksi tradisional seperti deteksi berbasis tanda tangan dan analisis dinamis memiliki keterbatasan dalam mendeteksi varian malware baru. Sebagai solusi inovatif, analisis malware berbasis gambar mengubah file biner malware menjadi representasi gambar, memanfaatkan pemrosesan citra digital dan pembelajaran mesin untuk identifikasi yang lebih efisien. Penelitian ini menggunakan arsitektur Vision Transformer (ViT) untuk klasifikasi malware multikelas berbasis gambar, menawarkan pendekatan yang lebih efektif dibandingkan CNN tradisional seperti EfficientNet dan VGG16. ViT muncul sebagai pendekatan baru yang menarik karena fleksibilitasnya dalam memahami hubungan objek dalam gambar dan mendeteksi pola penting. Dengan kemampuannya mempelajari hubungan jangka panjang antar data, ViT dapat mendeteksi perbedaan halus antara berbagai jenis malware dan mencapai akurasi lebih tinggi. Dataset yang digunakan adalah Malimg, yang merupakan hasil konversi malware biner menjadi format gambar. Hasil penelitian menunjukkan Vision Transformers mencapai akurasi pelatihan 99.96%, validasi 98.05%, dan pengujian 97.49%, meningkatkan akurasi dibandingkan CNN. Keberhasilan ini menunjukkan kemajuan signifikan dalam akurasi deteksi, mengindikasikan arah menjanjikan untuk penelitian dan aplikasi keamanan siber di masa depan. Studi ini menekankan pentingnya teknik pembelajaran mesin yang canggih untuk meningkatkan deteksi malware.
Kata kunci: Vision Transformers, Klasifikasi Malware, Deep learning
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The increasing sophistication of malware has become a serious threat to global cybersecurity, resulting in significant financial losses for individuals and organizations. Traditional detection methods, such as signature-based detection and dynamic analysis, face limitations in identifying new or modified malware variants. As an innovative solution, image-based malware analysis converts malware binary files into image representations, leveraging digital image processing and machine learning for safer and more efficient identification. This study employs the Vision Transformer (ViT) architecture for multiclass image-based malware classification, offering a more effective approach compared to traditional CNNs. The Vision Transformer (ViT) has emerged as an exciting new approach, gaining attention for its flexibility in understanding object relationships within images and detecting important patterns. ViT, with its ability to learn long-range relationships between data, can detect subtle differences between various types and subtypes of malware, achieving higher classification accuracy. The results of this study show that Vision Transformers achieve the highest training accuracy of 99.96%, the highest validation accuracy of 98.05%, and a testing accuracy of 97.49%. The success of Vision Transformers in malware classification indicates significant advancements in detection accuracy, suggesting a promising direction for future research and applications in cybersecurity. This study underscores the importance of leveraging advanced machine learning techniques to enhance malware detection capabilities
Keywords: Vision Transformers, Malware Classification, Deep learning
CT Number Conformity Test on Multislice CT Scan at Yogyakarta PDHI Islamic Hospital: Uji Kesesuaian CT Number pada CT Scan Multislice di Rumah Sakit Islam Yogyakarta PDHI
No full textThis research focuses on determining the CT number, which is the attenuation coefficient value of x-rays after passing through an organ. The level of energy attenuation depends on the initial energy of the x-rays and the atomic number of the object, which play a role in describing differences in the characteristics of organs or body tissues. This research aims to ensure the suitability of the CT number to obtain accurate information about CT scan images. Research procedures include observation, data collection, and data processing. The CT number data from the experimental results was then compared with the simulation results using IndoQCT software. The CT Number conformity test is carried out on a water phantom by adjusting the tube voltage, input current, and slice thickness. The Region of Interest (ROI) is made in the form of a circle at five measurement points, namely the central direction, 3 o\u27clock, 6 o\u27clock, 9 o\u27clock, and 12 o\u27clock. The research results, both direct testing and simulation using IndoQCT software, show that the CT number does not exceed the accuracy tolerance limit and uniformity, respectively, -4 ˂ HU ˂ +4 and -2 ˂ HU ˂ +2. Based on the analysis results, it can be concluded that the CT number measurements in the Radiology Unit at the Yogyakarta PDHI Islamic Hospital meet the requirements of BAPETEN Perka Number 2 of 2018
The Supply Chain Performance Measurement and Determination of Improvement Priorities Using the Supply Chain Operations Reference –Digital Standard (SCOR DS) and Analytic Network Process (ANP) Methods: (Case Study: Waste Management at Sendangsari)
No full textEffective and efficient waste management remains a key challenge in supporting environmental sustainability at the regional level. This study was conducted at the Sendangsari Integrated Waste Management Site (TPST), located in Sleman, Yogyakarta. The aim of the research is to measure the performance of the waste processing supply chain and to determine the priority areas for improvement. The method used is the Supply Chain Operations Reference – Digital Standard (SCOR DS) approach to identify and categorize performance indicators based on six core processes: Plan, Order, Source, Transform, Fulfill, and Return. The Analytic Network Process (ANP) method is employed to assign weights to 18 Key Performance Indicators (KPIs) based on their level of influence and interrelation. These weights are then applied using the Objective Matrix (OMAX) method to calculate the performance scores for each indicator, which are subsequently classified using the Traffic Light System (TLS). The results show that TPST Sendangsari achieved an overall performance score of 7, with 9 KPIs falling in the green category, 7 in yellow, and 2 in red. These findings indicate that TPST Sendangsari requires further evaluation and improvement efforts, particularly for KPIs in the red and yellow categories, to enhance its overall performance
TITIK KRITIS KEHALALAN SODIUM DEHYDROACETATE SEBAGAI BAHAN TAMBAHAN PANGAN DITINJAU DARI EFEK SAMPING TERHADAP KESEHATAN
No full textAbstrak. Sodium Dehydroacetate (DHA-S) adalah senyawa kimia yang digunakan sebagai pengawet dalam makanan, kosmetik, dan pakan ternak. Meskipun dianggap aman oleh beberapa badan pengawas makanan di berbagai negara, penelitian terbaru DHA-S menimbulkan kekhawatiran terkait efek samping bagi kesehatan makhluk hidup termasuk risiko kardiovaskular dan gangguan metabolisme. Penelitian ini bertujuan untuk meninjau mengenai kehalalan penggunaan DHA-S sebagai bahan tambahan pangan dari perspektif Al-Quran, regulasi pangan, dan efek sampingnya terhadap kesehatan. Penelitian ini merupakan penelitian berbasis studi pustaka dengan menggunakan metode tinjauan sistematis dalam menganalisis informasi dari beberapa literatur guna menemukan jawaban mengenai permasalahan yang diangkat. Menurut Al-Quran surat Al-Baqarah ayat 168 dan surat Al-Maidah ayat 88, umat muslim tidak hanya diharuskan mengkonsumsi makanan halal tetapi juga makanan yang tidak berbahaya bagi tubuh atau thayyib. Penggunaan DHA-S sebagai bahan tambahan pangan menimbulkan masalah karena efek toksiknya yang signifikan terhadap hewan uji. Meskipun termasuk dalam bahan positive list menurut KMA 1360 Tahun 2021 dan diperbolehkan menurut beberapa regulasi di luar negeri yang diatur secara ketat, DHA-S belum diatur penggunaannya sebagai bahan tambahan pangan di Indonesia. Dengan demikian, produk makanan yang mengandung DHA-S tidak dapat dikategorikan sebagai produk halal menurut regulasi Sistem Jaminan Produk Halal karena potensi dampak negatifnya terhadap kesehatan manusia yang bertentangan dengan prinsip thayyib dalam Islam.
Kata kunci: Sodium Dehydroacetate, Pangan, Titik Kritis, Halal
Abstract.Sodium Dehydroacetate (DHA-S) is a chemical compound used as a preservative in food, cosmetics and animal feed. Although considered safe by several food regulatory agencies in various countries, recent research on DHA-S has raised concerns regarding adverse effects on human health including cardiovascular risk and metabolic disorders. This study aims to review the halal use of DHA-S as a food additive from the perspective of the Quran, food regulations, and its side effects on health. This research is a literature study-based research using a systematic review method in analyzing information from several literatures to find answers to the problems raised. According to Al-Quran Surah Al-Baqarah verse 168 and Surah Al-Maidah verse 88, Muslims are not only required to consume halal food but also food that is not harmful to the body or thayyib. The use of DHA-S as a food additive is problematic due to its significant toxic effects on test animals. Although it is included in the positive list of ingredients according to KMA 1360 of 2021 and is allowed according to several regulations abroad that are strictly regulated, DHA-S has not been regulated for use as a food additive in Indonesia. Thus, food products containing DHA-S cannot be categorized as halal products according to the Halal Product Guarantee System regulations due to its potential negative impact on human health which is contrary to the principle of thayyib in Islam.
Keynote: Sodium Dehydroacetate, Food, Critical Point, Halal 
KAJIAN MEDIS TERHADAP TATA CARA MANDI SESUAI ANJURAN RASULULLAH SAW
No full textAbstrak. Perubahan suhu tubuh yang terjadi secara mendadak dapat menyebabkan berbagai respon fisiologis yang signifikan, termasuk perubahan tekanan darah dan penyempitan atau pelebaran pembuluh darah. Secara medis, perubahan suhu tubuh mendadak dapat memicu dampak berbahaya, seperti pusing, peningkatan risiko serangan jantung, serta gangguan sirkulasi darah. Dalam HR. Ahmad 4/81, anjuran Rasulullah SAW untuk berwudhu sebelum mandi memiliki relevansi medis, terutama dalam hal adaptasi tubuh terhadap suhu air yang berbeda. Fungsi wudhu sebelum mandi adalah memproses tubuh untuk beradaptasi terhadap perubahan suhu air, sehingga dapat mengurangi risiko dampak negatif dari perubahan suhu mendadak. Penelitian ini bertujuan untuk mengkaji secara mendalam pengaruh perubahan suhu mendadak pada tubuh manusia serta relevansi anjuran Rasulullah SAW dalam upaya menjaga kesehatan melalui praktek wudhu sebelum mandi. Metode penelitian yang digunakan meliputi kajian pustaka mengenai konsep suhu tubuh, tekanan darah, dan adaptasi fisiologis terhadap perubahan suhu, serta studi kasus yang relevan. Hasil penelitian menunjukkan bahwa anjuran Rasulullah SAW dapat diinterpretasikan sebagai solusi untuk mengurangi risiko gangguan kesehatan akibat perubahan suhu mendadak. Penelitian ini diharapkan dapat menjadi pengingat agar selalu berhati-hati dalam mengatur suhu air saat mandi, serta memahami pentingnya adaptasi tubuh terhadap perubahan suhu yang mendadak.
Abstract. Sudden changes in body temperature can cause a variety of significant physiological responses, including changes in blood pressure and narrowing or widening of blood vessels. Medically, sudden changes in body temperature can trigger dangerous effects, such as dizziness, increased risk of heart attack, and impaired blood circulation. In HR. Ahmad 4/81, Rasulullah SAW\u27s recommendation to perform ablution before bathing has medical relevance, especially regarding the body\u27s adaptation to different water temperatures. The function of ablution before bathing is to process the body to adapt to changes in water temperature, thereby reducing the risk of negative impacts from sudden temperature changes. This research aims to analyze in depth the effect of sudden changes in temperature on the human body and the relevance of the Prophet\u27s recommendation in maintaining health through ablution before bathing. The research methods used include a literature review regarding the concepts of body temperature, blood pressure, and physiological adaptation to changes in temperature, as well as relevant case studies. The research results show that Rasulullah SAW\u27s recommendations can be interpreted as a solution to reduce the risk of health problems due to sudden temperature changes. It is hoped that this research can be a reminder to always be careful in regulating the water temperature when bathing and to understand the importance of the body\u27s adaptation to sudden changes in temperature
CYBER BULLYING DI ERA DIGITAL DAN UPAYA PENGUATAN DIMENSI ETIKA PERSPEKTIF AL-QURAN
No full textDisrupsi teknologi digital telah membawa fenomena bullying keluar dari ruang fisik menuju ruang yang abstrak. Dilansir dari Center for Digital Society (CfDS), hasil penelitian terhadap remaja usia 13-18 tahun di 34 Provinsi, tercatat 1.895 siswa mengalami cyber bullying. United Nation Children’s Fund (UNICEF) melakukan penelitian terhadap 2.777 responden berusia 14-24 tahun di Indonesia dan menunjukkan 45% anak pernah mengalami cyber bullying. Persoalan maraknya cyber bullying harus segera dituntaskan. Tujuan penulisan artikel ini mendeskripsikan urgensi perundungan yang semakin marak terjadi di ruang digital serta solusi berbasis nilai-nilai Al-Quran. Digital Ethic menjadi salah satu konsep yang diajarkan dalam agama Islam dalam menghadapi perkembangan teknologi. manusia sudah sejak lama diingatkan oleh Allah SWT dalam firman-Nya, QS. Al-Maidah [5]: 35. Refleksi ayat tersebut membawa manusia pada sebuah upaya keras untuk menjadikan teknologi sebagai jalan menuju kepada-Nya. Etika digital menjadi pondasi utama untuk mengakhiri problematika kejahatan siber, salah satunya cyber bullying. Al-Quran menjadi pedoman abadi bagi umat Islam telah menegaskan pentingnya menjaga kehormatan manusia sebagaimana tertuang dalam QS. Al-Hujurat [49]: 11. Allah juga menegaskan akan menghukum orang-orang yang menyebarkan kerusakan dan penindasan di muka bumi ini.
Kata kunci: Cyber Bullying, Etika Digital, Al-Qura