Hasil untuk "Islam. Bahai Faith. Theosophy, etc."

Muhamad Adnan Royandi, Enung Hasanah, Suyatno Suyatno

The ever-growing era of globalization places demands on having 21st century skills which include Critical Thinking, Creativity, Communication, and Collaboration. Technological advances require us to have communication and English language skills, and as Muslims, we are also required to have Arabic language skills to understand the holy book. In its implementation, Student Management has the function of improving these abilities and skills. This research aims to determine the planning, organization, implementation and control, and supervision of boarding school student management in improving Arabic and English language skills. This research uses a qualitative type of research, with a field observation approach, and data collection techniques using interviews, observation, and documentation. The results of this research explain that boarding school student management in improving Arabic and English language skills is by: 1) Planning which begins with a Work Meeting which plans one semester's work program, committee design, budget, and activity calendar; 2) Organizing by dividing tasks, committee obligations, and coordinating with PLC, LA, and SOS; 3) Implementation of daily language programs using Arabic and English which change every 2 weeks, weekly programs with vocabulary learning, public speaking, and muhadatsah, as well as semester programs in the form of language competitions such as the LHI Language Competition and Public Speaking Contest; 4) Control and supervision carried out by all teachers and also dormitory supervisors as well as evaluations held every week.

Nanda Asmawati, Widhy Tri Astuti, Wisnalmawati Wisnalmawati

The rapid development of digital technology has significantly changed consumer behavior, especially among Generation Z in Indonesia. This study aims to examine the effect of digital marketing and influencer marketing on purchase intention, with consumer attitudes as a mediating variable, in the context of Shopee application users in Sleman Regency. Data were collected through a survey aimed at Generation Z consumers who actively use the Shopee platform. This study uses a quantitative approach with the Structural Equation Modeling (SEM) method with Partial Least Squares (PLS) version 4.0 to analyze the relationship between variables. The results of the study indicate that digital marketing and influencer marketing positively influence consumer attitudes and purchase intentions. In addition, consumer attitudes are proven to significantly mediate the relationship between marketing strategies and purchase intentions. This study provides theoretical contributions to the understanding of digital marketing dynamics as well as practical implications for e-commerce platforms in increasing consumer engagement through targeted digital and influencer marketing strategies.

Qiang Ding, Lvzhou Luo, Yixuan Cao et al.

Ensuring that Large Language Models (LLMs) generate summaries faithful to a given source document is essential for real-world applications. While prior research has explored LLM faithfulness, existing benchmarks suffer from annotation ambiguity, primarily due to the ill-defined boundary of permissible external knowledge in generated outputs. For instance, common sense is often incorporated into responses and labeled as "faithful", yet the acceptable extent of such knowledge remains unspecified, leading to inconsistent annotations. To address this issue, we propose a novel faithfulness annotation framework, which introduces an intermediate category, Out-Dependent, to classify cases where external knowledge is required for verification. Using this framework, we construct VeriGray (Verification with the Gray Zone) -- a new unfaithfulness detection benchmark in summarization. Statistics reveal that even SOTA LLMs, such as GPT-5, exhibit hallucinations ($\sim 6\%$ of sentences) in summarization tasks. Moreover, a substantial proportion ($\sim 9\%$ on average of models) of generated sentences fall into the Out-Dependent category, underscoring the importance of resolving annotation ambiguity in unfaithfulness detection benchmarks. Experiments demonstrate that our benchmark poses significant challenges to multiple baseline methods, indicating considerable room for future improvement.

Tousif Islam, Tejaswi Venumadhav

Characterizing eccentricity in gravitational waveforms in a consistent manner is crucial to facilitate parameter estimation, astrophysical population studies, as well as searches for these rare systems. We present a framework to characterize eccentricity directly from gravitational waveforms for non-precessing eccentric binary black hole (BBH) mergers using common modulations that eccentricity induces in all spherical harmonic modes of the signals. Our framework is in the spirit of existing methods that use frequency modulations in the waveforms, but we refine the approach by connecting it to state-of-the-art post-Newtonian calculations of the time evolution of the eccentricity. Using 39 numerical relativity (NR) simulations from the SXS and RIT catalogs, as well as waveforms obtained from the post-Newtonian approximation and effective-one-body (EOB) formalism, we show that our framework provides eccentricity estimates that connect smoothly into the relativistic regime (even up to $\sim 2M$ before merger). We also find that it is necessary to carry existing post-Newtonian calculations to an extra $0.5$PN order to adequately characterize existing NR simulations, and provide fits to the extra coefficient for existing simulations. We make the framework publicly available through the Python-based \texttt{gwModels} package.

Kyungha Kim, Sangyun Lee, Kung-Hsiang Huang et al.

Fact-checking research has extensively explored verification but less so the generation of natural-language explanations, crucial for user trust. While Large Language Models (LLMs) excel in text generation, their capability for producing faithful explanations in fact-checking remains underexamined. Our study investigates LLMs' ability to generate such explanations, finding that zero-shot prompts often result in unfaithfulness. To address these challenges, we propose the Multi-Agent Debate Refinement (MADR) framework, leveraging multiple LLMs as agents with diverse roles in an iterative refining process aimed at enhancing faithfulness in generated explanations. MADR ensures that the final explanation undergoes rigorous validation, significantly reducing the likelihood of unfaithful elements and aligning closely with the provided evidence. Experimental results demonstrate that MADR significantly improves the faithfulness of LLM-generated explanations to the evidence, advancing the credibility and trustworthiness of these explanations.

Tousif Islam, Gaurav Khanna, Steven L. Liebling

Using adiabatic point-particle black hole perturbation theory, we simulate plausible gravitational wave~(GW) signatures in two exotic scenarios (i) where a small black hole is emitted by a larger one ('black hole emission') and (ii) where a small black hole is emitted by a larger one and subsequently absorbed back ('black hole absorption'). While such scenarios are forbidden in general relativity!(GR), alternative theories (such as certain quantum gravity scenarios obeying the weak gravity conjecture, white holes, and Hawking radiation) may allow them. By leveraging the phenomenology of black hole emission and absorption signals, we introduce straightforward modifications to existing gravitational waveform models to mimic gravitational radiation associated with these exotic events. We anticipate that these (incomplete but) initial simulations, coupled with the adjusted waveform models, will aid in the development of null tests for GR using GWs.

Indah Rahmayanti, Abdul Muntaqim Al Anshory, R Taufiqurrochman et al.

In the digital era, learning activities must be adapted to developments in technology and information. Teachers are required to develop learning media creatively and innovatively. This study aims to determine the use of Canva as a medium for learning Arabic reading skills for class X students at MAN Batu City, student responses to the media and evaluate the use of the advantages and disadvantages. This research approach combines both qualitative and quantitative methods, employing data gathering techniques such as observation, interviews, and questionnaires. The research data respondents were 33 class X MAN Batu City students. The questionnaire instrument uses 13 statements with a Likert scale rating of 1-5 related to the use of Canva as a medium for learning Arabic reading skills for class X IPS 1 MAN Batu City. The results of the study show that using Canva as a media for reading skills is easy to use in learning, both in class and for independent study at home. Student response in using this media is also good. This can be seen from the results of the Pearson correlations for each item above 0.2826. So that the results of the questionnaire from students are valid. The 2-tailed significance of 0.000 <0.05 means that each item is correlated. So it can be concluded that student responses are acceptable. The advantages of using Canva are being able to make learning materials that are visually interesting and the drawbacks are requiring a stable internet network.

Hafiz Saeed Imran, Muhammad Samiullah

The comprehension of the Holy Qur'an holds direct relevance to humanity. However, elucidating how an ordinary individual can directly fathom the Holy Qur'an raises pertinent questions. Considering the present state of the educational system and the intricacy of Islamic sciences, which are characterized by their complexity, difficulty, and long-term nature, the challenge becomes evident. Presently, a concerted effort is underway to devise a more accessible and engaging approach that diverges from the complexities inherent in the conventional teaching system. This innovative endeavor involves categorizing commonly used words in the Holy Quran into groups, facilitating a more streamlined memorization process and consequently easing the journey of understanding the Qur'an. Moreover, a subset of individuals has undertaken the task of elucidating Qur'anic pronouns utilizing the more advanced Total Physical Interaction (TPI) method, surpassing the initial approach in sophistication. Another contemporary technique involves clarifying the prefixes and suffixes of Qur'anic words through the strategic use of colors and symbols. This modernized method aims to enhance comprehension based on the root word, enabling readers to grasp 65% to 70% of the Qur'anic meaning by directly engaging with the text. Despite the uniqueness and modernity underpinning these initiatives, it remains premature to assess the extent to which these modern teaching methods have effectively facilitated the common man's understanding of the Qur'an. This research article critically evaluates the aforementioned techniques and methods in comparison to traditional approaches. Through a comprehensive analysis, both positive and negative aspects are considered, paving the way for the proposal of a new model. The objective is to identify the most suitable method that bridges the gap, ensuring that the layman can comprehend the profound teachings of the divine Holy book.

Muhammad Ghozy Al Fatah, Fahmi Irfanuddin

Penelitian ini bertujuan untuk mengungkap atau mengetahui frame yang dibangun oleh media asing terhadap pemberitaan kasus Obstruction of Justice yang melibatkan Irjen Ferdy Sambo serta bagaimana frame tersebut dibangun, menggunakan teknik analisis Robert N. Entman. Media sebagai the fourth estate memiliki pengaruh yang besar dalam membangun persepsi publik atas suatu peristiwa. Semakin berkembangnya teknologi informasi tentu memperbesar kemungkinan atas terbentuknya opini publik melalui media berbasis digital yang dari memiliki tingkat fleksibilitas dan aksesibilitas yang lebih besar dari media konvensional. Kasus Obstruction of Justice menjadi penting diteliti mengingat populernya kasus ini selama beberapa bulan lamanya serta bagaimana kasus ini menjadi gambaran akan penegakan keadilan di Indonesia. Penelitian ini menggunakan pendekatan kualitatif deskriptif serta mengacu pada teknik analisis framing yang dirumuskan oleh Robert Entman dengan berfokus kepada empat aspek analisis untuk dapat mengungkap frame yang dibangun oleh suatu media. Temuan penelitian berupa frame yang dibangun oleh media online asing berupa narasi Polri sebagai institusi bermasalah secara internal maupun eksternal dan kasus Obstruction of Justice serta sederet permasalahan yang menyertainya, merupakan buah dari permasalahan di tubuh Polri. Dalam hal ini media online asing menonjolkan isu budaya impunitas (culture of impunity) sebagai penyebab terhalangnya penegakan hukum di Indonesia yang terkesan tajam ke atas namun tumpul ke bawah. Kata kunci: Analisis Framing, Obstruction of Justice, Ferdy Sambo, Media Online Asing

Nazmul Islam, Seokjoo Shin

Differentiating malware is important to determine their behaviors and level of threat; as well as to devise defensive strategy against them. In response, various anti-malware systems have been developed to distinguish between different malwares. However, most of the recent malware families are Artificial Intelligence (AI) enable and can deceive traditional anti-malware systems using different obfuscation techniques. Therefore, only AI-enabled anti-malware system is robust against these techniques and can detect different features in the malware files that aid in malicious activities. In this study we review two AI-enabled techniques for detecting malware in Windows and Android operating system, respectively. Both the techniques achieved perfect accuracy in detecting various malware families.

Ansh Radhakrishnan, Karina Nguyen, Anna Chen et al.

As large language models (LLMs) perform more difficult tasks, it becomes harder to verify the correctness and safety of their behavior. One approach to help with this issue is to prompt LLMs to externalize their reasoning, e.g., by having them generate step-by-step reasoning as they answer a question (Chain-of-Thought; CoT). The reasoning may enable us to check the process that models use to perform tasks. However, this approach relies on the stated reasoning faithfully reflecting the model's actual reasoning, which is not always the case. To improve over the faithfulness of CoT reasoning, we have models generate reasoning by decomposing questions into subquestions. Decomposition-based methods achieve strong performance on question-answering tasks, sometimes approaching that of CoT while improving the faithfulness of the model's stated reasoning on several recently-proposed metrics. By forcing the model to answer simpler subquestions in separate contexts, we greatly increase the faithfulness of model-generated reasoning over CoT, while still achieving some of the performance gains of CoT. Our results show it is possible to improve the faithfulness of model-generated reasoning; continued improvements may lead to reasoning that enables us to verify the correctness and safety of LLM behavior.

Javeriah Saleem, Rafiqul Islam, Zahidul Islam

The primary objective of an anonymity tool is to protect the anonymity of its users through the implementation of strong encryption and obfuscation techniques. As a result, it becomes very difficult to monitor and identify users activities on these networks. Moreover, such systems have strong defensive mechanisms to protect users against potential risks, including the extraction of traffic characteristics and website fingerprinting. However, the strong anonymity feature also functions as a refuge for those involved in illicit activities who aim to avoid being traced on the network. As a result, a substantial body of research has been undertaken to examine and classify encrypted traffic using machine learning techniques. This paper presents a comprehensive examination of the existing approaches utilized for the categorization of anonymous traffic as well as encrypted network traffic inside the darknet. Also, this paper presents a comprehensive analysis of methods of darknet traffic using machine learning techniques to monitor and identify the traffic attacks inside the darknet.

Tunazzina Islam, Ruqi Zhang, Dan Goldwasser

Climate change is the defining issue of our time, and we are at a defining moment. Various interest groups, social movement organizations, and individuals engage in collective action on this issue on social media. In addition, issue advocacy campaigns on social media often arise in response to ongoing societal concerns, especially those faced by energy industries. Our goal in this paper is to analyze how those industries, their advocacy group, and climate advocacy group use social media to influence the narrative on climate change. In this work, we propose a minimally supervised model soup [57] approach combined with messaging themes to identify the stances of climate ads on Facebook. Finally, we release our stance dataset, model, and set of themes related to climate campaigns for future work on opinion mining and the automatic detection of climate change stances.

Tasin Islam, Alina Miron, XiaoHui Liu et al.

Our study introduces a new image-to-video generator called FashionFlow to generate fashion videos. By utilising a diffusion model, we are able to create short videos from still fashion images. Our approach involves developing and connecting relevant components with the diffusion model, which results in the creation of high-fidelity videos that are aligned with the conditional image. The components include the use of pseudo-3D convolutional layers to generate videos efficiently. VAE and CLIP encoders capture vital characteristics from still images to condition the diffusion model at a global level. Our research demonstrates a successful synthesis of fashion videos featuring models posing from various angles, showcasing the fit and appearance of the garment. Our findings hold great promise for improving and enhancing the shopping experience for the online fashion industry.

S Suharjianto, Rofi Atina Maghfiroh

Kata Jahiliyyah berasal dari kata Al Jahlu yang berarti bodoh atau kebodohan. Jaman jahiliyyah adalah jaman kebodohan. Yang dimaksud dengan jaman kebodohan di sini bukan berarti orang-orang jahiliyyah tidak memiliki kepandaian, tetapi mereka tidak dapat membedakan kebenaran dan kebatilan. Contoh yang menyolok adalah ketika salah seorang dari mereka memiliki anak perempuan, mereka akan menanamkan hidup-hidup. Kebodohan yang paling menonjol adalah karena mereka menyembah berhala yang dibuatnya sendiri. Terlepas dari arti kata di atas, paling tidak ada dua ahli yang menerangkan tentang jahiliyyah, mereka adalah Jarji Zaedan dan Munawar Cholil. Jarji Zaedan berpendapat bahwa jahiliyyah adalah jaman yang masyarakatnya telah memiliki kemajuan di berbagai bidang lapangan kehidupan, seperti: bidang sosial, budaya, ekonomi, politik, dan lain. Sedangkan Munawar Cholil pendapat yang berbeda dengan yang pertama. Menurutnya jaman jahiliyyah adalah jaman yang diatandai oleh kerusakan diberbagai bidang, seperti bidang Sosial, budaya, ekonomi, politik, dan lain-lain. Itulah dua pendapat yang berbeda ketika melihat jahiliyyah dari sisi masing-masing. Sedangkan kata jahiliyyah terdapat dalam empat ayat dalam al-Quran, yaitu pada surat Ali Imran ayat 154, surat al-Maidah ayat 50, surat al-Ahdzab ayat 33 dan surat al-Fath ayat 26. Terlepas dari dua pendapat di atas, riset ini akan mengkaji jahiliyyah dalam Tafsir al-Quran al-'Azim karya Ibnu Katsir. Pendekatan yang digunakan dalam riset ini adalah pendekatan interpretatif. Sedangkan analisis yang digunakan adalah analisis deskriptif. Adapun simpul dari riset ini adalah kata jahiliyyah dalam Tafsir al-Qurin al-'Azim merupakan (1) sangkaan buruk terhadap takdir Allah s.w.t, (2) berhukum dengan hukum lain atas hukum yang Allah syariatkan, (3) perilaku yang menjerumuskan pada perzinaan dan (4) sikap sombong sebagai hasil dari sikap fanatik yang menutup pintu kebenaran.

Alissa Aulina Rahmawati, Hendy Mustiko Aji

Purpose – This study aims to determine what factors encourage Muslim consumers to purchase non-halal MUI-certified instant noodles. Methodology – The sample for this study is selected using a purposive sampling technique with the criteria of Muslim respondents who never purchased non-halal MUI-certified instant noodles. This study collected 114 usable responses for further analysis. All data were analyzed using the PLS-SEM method. Finding – The results indicated that product knowledge has an effect on halal product awareness and intention to purchase non-halal MUI-certified Korean instant noodles. Intrinsic religiosity value does not affect halal product awareness, but halal product awareness significantly affects the intention to purchase non-halal MUI-certified Korean instant noodles. Finally, halal product knowledge positively links the purchase intention of non-halal MUI-certified Korean instant noodles. Implications – The results of this study are expected to help supermarkets, distributors, and the government to improve the supervision of products, especially Korean instant noodle products that do not yet have an MUI halal certificate. Originality – Studies that investigated intrinsic religiosity, halal product awareness, and knowledge toward purchase intention have been previously performed. However, the results are inconclusive. Besides, such studies in non-halal-certified Korean noodles are scarce. This study contributes to the literature by re-investigating these relationship in the context of non-halal-certified Korean noodles in Indonesia.

Khawar Islam, Muhammad Zaigham Zaheer, Arif Mahmood

A novel Face Pyramid Vision Transformer (FPVT) is proposed to learn a discriminative multi-scale facial representations for face recognition and verification. In FPVT, Face Spatial Reduction Attention (FSRA) and Dimensionality Reduction (FDR) layers are employed to make the feature maps compact, thus reducing the computations. An Improved Patch Embedding (IPE) algorithm is proposed to exploit the benefits of CNNs in ViTs (e.g., shared weights, local context, and receptive fields) to model lower-level edges to higher-level semantic primitives. Within FPVT framework, a Convolutional Feed-Forward Network (CFFN) is proposed that extracts locality information to learn low level facial information. The proposed FPVT is evaluated on seven benchmark datasets and compared with ten existing state-of-the-art methods, including CNNs, pure ViTs, and Convolutional ViTs. Despite fewer parameters, FPVT has demonstrated excellent performance over the compared methods. Project page is available at https://khawar-islam.github.io/fpvt/

Zubayer Islam, Mohamed Abdel-Aty

In this work, we focus on detecting emergency vehicles using only audio data. Improved and quick detection can help in faster preemption of these vehicles at signalized intersections thereby reducing overall response time in case of emergencies. Important audio features were extracted from raw data and passed into extreme learning machines (ELM) for training. ELMs have been used in this work because of its simplicity and shorter run-time which can therefore be used for online learning. Recently, there have been many studies that focus on sound classification but most of the methods used are complex to train and implement. The results from this paper show that ELM can achieve similar performance with exceptionally shorter training times. The accuracy reported for ELM is about 97% for emergency vehicle detection (EVD).

Suhaimi Suhaimi

Salah satu gaya bahasa yang ditunjukkan Allah swt dalam menyampaikan pesan-pesan suci-Nya dalam Al-Quran adalah dengan menggunakan qasam atau sumpah. Siapa saja yang membaca dan meneliti Al-Quran tentu saja dia pasti mendapati ungkapan yang mengandung sumpah Allah dalam berbagai variasinya, semua itu tidaklah merupakan suatu kebetulan, melainkan memiliki maksud-maksud atau tujuan tertentu yang seharusnya menjadi perhatian bagi siapapun yang meyakini Al-Quran itu sebagai Kalam Allah yang menjadi petunjuk dalam hidup dan kehidupan ini. Bagaimana dan dengan apa Allah bersumpah? mengapa Allah bersumpah? dan apa rahasia dan manfaat sumpah yang terdapat dalam Al-Quran tersebut?. Tulisan sederhana ini diupayakan untuk dapat menjawab berbagai masalah tersebut dengan menelusuri pandangan para ulama Al-Quran dalam berbagai kitab yang mereka wariskan dengan harapan dapat menjadi pelajaran yang berharga untuk lebih meningkatkan pemahaman kita terhadap Al-Quran itu sendiri. Secara umum dapat dikatakan bahwa sumpah Allah dalam Al-Quran tidak terlepas dari pada isyarat yang jelas agar kita sungguh-sungguh memperhatikan pesan-pesan yang disampaikan, karena pesan yang disampaikan mengandung tujuan untuk kebaikan dan kebahagiaan manusia di dunia dan di akhirat.