Journals of Universiti Tun Hussein Onn Malaysia (UTHM)
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Reconciling Faith and Reason: Al-Bouti’s Defence of Roger Garaudy in the Context of Apostasy and Islamic Jurisprudence
Get PDFThis paper is, in a way, an assessment of an apologia of the offence of hadd written by Muhammad Said Ramadan al-Bouti (1929-2013) to defend Roger Garaudy (1913-2012) against the accusation of apostasy. It analyses the evidence presented by al-Bouti to support his arguments for exonerating Garaudy. Al-Bouti was a prominent Syrian scholar and one of the most influential Islamic jurists in the contemporary Arab world, and a Shafi’i jurist who believed in applying independent reasoning in his interpretation of rulings. In his efforts to preserve the Sufi concept of ‘interior form’ and ‘exterior behaviour’, al-Bouti combines the spirituality of Sufism with traditional legal rulings of fiqh to derive the power of a believer’s conformity with the Sharia. It was this hypothesis of reconciling Islamic mysticism with fiqh that helped his work to gain currency in the Islamic world. Roger Garaudy (1913-2012), on the other hand, was a French Marxist philosopher who converted to Islam in 1982/83, at the age of 70. His conversion to Islam was perceived in the West as indicating “the superiority of Islam over the West”. For this reason, the attack of Western scholars on him was interpreted as part of the West’s attack on Islam. However, Garaudy faced widespread criticism in the Muslim world after publishing his book Islam, to the extent that Muslim authors began to question the orthodoxy of his beliefs. The strongest assault came from the Saudi journal al-Mujallah in 1996, after Garaudy was interviewed by its correspondent in Paris. The article claims that Garaudy’s conversion to Islam was more or less superficial. This paper introduces brief details of al-Bouti’s life and his intellectual impact. Similarly, it highlights the Garaudy affair, his impact in the Muslim world, and the historical origin of the kufr accusation. Finally, it explores the main argument of al-Bouti in his defense case, making particular reference to the al-Mujallah article.
iHaji VR Simulasi: Pembangunan Aplikasi Simulasi Ibadah Haji Menggunakan Teknologi Realiti Maya
Get PDFIbadah Haji merupakan salah satu daripada lima rukun Islam dan wajib dilaksanakan oleh umat Islam yang berkemampuan. Namun, kaedah pembelajaran sedia ada seperti penggunaan buku teks dan video kurang mengandungi elemen interaktif dan imersif untuk memenuhi keperluan pembelajaran generasi kini. Oleh itu, aplikasi iHaji VR Simulasi telah dibangunkan menggunakan teknologi realiti maya (VR) sebagai alternatif pembelajaran Haji yang lebih menarik dan praktikal. Aplikasi ini dibangunkan untuk platform Android dengan menggunakan metodologi TRES-D sebagai pendekatan pembangunan, dan mengandungi dua modul utama, iaitu Modul Simulasi, yang membimbing pengguna melalui rukun dan wajib Haji secara maya, serta Modul Ziarah, yang membolehkan penerokaan lokasi penting seperti Masjidil Haram dan Padang Arafah. Gabungan elemen audio, visual dan interaktif digunakan bagi menghasilkan pengalaman pembelajaran yang lebih realistik dan imersif. Hasil ujian penerimaan pengguna menggunakan kaedah Skala Kebolehgunaan Sistem (SUS) menunjukkan skor purata 82.50, yang berada dalam kategori cemerlang, menunjukkan bahawa aplikasi iHaji VR Simulasi mempunyai tahap kebolehgunaan yang tinggi dan mesra pengguna. Secara keseluruhannya, iHaji VR Simulasi berpotensi besar dalam membantu pengguna memahami dan menghayati pelaksanaan ibadah Haji secara lebih mendalam melalui pengalaman maya yang interaktif
Lancar Solat: Aplikasi Hafazan Bacaan dalam Solat untuk Kanak-kanak Autisme
Get PDFSolat merupakan rukun Islam kedua dan wajib dilaksanakan setiap individu Muslim. Kanak-kanak autisme tidak diwajibkan menunaikan solat namun pendedahan awal pembelajaran solat amat penting. Kanak-kanak autisme biasanya mempelajari solat dengan mendengar dan mengulangi bacaan solat untuk membantu mereka mengingat. Walaubagaimanapun, aplikasi pembelajaran solat bagi kanak-kanak autisme masih terhad. Kebanyakan aplikasi sedia ada hanya memfokuskan kepada aspek pembelajaran solat secara umum tanpa menekankan kepada kaedah hafazan bacaan dalam solat. Oleh itu, aplikasi Lancar Solat dicadangkan bertujuan membangunkan aplikasi pembelajaran berasaskan permainan untuk membantu kanak-kanak autisme dalam menghafaz bacaan dalam solat. Kaedah tikrar iaitu kaedah hafazan secara ulangan digunakan dalam aplikasi ini. Metodologi Pembangunan Kandungan Mudah Alih Multimedia (MMCD) digunakan dalam pembangunan aplikasi ini. Hasil keputusan pengujian pengguna menggunakan kaedah Skala Kebolehgunaan Sistem (SUS) menunjukkan skor yang cemerlang iaitu 79.38. Hasil ini membuktikan aplikasi ini diterima oleh pengguna dari segi aspek kebolehgunaannya
Peranan Al-Quran dalam Pembentukan Emosi Sosial Remaja: The Role of the Quran in the Formation of Social Emotions Teenagers
Get PDFMalay:
Kajian ini bertujuan untuk meneroka peranan Al-Quran dalam pembentukan emosi sosial dalam kalangan remaja dengan memberikan fokus kepada bagaimana ajaran Al-Quran dapat membentuk tingkah laku dan nilai sosial yang positif dalam kalangan anak muda pada masa kini. Remaja merupakan kelompok yang sedang mengalami fasa transisi dalam kehidupan. Mereka sering terdedah kepada pelbagai pengaruh luar yang tanpa disedari telah mempengaruhi dalam pembentukan nilai dan moral mereka. Dalam konteks ini, Al-Quran sebagai sumber utama ajaran Islam mempunyai potensi yang besar untuk memberikan panduan dalam membentuk etika sosial yang baik termasuk nilai-nilai seperti kejujuran, hormat, tanggungjawab dan kasih sayang. Kajian ini akan menganalisis ayat-ayat Al-Quran yang berkaitan dengan aspek akhlak dan emosi serta bagaimana ajaran al-Quran dapat diterjemahkan dalam kehidupan seharian remaja melalui pendidikan, keluarga dan masyarakat. Kajian ini juga dilakukan berbentuk kepustakaan dengan meninjau kajian-kajian lepas yang berkaitan. Di samping itu, kajian ini juga akan menilai keberkesanan program dakwah dan pendidikan Islam dalam memupuk nilai-nilai ini dalam kalangan remaja. Hasil kajian ini diharapkan dapat memberikan sumbangan dalam usaha meningkatkan kesedaran emosi sosial remaja dan memperkukuhkan penerapan ajaran Islam dalam kehidupan mereka.
English:
This study aims to explore the role of the Qur’an in shaping social emotions among adolescents, with a particular focus on how Qur’anic teachings can cultivate positive behaviours and social values in today’s youth. Adolescents represent a group undergoing a transitional phase in life and are often exposed to various external influences that, consciously or unconsciously, shape their values and moral development. In this context, the Qur’an, as the primary source of Islamic teachings, holds significant potential in guiding the formation of sound social ethics, including values such as honesty, respect, responsibility, and compassion. This study analyses selected Qur’anic verses related to moral and emotional aspects and examines how these teachings can be translated into the daily lives of adolescents through education, family, and community engagement. Employing a library-based research design, this study reviews relevant past literature and further evaluates the effectiveness of Islamic educational and dakwah programmes in nurturing these values among youth. The findings of this study are expected to contribute to enhancing adolescents’ social-emotional awareness and strengthening the application of Islamic teachings in their everyday lives
Cu and CuO Nanoparticles in Heat Transfer Applications: A Comprehensive Review
Get PDFThis review highlights the role of Copper (Cu) and Copper Oxide (CuO) nanoparticles in enhancing heat transfer through mono, binary, and ternary nanofluids. Mono nanofluids consistently improved thermal conductivity, viscosity, pressure drop, and heat transfer coefficient, with higher gains at higher concentrations. Binary systems showed synergistic effects, with CuO–MWCNT yielding maximum conductivity, CuO–TiO₂ showing Newtonian behavior, and Cu with Al₂O₃ and TiO₂ achieving peak conductivity at a 40:40:20 ratio. Ternary mixtures of Cu, CuO, and Al₂O₃ offered further conductivity enhancement but with larger pressure drops, notably at 60:20:20. Overall, nanoparticle selection, base fluid, and mixing proportion are key to balancing thermal performance with hydrodynamic penalties.
Glycerolysis-Based Reduction of Free Fatty Acids in Crude Palm Oil (CPO) for Cost Effective Biodiesel Pre-Treatment
Get PDFThe high content of free fatty acids (FFA) in crude palm oil (CPO) presents a significant challenge for biodiesel production. This study investigates the glycerolysis pretreatment method using crude glycerol and potassium hydroxide (KOH) to reduce FFAs. Experiments were performed at varying molar ratios (1:3 to 1:9) and temperatures (60°C to 80°C). Results showed optimal FFA reduction at a 1:7 molar ratio and 80°C, reducing FFA below 5% within 60 minutes. FTIR analysis confirmed FFA conversion. The reaction followed a pseudo-second-order kinetic model (R² = 0.9832). Viscosity and density of the oil improved to 41.2 mPa·s and 0.886 g/cm³, respectively. These findings demonstrate that glycerolysis is a promising, eco-friendly, and cost-effective solution for pretreating high-FFA feedstock in biodiesel production
Optimisation of NaOH Concentration for Sustainable Soap Production Using Waste Cooking Oil
Get PDFThis study presents a sustainable approach for synthesizing soap bars from WCO. The process involves collecting and filtering WCO, followed by an optimized saponification reaction using alkaline, resulting in soap bars with desirable properties. Comparative analysis reveals that WCO appears darker, with higher free fatty acid content (4.00%) and slightly increased viscosity (79.13 cP) compared to new cooking oil. The study highlights the significant impact of NaOH concentration on soap consistency, where 10% NaOH concentration (sample BS3) has achieved the most stable foam formation. BS3 has no appearance of a gel phase upon cutting and shows 1.78% moisture content. This research emphasizes the utilization of waste cooking oil as a valuable resource for soap production, contributing to waste reduction and supporting sustainable practices within the circular economy framework
Oil Absorption Analysis of Vegetable Oil onto Kapok Fiber Using pH and Temperature
Get PDFOil spills pose serious environmental and economic threats, driving the search for sustainable sorbent materials. This study examines the effect of pH and temperature on the oil absorption performance of treated kapok fiber, a natural and hydrophobic material with a hollow tubular structure. Kapok fibers were treated and tested under varying pH (3, 7, and 11) and temperature (40 °C and 70 °C) conditions using coconut and canola oils. Characterization through SEM, FTIR, and contact angle analysis revealed that alkaline treatment effectively removed surface waxes, improving oil affinity while maintaining structural integrity. The highest oil uptake occurred under alkaline conditions (pH 11) and elevated temperature, indicating enhanced sorption efficiency. These results demonstrate the potential of chemically treated kapok fiber as an eco-friendly sorbent for oil spill remediation applications
An Intelligent Botnet Detection System for IoT Using Neural Networks and an Enhanced Moth Search Optimize
Get PDFBotnets, distributed networks of compromised devices under remote control, continue to pose a serious cybersecurity threat, as they are challenging to detect with traditional methods because of their evasion capabilities. The evolving nature of botnets demands stronger detection systems that can effectively detect malicious traffic patterns. To confront this problem, we introduce a new botnet detection framework called BDS (Botnet Detection System), aimed at improving the accuracy of detection and reducing the number of false positive results. We integrate the Enhanced Moth Search Algorithm (EMSA) with Multi-Layer Perceptron (MLP) for the enhancement of training of the neural network model, titled EMSA-MLP. For this, we test our model with a representative Bot-IoT dataset with diverse botnet attack scenarios in terms of separating honest and malicious traffic with the help of efficient optimization by EMSA. To assess the proposed EMSA-MLP, the Bot-IoT benchmark dataset was used, containing a variety of botnet attack methods. The detection performance of the model was demonstrated to be excellent. The model achieved a high detection performance in identifying botnet attacks, with an accuracy rate of 97.09%. They also preserved a good accuracy of 91.59%, and their false alarm rate was kept low at 0.0291. Overall, compared to some common classifiers: random forest, decision tree, and base MLP-this model did pretty well. It also outperformed relatively newer and more complex models. This architecture has achieved good accuracy, while it has not made the growth of IoT settings very large, and it has been formulated to be used by devices. This model provides high accuracy without burdening the IoT infrastructure, so it is applicable to devices with restricted capabilities. It is suited for practical applications, as it can adapt to different types of data
The Use of Transformer-Based Models for Automatic Short-answer Scoring in Education: A Systematic Literature Review
Get PDFThis review focuses on recent advancements in the Automatic Short-Answer Scoring (ASAS) system in education. The primary objective of this review is to identify current trends in utilizing transformer-based models for the ASAS system. This review also aims to discuss future directions for ASAS technology. ASAS’s conventional machine learning methods were inconsistent because they rely on statistical similarity and are prone to bias. Meanwhile, transformer-based models were typically used for feature extraction, embedding, and score calculation via classification or regression. They generally served as a similarity calculator comparing students’ answers to the reference answer. We applied the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework to explore ASAS’s state of the art and uncover its future trends. Our findings reveal that transformer-based models significantly outperform traditional machine learning approaches by capturing complex context. On the other hand, LLMs excel at providing feedback and score justification. Recent studies have shown a shift toward using transformer-based models for ASAS’s complex tasks, including data augmentation and feedback generation. However, further research is needed to use LLMs and GPTs to generate explainable, fairer scores and to address data scarcity through reasoning and augmentation