Article Per Year (5 Year)
p-Index From 2021 - 2026
2.439
P-Index
This Author published in this journals
All Journal E-Jurnal Ekonomi Sumberdaya dan Lingkungan Nadwa : Jurnal Pendidikan Islam Dialogia: Jurnal Studi Islam dan Sosial Scholastica : Jurnal Pendidikan dan Kebudayaan Jurnal Rekayasa Lingkungan PAKAR Pendidikan Journal of Correctional Issues (JCI) Action Research Literate (ARL) Journal of Integrated Elementary Education Jurnal Komputer dan Teknologi (JUKOMTEK) Iqtisad : Journal of Islamic Economic and Civilization Halaqa: Journal of Islamic Education Research Journal on Teacher Professional Development
Nasirudin Nasirudin, Nasirudin
Unknown Affiliation
Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Social Sciences Other

Published : 36 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 36 Documents
Search

 1   2   3   4 
Waste-to-Energy Modeling via Digital Algorithms Based on  Faith-Based Cleanliness and Educati Bagiono, Bambang Judi; Nasirudin, Nasirudin
Halaqa: Journal of Islamic Education Vol. 2 No. 1 (2026): Halaqa : Journal of Islamic Education
Publisher : PT. Student RIhlah Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61630/hjie.v2i1.41

Abstract

This research examines the integration of Islamic cleanliness principles into digital algorithm modeling as a conceptual foundation for ethical system design. In Islamic thought, cleanliness encompasses not only physical purity but also moral intention, cognitive clarity, and structural order, as articulated by Al-Ghazali. The objective of this study is to formulate a value-based digital algorithm framework grounded in these principles. The research employs a qualitative conceptual methodology through critical literature review of classical Islamic scholarship and contemporary digital modeling and algorithm studies published within the last decade. The results demonstrate that Islamic cleanliness principles can be systematically translated into algorithmic stages, including purified input selection, integrity-driven processing, and accountable output validation. The discussion indicates that this approach introduces an ethical and spiritual dimension absent from most conventional algorithmic models. The novelty of this study lies in its interdisciplinary synthesis of Islamic ethical philosophy and formal digital system modeling. The findings have important policy implications for ethical artificial intelligence, digital governance, and education systems, particularly in culturally and religiously contextualized environments. This research is significant as it provides an original conceptual contribution to the development of responsible and value-oriented digital transformation.
Modeling Lamastum Parameter–Variable Systems Using Lagrange Deep Learning Methodologies for Education and Life Sciences Bagiono, Bambang Judi; Nasirudin, Nasirudin; Abuzar, Asra
Halaqa: Journal of Islamic Education Vol. 2 No. 1 (2026): Halaqa : Journal of Islamic Education
Publisher : PT. Student RIhlah Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61630/hjie.v2i1.46

Abstract

The significant progress of Artificial Intelligence (AI), particularly within Deep Learning paradigms, has enabled the exploration of new frameworks for representing language as symbolic and semantic systems. Contemporary AI is no longer confined to numerical computation but increasingly addresses the complexity of meaning embedded in linguistic structures..One of the main challenges in educational AI is how to model non-numerical parameters and variables—such as language, conceptual meaning, and ethical values—within mathematical systems that remain computationally optimizable. This study proposes modeling the word “Lamastum” as a system of semantic parameters and variables using a Lagrange Deep Learning approach. The Lagrange method is employed to link learning objective functions with constraints related to values, ethics, and life contexts through constrained optimization formulations . The Lagrangian approach enables simultaneous integration of learning objectives and humanistic. The results indicate that this approach can represent interactions among linguistic meaning, educational goals, and real-life contexts in a more structured and adaptive manner. The proposed model has the potential to serve as a new conceptual framework for the development of humanistic AI oriented toward sustainable education and character formation Originally developed for constrained mathematical optimization, the Lagrangian approach has been increasingly adopted in contemporary AI research to integrate human-centered constraints into machine learning systems.  
Kesehatan Mental Perspektif Abu Zaid Al-Balkhi dan Implikasinya terhadap Pendidikan Karakter di Era Digital Hakim, Muhammad Abdul Rahman; Nasirudin, Nasirudin; Lutfiyah, Lutfiyah
PAKAR Pendidikan Vol 24 No 1 (2026): Published in January 2026
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/pakar.v24i1.869

Abstract

Mental health is the cornerstone of developing a well-rounded and high-quality character, especially in the digital age, which is marked by social media pressure, instant gratification expectations, and identity crises. This study aims to analyze the thoughts of Sheikh Abu Zaid al-Balkhi in his book Maṣāliḥ al-Abdān wa al-Anfus (The Well-being of the Body and Soul) and to examine its implications for character education in the digital age. This study employs a descriptive qualitative approach based on library research, with content and discourse analysis of primary texts and contextual data. The findings reveal that al-Balkhi divides mental health into preventive and curative functions, grounded in the balance between physical aspects (al-abdān), spiritual aspects (al-anfus), rationality, and spirituality. The implications of these findings in humanistic-oriented education encourage the development of empathetic, resilient, and reflective character, as indicated by Maslow's basic needs such as safety, love, self-esteem, and self-actualization. Meanwhile, in a holistic approach, al-Balkhi's thinking aligns with Miller's emphasis on integrative character education, encompassing cognitive, affective, psychomotor, and spiritual aspects, thereby producing intellectually and emotionally balanced character. Indicators include emotional management skills, moral stability, healthy social relationships, and spiritual reflection. The conclusion of this study affirms that al-Balkhi's ideas are highly relevant as a foundation for character education in the digital age, blending classical Islamic approaches and modern psychological theories within a humanistic, holistic educational framework.
Design and Evaluation of AI-Based Musyarakah Sales System at UMKM XYZ Tangerang Bagiono, Bambang Judi; Nasirudin, Nasirudin; Sarono, Joko
Iqtisad: Journal of Islamic Economic and Civilization Vol. 2 No. 1 (2026): Iqtisad : Journal of Islamic Economic and Civilization (In Progress)
Publisher : PT. Student Rihlah Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The rapid development of digital technology and Artificial Intelligence (AI) has significantly transformed business governance, particularly among Micro, Small, and Medium Enterprises (MSMEs). Sharia-based MSMEs applying musyarakah contracts frequently face managerial challenges due to manual transaction recording and profit-sharing calculations, leading to computational errors, reporting delays, and limited transparency. This study designs and evaluates an AI-based remotized musyarakah sales management system at UMKM XYZ Tangerang using a compound percentage method. A mixed-methods approach was employed, involving observation, in-depth interviews, and financial document analysis. The system was tested over a 12-month period, analyzing 1,080 sales transactions (540 before and 540 after implementation). The web-based platform enables partners to remotely monitor real-time sales and profit-sharing data. The compound percentage method calculates profit distribution proportionally based on capital contribution, operational involvement, and managerial responsibility. Quantitative results show that profit-sharing calculation accuracy increased from 88% to 97%, reporting time decreased by 35%, and financial discrepancies were reduced by 42%. Revenue forecasting accuracy reached 93% using machine learning models. Operational efficiency improved by 30%, while partner satisfaction scores increased from 3.4 to 4.5 (on a 5-point scale). These findings demonstrate that integrating Islamic financial principles with AI-driven systems enhances transparency, efficiency, and sustainable Sharia-compliant MSME growth.
AI-Based Break-Even Optimisation within an Ethical Reflective Framework Bagiono, Bambang Judi; Sarono, Joko; Nasirudin, Nasirudin
Iqtisad: Journal of Islamic Economic and Civilization Vol. 2 No. 1 (2026): Iqtisad : Journal of Islamic Economic and Civilization (In Progress)
Publisher : PT. Student Rihlah Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Break-even management is essential for ensuring business sustainability, pricing fairness, and financial accountability, particularly in environments that demand ethical governance. However, conventional break-even analysis is typically static and lacks adaptive optimisation and structured feedback mechanisms. This study aims to develop an AI-based prototype system for optimising break-even variables within an ethical reflective framework that integrates predictive modelling, constrained optimisation, and governance-based feedback. The methodology combines multiple linear regression and exponential smoothing for revenue forecasting, followed by nonlinear optimisation (SLSQP) to minimise time-to-break-even subject to ethical guardrails, including margin floor and price-smoothing constraints. Simulation results show that the prototype improves forecast accuracy (MAPE reduced from 9.45% to 4.87%) and decreases time-to-break-even from 12.4 to 9.8 months (−21%), while reducing deviation variance from 11% to 5.2% through iterative feedback. The novelty lies in embedding ethical accountability constraints into AI-driven optimisation, offering policy implications for transparent pricing, accountable financial planning, and governance-aligned business decision-making.
AI-Based Prototype for Identifying Murabahah, Ujroh, Nisbah Variables Using Quran-Hadith Foundations Bagiono, Bambang Judi; Nasirudin, Nasirudin; Sarono, Joko
Iqtisad: Journal of Islamic Economic and Civilization Vol. 2 No. 1 (2026): Iqtisad : Journal of Islamic Economic and Civilization (In Progress)
Publisher : PT. Student Rihlah Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study is important because Murabahah, Ujroh, and Nisbah contracts form the backbone of contemporary Islamic banking, yet their variables are often implemented without computationally verifiable links to primary Quran–Hadith foundations. The objective of this research is to develop and evaluate an AI-Based Prototype for Identifying Murabahah, Ujroh, and Nisbah Variables Using Quran-Hadith Foundations in order to enhance transparency, consistency, and doctrinal authenticity in Islamic financial transactions. The study employs a hybrid methodological framework combining natural language processing (NLP), semantic classification, supervised machine learning, and rule-based inference, integrated with Shariah expert validation. Textual data derived from the Qur'an and authenticated Hadith literature are processed to extract jurisprudential concepts and convert them into measurable contractual parameters. The results indicate that the prototype successfully identifies core variables, including cost disclosure and profit margin (Murabahah), service fee structure and duration (Ujroh), and proportional profit-sharing ratios and risk allocation (Nisbah). Statistical validation demonstrates consistent classification accuracy and alignment with Shariah expert assessments. The novelty of this research lies in integrating foundational Islamic textual analysis directly into an AI computational model, rather than relying solely on contemporary regulatory interpretations. Policy implications include supporting regulators, Shariah supervisory boards, and Islamic financial institutions in developing standardized AI-assisted compliance frameworks, thereby strengthening governance, transparency, and digital transformation in Islamic finance.
Co-Authors Aang Kunaepi Abuzar, Asra Ahmad Fanani Akhsin Zulkoni Bambang Judi Bagiono Bernanetha, Prilly Darmalingganawati, Darmalingganawati Dewi, Lestari Retna Djoko Marsono Fachri, Mohamad Hakim, Muhammad Abdul Rahman Indriyanti Octavia, Dina Kusuma Admaja, Wikan Lutfiyah Lutfiyah Marzuki, Arifuat Musthofa Musthofa Nasikhin, Nasikhin Panaemale, Abdul Razak Abdulraya Prihandoko, Diananto Radjali Amin Rahyuni, Dewi Rini Setiawati Rukmini Rukmini Saefudin, Wahyu Sarono, Joko Sidiq, Ahmad Fajar Silviani, Silviani Sitomo, Rizky Sriwinarno, Handayani Subana, Bambang Sudarmaji, Waluyo Sudibiyakto Sudibiyakto Sutrisno, Sutrisno Syahputri, Yasinta Daniar Tandjung, Shalahuddin Djalal Triastanti, Rita Dewi Windarto, Windarto