Article Per Year (5 Year)
p-Index From 2021 - 2026
0.562
P-Index
This Author published in this journals
All Journal Iqtisad : Journal of Islamic Economic and Civilization
Joko Sarono
Universitas Saintek Muhammadiyah, Jakarta, Indonesia
Religion Economics, Econometrics & Finance

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Design and Evaluation of AI-Based Musyarakah Sales System at UMKM XYZ Tangerang Bambang Judi Bagiono; Nasirudin Nasirudin; Joko Sarono
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 | DOI: 10.61630/ijiec.v2i1.20

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 Bambang Judi Bagiono; Joko Sarono; 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 | DOI: 10.61630/ijiec.v2i1.24

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 Bambang Judi Bagiono; Nasirudin Nasirudin; Joko Sarono
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 | DOI: 10.61630/ijiec.v2i1.25

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 Bambang Judi Bagiono Nasirudin Nasirudin