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Transformational Leadership of Kiai: Efforts to Strengthen Teacher Performance at the Hidayatul Mubtadiien Islamic Boarding School in South Lampung Muhammad Abdul Aziz; Rahmat; Fathi Hisyam Panagara
al-Afkar, Journal For Islamic Studies Vol. 9 No. 2 (2026)
Publisher : Perkumpulan Dosen Fakultas Agama Islam Indramayu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31943/afkarjournal.v9i2.3372

Abstract

The quality of education in Indonesia faces serious challenges related to low teacher competency, and teacher performance in Islamic boarding schools (pesantren) is inextricably linked to the way leadership authority shapes commitment, discipline, and organizational rhythm. This article aims to explore the articulation of the kiai's transformational leadership in improving the performance of educators at the Hidayatul Mubtadiien Islamic Boarding School in South Lampung. Using a qualitative single-case study method, data were collected in depth to examine the dynamics of leadership in the field. The results show that the dimensions of ideal influence, inspirational motivation, and individual attention are operationalized through the integration of strong religiosity values ​​as a form of spiritual "energy transfer." The novelty of this study lies in the mechanism of transforming kiai authority into a collective work tool that fosters discipline and innovation without eroding the tradition of the salaf. The implications of this research emphasize the importance of synergy between spiritual leadership and modern management to address quality incompatibilities in traditional educational institutions. This study provides a theoretical contribution to the development of an Islamic educational leadership model that is adaptive to global dynamics.
Implementation of CNN Method with Otsu Thresholding Preprocessing for Pneumonia Detection Surya Afriza; Noval Aditya Candra Pratama; Muhammad Abdul Aziz; Faisal Muttaqin
JITTER: Jurnal Ilmiah Teknologi dan Komputer Vol. 7 No. 1 (2026): JITTER, Vol.7, No.1, April 2026
Publisher : Program Studi Teknologi Informasi, Fakultas Teknik, Universitas Udayana

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Abstract

Pneumonia is a lung infection requiring rapid diagnosis to prevent fatal complications, yet X-ray image quality often hinders manual detection accuracy. This study proposes a hybrid approach using a Convolutional Neural Network (CNN) optimized with Otsu Thresholding for lung area (Region of Interest) segmentation. Experiments were conducted on 1,840 images from a secondary dataset. Evaluation results demonstrate a highly balanced and superior model performance, achieving 96% Recall, 91% F1-Score, and 96% Accuracy. The alignment between accuracy and recall values indicates that the model possesses equally good sensitivity and specificity in detecting both positive and negative cases. These findings prove that Otsu pre-processing effectively assists the CNN in focusing on pathological features, making this method a promising automated diagnostic solution.
Artificial Intelligence in Istinbat Al-Hukm from Muamalah Hadiths: a Fiqh and Library-Based Analysis Muhmmad Irkham Firdaus; Muhammad Abdul Aziz; M. Abdurrozaq
MADINAH Vol 13 No 1 (2026): Madinah: Jurnal Studi Islam
Publisher : INSTITUT AGAMA ISLAM TARBIYATUT THOLABAH LAMONGAN, INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58518/madinah.v13i1.4632

Abstract

The complexity of Hadith verification and the current diversity of schools of thought (madhhab) necessitate Artificial Intelligence (AI)-based solutions to provide a more efficient, structured, and unbiased analysis. The integration of AI raises fundamental questions regarding the normative authority of its legal outcomes, specifically whether AI can replace the role of a Mujtahid, who possesses intellect (aql) and intention (niyyah). Therefore, this study aims to analyze the shar'i ruling on the use of AI from a Fiqh perspective, focusing on three areas: mapping the technical capabilities of AI in Hadith and Usul Fiqh analysis, assessing the shar'i legal validity of AI products as either a hukm (binding ruling) or a wasīlah (aid/tool), and formulating an Islamic ethical framework (Akhlaq) for its development. This study employs a qualitative research method with a library research approach, comprehensively analyzing and interpreting data from primary and secondary literature, academic journals, and publications from fatwa institutions related to Usul Fiqh, technological ethics, and the implementation of AI in the religious field. Data analysis is conducted using a descriptive-analytical technique, where data concerning AI capabilities and Usul Fiqh principles are collected, classified, and critically analyzed to produce a systematic legal synthesis and ethical framework. The results of this study explain that the utilization of Artificial Intelligence (AI) in Istinbāṭ al-Hukm is fundamentally permissible (mubah) as it supports the principles of Taisīr (ease) and Maslahah (public interest), making it an effective aid (wasīlah) for technical tasks such as sanad verification, data classification, and the analysis of Qat'i al-Dilālah Hadiths. However, the outcomes of istinbāṭ ḥukm generated by AI cannot be accepted as shar'i-ly binding legal decisions. This is because the authority of Ijtihād is inherently attached to humans, which is essential for understanding the Maqāṣid al-Sharī‘ah. Consequently, AI output must be treated as logical predictions that must be validated by a human Mujtahid. Furthermore, the use of AI is prohibited for Muamalah Hadiths, as the proofs (dalil) in muamalah fall under the category of Ẓannī al-Dilālah (speculative in meaning), which lack a single, clear, or direct definitive meaning, thus requiring further analysis, interpretation, or explanation to understand their true intended meaning.