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All Journal Journal La Multiapp Ilmu Komputer untuk Masyarakat
Huda, Besse Nurul
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Pendampingan dan Penerapan Augmented Reality (AR) dalam Meningkatkan Kompetensi Guru TK/TPA Nurul Iman Pannara pada Pengajaran Huruf Hijaiyah Fattah, Farniwati; Sugiarti, Sugiarti; Wahab, Abdul; Irawati, Irawati; Hayati, Lilis Nur; Huda, Besse Nurul; Bora, Leni J; Munawir, Munawir
Ilmu Komputer untuk Masyarakat Vol 6, No 2 (2025)
Publisher : Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkomas.v6i2.3121

Abstract

Pengabdian masyarakat ini dilaksanakan di TPA Nurul Iman Pannara, Kota Makassar, yang menghadapi keterbatasan dalam pemanfaatan teknologi digital pada pembelajaran huruf hijaiyah. Kegiatan dilakukan melalui pelatihan, pendampingan, dan praktik penggunaan aplikasi Augmented Reality (AR) kepada 21 guru dan asisten guru. Aplikasi AR ini menampilkan 30 huruf hijaiyah dalam bentuk tiga dimensi (3D), dilengkapi audio pelafalan, menu petunjuk, serta kuis interaktif untuk menguji pemahaman santri. Hasil implementasi menunjukkan adanya peningkatan kompetensi guru dalam mengoperasikan teknologi AR serta munculnya variasi metode pembelajaran yang lebih menarik dan interaktif. Bagi santri, penggunaan aplikasi AR mempermudah pemahaman bentuk huruf, meningkatkan motivasi belajar, serta memperkuat daya ingat melalui visualisasi tiga dimensi. Evaluasi dengan kuesioner terhadap 19 responden menghasilkan skor rata-rata 4,25 (kategori tinggi), yang menegaskan respon positif terhadap penggunaan aplikasi ini. Dengan demikian, kegiatan ini berhasil meningkatkan kompetensi guru sekaligus efektivitas pembelajaran huruf hijaiyah, serta mendukung transformasi digital pendidikan nonformal.
Comparative Analysis of the Certainty Factor and Dempster-Shafer Methods in the Diagnosis of Acute Respiratory Infection in Childern Huda, Besse Nurul; Mansyur, St. Hajrah; Anraeni, Siska
Journal La Multiapp Vol. 7 No. 1 (2026): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v7i1.2920

Abstract

Acute Respiratory Infections (ARI) are one of the diseases that often affect children and are a major cause of morbidity and mortality in Indonesia. Accurate early diagnosis is very important to prevent complications, but limited medical personnel and the similarity of ARI symptoms to other diseases are often obstacles. In this context, an artificial intelligence-based expert system can be a solution to support medical decisions. This article presents a comparative analysis of two inference methods commonly used in expert systems, namely Certainty Factor (CF) and Dempster-Shafer (DS). Through a Systematic Literature Review (SLR) approach, this study evaluates the performance of both methods based on accuracy, complexity, flexibility, and ease of implementation. The results of the study show that Certainty Factor excels in simplicity and efficiency, while Dempster-Shafer is more reliable in handling uncertainty and cases with many overlapping symptoms. This article is expected to be a reference for the development of more accurate and efficient medical expert systems in assisting the diagnosis of ARI in children.
Co-Authors Abdul Wahab Bora, Leni J Fattah, Farniwati Irawati Irawati lilis nurhayati Mansyur, St. Hajrah Munawir Munawir Siska Anraeni Sugiarti Sugiarti