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All Journal JURNAL TEKNOLOGI DAN OPEN SOURCE Journal of Education and ICT
Taufiq Agung Cahyono
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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PENGEMBANGAN MEDIA PEMBELAJARAN PENGENALAN BINATANG MENGGUNAKAN AUGMENTED REALTY BERBASIS ANDROID PADA MATA PELAJARAN BAHASA INGGRIS Hendri Novantrias; Taufiq Agung Cahyono
JoEICT (Jurnal of Education And ICT) Vol 5, No 2 (2021)
Publisher : STKIP PGRI TULUNGAGUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/joeict.v5i2.1231

Abstract

Penelitian pengembangan aplikasi ini bertujuan untuk Mengetahui langkah-langkah dalam menghasilkan produk berupa aplikasi berbasis android dengan menggunakan augmented reality sebagai media belajar, buku katalog, dan mengetahui kualitas produk yang dibuat dalam membantu guru serta orang tua untuk mengenalkan diskripsi binatang. Penelitian pengembangan ini dibuat dengan menggunakan model Prototype, yakni Mendengarkan pelanggan, Merancang dan membuat Prototype, Uji Coba Prototype. Langkah-langkah dalam menghasilkan suatu produk yaitu menetapkan materi pengenalan binatang untuk anak sekolah dasar (SD) sesuai dengan hasil wawancara di SDN II SIDOMULYO, membuat marker, mendesain aplikasi, mencoding aplikasi, membentuk file apk android, membuat dan mencetak buku katalog, uji materi dan analisis hasil uji materi, uji media pada aspek functional suitability dan analisis hasil uji media, uji lapangan pada aspek usability dan analisis uji lapangan, uji performance aplikasi pada aspek performance efficiency,dan analisis uji performance aplikasi. Berdasarkan hasil dari pengujian produk dapat diketahui: materi yang ada pada aplikasi sudah layak dan sesuai, pada uji functional suitability dinyatakan layak digunakan karena setiap fungsi menu aplikasi dapat berfungsi dengan baik, pada uji aspek portability aplikasi sudah dapat berjalan pada 4 versi android yang berbeda, dan pada aspek pengujan usability memperoleh presentase sebesar 85% (sangat baik)
Semantic Diversity In The Formation Of Story Questions From The Big Language Model Andra Havid Andra Ramadhon; Agung Cahyono; Taufiq Agung Cahyono
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 9 No. 1 (2026): Jurnal Teknologi dan Open Source, June 2026
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v9i1.5490

Abstract

The development of Large Language Models (LLMs) has opened new opportunities for the automatic generation of math word problems (MWPs). However, many existing approaches still produce repetitive and template-based problems due to limited variation in context, narrative structure, and semantic relationships. This limitation reduces the effectiveness of such problems in assessing students’ conceptual understanding. This study aims to develop a semantic diversity pipeline based on context-aware generation to produce more varied, meaningful, and curriculum-aligned math word problems for Indonesian elementary education. The proposed method involves building an Indonesian MWP dataset, fine-tuning an LLM using Low-Rank Adaptation (LoRA), and designing a generation pipeline consisting of context retrieval, prompt diversification, semantic evaluation, and a solvability filtering mechanism. Evaluation was conducted using automated metrics, including Self-BLEU, Jaccard Similarity, and Cosine Similarity based on Sentence-BERT, as well as qualitative assessments from mathematics teachers. The results show that the proposed approach successfully improves lexical, semantic, and contextual diversity in generated problems. The Self-BLEU score of 4.79 indicates low repetition, the Jaccard Similarity score of 0.194 reflects high vocabulary variation, and the Cosine Similarity score of 0.424 demonstrates balanced semantic diversity while maintaining mathematical consistency. Teacher evaluations further confirm that the generated problems are relevant to the curriculum, appropriately challenging, and more natural compared to conventional methods. Overall, this research contributes to the development of more adaptive and diverse LLM-based math word problem generation systems for mathematics learning in Indonesia.
Co-Authors Agung Cahyono Andra Havid Andra Ramadhon Hendri Novantrias