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All Journal Journal of English and Education International Journal of Artificial Intelligence Research Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat
Akhyari, Muhammad Wafa
Unknown Affiliation
Computer Science & IT Education Electrical & Electronics Engineering

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Klasifikasi Penyakit Pada Daun Jagung Menggunakan Convolutional Neural Network Akhyari, Muhammad Wafa; Suyoto, Andi; Wibowo, Ferry Wahyu
Jurnal Informa : Jurnal Penelitian dan Pengabdian Masyarakat Vol 7 No 2 (2021): Desember
Publisher : Politeknik Indonusa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46808/informa.v7i2.199

Abstract

Deep Learning masih diteliti secara luas dan masih menjadi masalah yang menarik. Pada penelitian ini daun pada jagung di gunakan sebagai objek penelitian sedangkan Deep Learning digunakan untuk memproses dan mendiagnosa penyakit tanaman pada daun jagung menggunakan metode Convolutional Neural Network (CNN), sebanyak 3.846 gambar pada daun tanaman jagung, yang terdiri dari tiga jenis penyakit jagung yaitu penyakit Bercak Daun, Hawar Daun dan Karat Daun digunakan sebagai dataset. Dengan hasil akurasi keseluruhan di atas 90%, dalam mendeteksi penyakit pada tanaman jagung berdasarkan daunnya.
Identify the Usability of the Netraku Application System Using the Usability Testing Method Dewi, Alifa Permata; Sari, Amarria Dila; Iryani, Devina Inayah; Akhyari, Muhammad Wafa
International Journal of Artificial Intelligence Research Vol 8, No 2 (2024): December 2024
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v8i1.1472

Abstract

The Netraku application is aimed at the visually impaired who want to know the name of an object or the writing of an object or printed media, as well as knowing the nominal currency conveyed via voice in the application. The application works by pointing the camera at the object or currency you want to see the name or amount of. The Netraku application will detect it, and a voice will appear stating the information you want to convey. The problem found is that the Netraku application has not carried out usability testing for blind users. Therefore, it is necessary to develop usability testing to obtain user needs from the Netraku application, determine the effectiveness and efficiency values, and provide recommendations that can be applied to the Netraku application. The methods used in usability testing are performance measurement, focus group discussion, and participatory design. The results obtained on the effectiveness value received a success rate of 83.33% and a failure rate of 16.7%, concluding that the user can complete the task effectively. The efficiency value obtained from the average processing time is 10.34 seconds.
Integrating AI in academic writing: Lecturers and students' experiences related to benefits and challenges Andriyanti, Erna; Murtafi’ah, Banatul; Zudianto, Hardian; Rochma, Anis Firdatul; Tuilan, Jeane; Akhyari, Muhammad Wafa
Journal of English and Education (JEE) Vol. 11 No. 2 (2025): Vol 11 No. 2 (2025): VOLUME 11 NO 2 NOVEMBER 2025
Publisher : English Education Department, Universitas Islam Indonesia

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Abstract

The rapid development of Generative Artificial Intelligence (Gen AI) has influenced how English as a Foreign Language (EFL) learners and educators engage in academic writing. This study aims to explore how lecturers and students in Indonesian higher education integrate AI tools into their academic writing practices, perceive benefits and challenges of using AI, and concern with ethical considerations. Using a qualitative approach combining interviews and photovoice, the study involved thirteen participants from western, central, and eastern Indonesia. The findings show that AI tools are used not only for linguistic assistance but also for idea generation, prompt refinement, and collaborative meaning-making, reflecting an interactive relationship between users and technology. Participants reported that AI improves efficiency, creativity, and clarity in writing, while concerns were raised regarding hallucinated references, inconsistency, and overreliance that may reduce critical thinking and authenticity. The study also finds that AI should be used ethically as a complementary partner that supports, rather than replaces, human intellect in academic writing. The main ethical considerations include maintaining authorship, content verification, and proper referencing. The findings imply the need for pedagogical frameworks and institutional policies that promote ethical, reflective, and responsible AI use in higher education.  
Co-Authors Dewi, Alifa Permata Erna Andriyanti Ferry Wahyu Wibowo Iryani, Devina Inayah Jeane Tuilan Murtafi'ah, Banatul Rochma, Anis Firdatul Sari, Amarria Dila Suyoto, Andi Zudianto, Hardian