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All Journal Jurnal Teknik Informatika (JUTIF) Jurnal Masyarakat Mengabdi Nusantara Nusantara Journal of Computers and its Applications
Kamil Malik
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Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Other

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KLASIFIKASI JENIS JAMBU BIJI BERDASARKAN TEKSTUR DAUN MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORKS (CNN). Kamil Malik
NJCA (Nusantara Journal of Computers and Its Applications) Vol 6, No 2 (2021): Desember 2021
Publisher : Computer Society of Nahdlatul Ulama (CSNU) Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36564/njca.v6i2.266

Abstract

Jambu biji adalah tanaman buah yang banyak berkembang di daerah dengan iklim tropis ataupun subtropis, seperti di negara Mexico, Amerika Selatan, Indonesia dan negara disekitarnya. Beberapa jenis jambu memiliki daun yang mirip, maka akan sulit untuk membedakan jenisnya. Salah satu alternatif yang dapat digunakan untuk permasalahan tersebut adalah klasifikasi menggunakan teknik Image Processing (pengolahan citra) dengan menggunakan metode Convolu-tional Neural Networks(CNN). Pengolahan citra pada daun jambu dilakukan untuk mengenali warna dan teksturnya. selanjutnya akan di proses menggunakan metode Convolutional Neural Networks (CNN). Jumlah Dataset yang digunakan sebanyak 880 gambar, 640 sebagai data train, 160 sebagai data validasi dan 80 sebagai data uji, data terse-but dibagi menjadi 4 kelas. Hasil dari proses pelatihan terhadap model pada penelitian ini mendapat nilai akurasi sebesar 97%. Sedangkan pada pengujian terhadap data baru menggunakan data test pada dataset dimana model di uji menggunakan 20 data citra daun jambu pada masing-masing kelas dan mendapatkan hasil rata-rata nilai akurasi sebe-sar 93%.
Optimalisasi Produktivitas UKM di Probolinggo Melalui Inovasi Teknologi Informasi Kamil Malik
Jurnal Masyarakat Mengabdi Nusantara Vol. 2 No. 4 (2023): Desember : Jurnal Masyarakat Mengabdi Nusantara
Publisher : STIPAS Tahasak Danum Pambelum Keuskupan Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58374/jmmn.v2i4.215

Abstract

This study investigates the impact of information technology education and mentoring on enhancing the productivity of Small and Medium Enterprises (SMEs) in Probolinggo Regency. Involving 30 SME participants, the study utilized qualitative methodologies, including interviews, surveys, and observations, to assess changes in participants' knowledge, attitudes, and practices towards information technology. The results indicate a significant increase in understanding and use of digital technology post-activity, with 85% of participants reporting improved knowledge and 90% exhibiting a positive attitude towards the use of technology in their businesses. Practical implementation of new skills was observed in 65% of participants, who successfully activated and managed accounts on online marketplaces within two weeks after training. The study concludes that effective education and mentoring in information technology are crucial catalysts for digital adaptation in SMEs, especially in rural areas, and highlights the need for more tailored training approaches for older participants.
ENHANCING EFFICIENCY IN DETERMINING QURAN LEARNING GROUPS: A WEBSITE-BASED K-MEANS ALGORITHM APPROACH AT NURUL JADID ISLAMIC BOARDING SCHOOL Ikhwan Abdillah; Andi Wijaya; Kamil Malik
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.2215

Abstract

This research aims to develop a web-based application system using the K-Means algorithm to group students in Quran coaching at the Nurul Jadid Islamic Boarding School in Paiton, Probolinggo. The need for this system is based on the importance of efficiency and accuracy in determining student coaching groups based on their abilities in reading the Quran, including Tajweed, fluency, and memorization scores. This research method involves data analysis from 412 students. The data is processed using the K-Means algorithm to group students into three skill categories: "Good", "Sufficient", and "Poor". The grouping results provide objective and accurate guidance in determining suitable coaching groups for each student. The research results show that the K-Means algorithm is effective in grouping students, thereby improving the efficiency and accuracy of the coaching process. The implementation of web-based technology facilitates access and use of the system by administrators and coaching participants, ensuring that the grouping and coaching processes become faster, more accurate, and more objective. In conclusion, this research successfully develops a more responsive and efficient Quran coaching system, which not only solves specific problems at the Nurul Jadid Islamic Boarding School but also makes a significant contribution to the development of similar systems in other Islamic educational institutions.
Co-Authors Andi Wijaya Ikhwan Abdillah