Article Per Year (5 Year)
p-Index From 2020 - 2025
0.61
P-Index
This Author published in this journals
All Journal SMARTICS Journal TRILOGI: Jurnal Ilmu Teknologi, Kesehatan, dan Humaniora Proceeding Of International Conference On Education, Society And Humanity
Ghozali, Achmad Fais
Unknown Affiliation
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Other

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Klasifikasi Nilai Pengurus Teladan Pondok Pesantren Nurul Jadid Menggunakan Metode K-Nearest Neighbor (KNN) Jasri, Moh.; Ghozali, Achmad Fais; Sukron
SMARTICS Journal Vol 10 No 1 (2024): SMARTICS Journal (April 2024)
Publisher : Universitas PGRI Kanjuruhan Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/smartics.v10i1.9913

Abstract

In determining exemplary administrators, there are several assessment criteria that have been designed by looking at all the tasks and programs carried out. This is done to encourage administrators to be more enthusiastic in their service at Islamic boarding schools. Apart from that, this program is also an evaluation for management who need to follow up on their negligence in all duties and responsibilities. From the research carried out, there is a problem, namely in determining exemplary administrators, currently at the Nurul Jadid Islamic Boarding School it is only based on observations of regional heads and regional heads, and does not pay attention to assessment criteria and indicators in the form of professionalism, personality and social issues. Therefore, a decision support system implemented in web form is very necessary to solve the problems that occur. The programming language used is PHP (Hypertext Preprocessor) using the CodeIgniter framework. The hope is that the resulting website can help regional and regional heads make the right decisions for exemplary organizers. K-Nearest Neighbor (KNN) is the method used for classification in this research. The KNN algorithm uses the k value to determine the number of nearest neighbors whose status will be calculated. The data used is 348 lines of management assessment data for 2021-2023. Optimizing the k value using k-fold cross validation produces the highest level of accuracy, namely 97.70% with a value of k = 4 and training data of 75% of the total previous assessment data.
INTEGRATION OF CODING AND AI IN ISLAMIC EDUCATION CURRICULUM MANAGEMENT: A CONCEPTUAL STUDY Ghozali, Achmad Fais; Jasri, Moh.; Syafiih, M.
PROCEEDING OF INTERNATIONAL CONFERENCE ON EDUCATION, SOCIETY AND HUMANITY Vol 2, No 2 (2024): Third International Conference on Education, Society and Humanity
Publisher : PROCEEDING OF INTERNATIONAL CONFERENCE ON EDUCATION, SOCIETY AND HUMANITY

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This paper aims to explore the integration of programming (coding) and artificial intelligence (AI) in the management of Islamic education curriculum, with a focus on maintaining traditional Islamic values. This paper uses a conceptual approach to develop a theoretical understanding of how technology can be applied in Islamic education without ignoring religious principles. The results of the study indicate that coding and AI have great potential in improving the quality of teaching, accessibility of education, and supporting independent learning. In the context of Islamic education, this technology can be used to enrich the learning experience, such as the development of AI-based Al-Quran learning applications and coding-based interactive teaching applications. The integration of coding and AI in the Islamic education curriculum should be carried out through a holistic planning process, which includes identifying needs, integrating technology into curriculum content, and designing lessons that are in line with Islamic values. Therefore, technology not only increases the effectiveness of learning but also helps shape students' character in accordance with Islamic teachings. This paper provides recommendations for developing a curriculum that combines technology with Islamic principles, making it relevant to the development of the times while maintaining the spiritual aspect of education.Keywords: Artificial Intelligent, Coding, Curriculum Management, Islamic Education
Implementasi K-Nearest Neighbor (KNN) untuk Mengklasifikasi Masyarakat Pra-Sejahtera Desa Sapikerep Kecamatan Sukapura Khairi, Ahmad; Ghozali, Achmad Fais; Hidayah, Ach Darul Nur
TRILOGI: Jurnal Ilmu Teknologi, Kesehatan, dan Humaniora Vol 2, No 3 (2021): Pengembangan Teknologi dan Kesehatan di Lembaga Keagamaan
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (431.948 KB) | DOI: 10.33650/trilogi.v2i3.2878

Abstract

Kemiskinan merupakan masalah umum yang sangat kompleks yang terdapat dibeberapa bagian negara indonesia, hal ini dapat diketahui dari rendahnya pendidikan, kesehatan dan kualitas hidup masyarakat. Kemiskinan juga merupakan salah satu penghambat bagi seseorang untuk memperoleh kehidupan yang layak atau kehidupan yang sejahtera. Pemerintah memiliki peranan penting dalam mensejahterakan warga negaranya dari kemiskinan. Pemerintah telah melakukan beberapa upaya untuk mengentaskan kemiskinan diantaranya dengan adanya Program Keluarga Harapan (PKH), Bantuan Langsung Tunasi (BLT) dan beberapa program lainnya. Namun dalam pelaksanaannya masih terdapat penerima bantuan yang tidak tepat sasaran sehingga terdapat keluarga dengan katergori sejahtera masih mendapatkan bantuan dan keluarga tidak sejahtera tidak memperoleh bantuan, seperti yang terdapat di desa sapikerep sukapura probolinggo. Beberapa kriteria untuk menentukan masyarakat sejahtera yang telah ditentukan oleh pemerintah setempat diataranya yakni aset/harta benda, jenis lantai, jenis dinding, status lahan atau bangunan, sumber penerangan, sumber air minum, penghasilan, serta sumber energi memasak. Dari permasalah diatas dibutuhkan suatu analisa yang tepat untuk menentukan suatu keputusan. Oleh sebab itu, dalam penelitian ini akan melakukan analisa terhadap data yang diperoleh dengan indikator yang telah disebutkan diatas dengan menggunakan suatu algoritma datamining. Algoritma K-Nearest Network (K-NN) merupakan algoritma yang bisa digunakan untuk melakukan prediksi ataupun klasifikasi terhadap suatu data tergantung dari jenis data pada kumpulan data yang ada. K-NN melakukan klasifikasi pada suatu data berdasarkan nilai k yang telah ditetapkan sebelumnya. Nilai k pada K-NN harus menggunakan nilai ganjil jika digunakan untuk proses klasifikasi beda halnya jika digunakan untuk melakukan prediksi nila k pada K-NN dapat berupa bilangan ganjil ataupun genap. Nilai k yang digunakan untuk menguji kinerja algoritma K-NN yakni k-3, k-5, dan k-7, dimana hasil akurasi masing-masing nilai k pada K-NN yang digunakan memiliki hasil akurasi yang berbeda terkecuali nilai akurasi k-5 dan k-7 yang memiliki nilai akurasi yang sama. Nilai akurasi k-3 pada K-NN sebesar 97.36% sedangkan nilai akurasi k-5 dan k-7 pada K-NN sebesar 98.68%.
Co-Authors Hidayah, Ach Darul Nur Jasri, Moh. Khairi, Ahmad sukron Syafiih, M.