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All Journal Swabumi (Suara Wawasan Sukabumi) : Ilmu Komputer, Manajemen, dan Sosial IJCIT (Indonesian Journal on Computer and Information Technology) Informatics for Educators and Professional : Journal of Informatics Jurnal Teknik Informatika STMIK Antar Bangsa Infotek : Jurnal Informatika dan Teknologi Indonesian Journal of Networking and Security - IJNS SPEED - Sentra Penelitian Engineering dan Edukasi Journal of Artificial Intelligence and Engineering Applications (JAIEA) Indonesian Community Service Journal of Computer Science (IndoComs)
Muhamad Abdul Ghani
Universitas Bina Sarana Informatika
Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Library & Information Science Social Sciences Other

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Implementasi Metode Waterfall Dalam Mengembangkan Sistem Informasi Ujian Online Dengan Fitur Proctoring Robi Aziz Zuama; Muhamad Abdul Ghani; Deni Gunawan; Abdul Latif Matihudin
INFORMATICS FOR EDUCATORS AND PROFESSIONAL : Journal of Informatics Vol 7 No 2 (2023): INFORMATICS FOR EDUCATORS AND PROFESSIONAL : JOURNAL OF INFORMATICS (Juni 2023)
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat Universitas Bina Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51211/itbi.v7i2.2382

Abstract

Sistem ujian online berbasis web dengan fitur pengawasan proctoring telah menjadi tren yang populer dalam lembaga pendidikan dan perguruan tinggi saat ini. Penelitian ini bertujuan untuk merancang dan mengembangkan sistem informasi ujian online yang aman dan terpercaya dengan fitur pengawasan proctoring. Sistem ini memberikan fleksibilitas waktu dan tempat bagi peserta ujian, sambil mengurangi biaya dan upaya administratif yang terkait dengan ujian konvensional. Metode pengembangan Perangkat lunak yang digunakan yaitu waterfall, dengan tahapan analisis kebutuhan, perancangan, implementasi, testing, dan perawatan. Model yang diusulkan mampu mengefisiensikan kegiatan ujian disekolah serta kecurangan dalam ujian dapat di minimalisir.
Analysis of Machine Learning Algorithms for Early Detection of Alzheimer’s Disease: A Comparative Study Deni Gunawan; Robi Aziz Zuama; Muhamad Abdul Ghani
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 3 (2024): June 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i3.579

Abstract

This study aims to analyze and compare the performance of various machine learning algorithms in predicting Alzheimer's disease based on patient clinical data. The algorithms tested include Decision Tree, Random Forest, K-Nearest Neighbors (KNN), and Logistic Regression. The dataset used in this research consists of clinical data from patients, encompassing various health parameters. The results indicate that the Decision Tree and Random Forest algorithms provide the best performance, with an overall accuracy of 93%. Random Forest performs slightly better in recall for class 0 but slightly worse in recall for class 1 compared to Decision Tree. Logistic Regression also shows good performance with an overall accuracy of 83%, while K-Nearest Neighbors has the lowest performance with an overall accuracy of 72%. This research offers insights into the effectiveness of various machine learning algorithms in detecting Alzheimer's disease and underscores the importance of selecting the appropriate model based on data characteristics and application needs. For future research, it is recommended to further optimize the model hyperparameters, increase the dataset size, add new relevant features, and combine several models using ensemble learning techniques. External validation and the development of more interpretable models are also crucial to build trust in the use of machine learning in the healthcare field.
Penerapan Game Edukasi 3D Endless Runner Berbasis Android Sebagai Media Belajar Matematika Anak Ghani, Muhamad Abdul; Pohan, Achmad Baroqah; Gunawan, Deni; Saputra, Yoga
Infotek: Jurnal Informatika dan Teknologi Vol. 7 No. 1 (2024): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v7i1.24194

Abstract

In the current pandemic era where learning media is done online, information technology is needed to help online learning media. Video Game is one of the information technology software that is currently developing, there are lots of devices that can be used to play video games such as computers, laptops, smartphones, etc. Since the era of the Video Game era, many genres of games were created, one of which is “Endless Runner”. Due to the lack of interest in mathematics which makes elementary school achievement low in Indonesia, for this reason the author tries to make an Android-based 3D Educational Game “Endless Runner” using the Unity3D application with the C # language program and researched using GDLC for learning mathematics  cause the genre of this game is suitable for children, where there is no violence, pornography or sara in the Game “Endless Runner”. This game can be played when you have free time and anywhere because the Game “Endless Runner” is made for Android. Learning tools using the Game “Endless unner” helps children love math lessons
PEMANFAATAN TEKNOLOGI UNTUK PENCATATAN KESEHATAN BALITA DI POSYANDU MAWAR MELATI Verra Sofica; Fani Nurona Cahya; Muhamad Abdul Ghani; Rangga Pebrianto
Indonesian Community Service Journal of Computer Science Vol. 2 No. 1 (2025): Periode Januari 2025
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/indocoms.v2i1.7536

Abstract

Kesehatan balita sangat penting untuk mendukung tumbuh kembang yang optimal. Namun, di beberapa daerah, pencatatan kesehatan balita masih dilakukan secara manual, yang berisiko terhadap kesalahan data dan kurang efisien. Dengan kemajuan teknologi, penggunaan aplikasi berbasis teknologi informasi dapat membantu memudahkan pencatatan dan pemantauan kesehatan balita secara lebih akurat dan efisien. Pelatihan ini mengusulkan pemanfaatan teknologi sederhana, seperti Google Sheets atau Microsoft Excel, untuk mencatat dan memantau data kesehatan balita. Data yang dicatat meliputi berat badan, tinggi badan, status imunisasi, dan indikator kesehatan lainnya. Aplikasi tersebut dipilih karena mudah diakses, sederhana digunakan, dan dapat diintegrasikan ke dalam kegiatan posyandu sehari-hari tanpa memerlukan keterampilan teknis yang kompleks.Tujuan utama dari program ini adalah meningkatkan kemampuan ibu-ibu kader Posyandu dalam mengelola data kesehatan balita secara digital. Dengan menggunakan aplikasi seperti Google Sheets atau Excel, diharapkan proses pencatatan dan pemantauan kesehatan menjadi lebih efisien, mudah diakses, dan dapat dilaporkan dengan cepat dan akurat. The health of toddlers is crucial to supporting optimal growth and development. However, in some areas, toddler health records are still maintained manually, posing risks of data errors and inefficiency. With advancements in technology, the use of information technology-based applications can facilitate more accurate and efficient recording and monitoring of toddler health. This training suggests utilizing simple technologies such as Google Sheets or Microsoft Excel to record and monitor toddler health data, including weight, height, immunization status, and other health indicators. These applications are chosen for their accessibility, ease of use, and ability to be integrated into daily Posyandu activities without requiring complex technical skills. The main goal of this program is to enhance the capability of Posyandu volunteer mothers in managing toddler health data digitally. By using applications like Google Sheets or Excel, it is expected that the recording and monitoring processes will become more efficient, easily accessible, and can be reported quickly and accurately.
Co-Authors Abdul Latif Matihudin Achmad Baroqah Pohan Agus Subekti Ami Rahmawati Deni Gunawan Deni Gunawan Fani Nurona Cahya Gunawan, Deni Hamdun Sulaiman Irwan Herliawan - Universitas Nusa Mandiri Ita Yulianti Mahmud Safudin Mardiyanto-Institut Teknologi Bandung, M. Sukrisno Muhammad Rifqi Firdaus Rahmawati-Universitas Bina Sarana Informatika, Eka Ramdhan Saepul Rohman, Ramdhan Saepul Rangga Pebrianto Riswandi Ishak Robi Aziz Zuama Saputra, Yoga Setiaji Tya Septiani Nurfauzia Koeswara Veithzal Rivai Zainal Verra Sofica