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All Journal Jurnal Inotera Journal of Artificial Intelligence and Innovative Applications (JOAIIA) AMMA : Jurnal Pengabdian Masyarakat APPA : Jurnal Pengabdian Kepada Masyarakat
Ahmad
Universitas Pamulang
Humanities Chemistry Computer Science & IT Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Nursing

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Pelatihan Pembuatan Blog / Website Pribadi Gratis Untuk Siswa Di SMPN 4 Tangerang Selatan Indra Kristianto; Ahmad; Muhammad Santoso
AMMA : Jurnal Pengabdian Masyarakat Vol. 2 No. 5 (2023): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

A blog / website is an online journal or journal that contains a variety of information, such as articles, photos or videos, which are updated regularly. PKM activities at the Tangsel 4 Middle School in the South Tangerang area this time we will provide training on creating personal blogs/websites for free with the aim of students knowing how to create them from the start. Apart from that, creating a blog can be useful for improving oneself both in iincreasing knowledge and improving writing skills and the ability to understand technology.
Web-Based Expert System for Diagnosing Adolescent Mental Health Disorders Using Support Vector Machine and Naïve Bayes Anggito Gabehalomoan; Ahmad
Journal of Artificial Intelligence and Innovative Applications (JOAIIA) Vol. 7 No. 1 (2026): February
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/joaiia.v7i1.57242

Abstract

Mental health disorders are serious issues that can affect anyone, including adolescents. The lack of public awareness, limited access to mental health services, and the absence of practical diagnostic systems are major obstacles in the early detection and treatment of mental disorders. This study aims to design and develop a web-based expert system capable of providing early diagnosis for 10 (ten) types of mental health disorders in adolescents. The system employs the Support Vector Machine (SVM) and Naïve Bayes algorithms to enhance classification accuracy based on symptoms input by users. The system’s knowledge base is derived from literature, mental health experts, and the PPDGJ III (Indonesian Guidelines for the Classification of Mental Disorders). Additionally, the system is equipped with an error-prevention feature to minimize human error during data input. The results indicate that the system can deliver efficient and accurate preliminary diagnoses and can be easily accessed by adolescents and the general public through a web platform. Therefore, this system is expected to serve as an alternative solution for early detection of mental health disorders and to raise public awareness of the importance of mental well-being.
Efektivitas Kolaborasi Digital: Pemanfaatan Microsoft Teams di Lingkungan Perusahaan IT Kazhem Avie AlHakim Umarona; Mohammad Nur Arie; Dwi Ihwanto; Marcel Wang; Angga Firman Hidayat; Ahmad
APPA : Jurnal Pengabdian Kepada Masyarakat Vol 3 No 2 (2025): APPA : Jurnal Pengabdian kepada Masyarakat
Publisher : Shofanah Media Berkah

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Abstract

Dalam era digital saat ini, kolaborasi menjadi kunci utama dalam meningkatkan produktivitas dan efisiensi di lingkungan perusahaan, terutama di sektor IT. Microsoft Teams sebagai platform kolaborasi digital menawarkan berbagai fitur yang mendukung komunikasi dan kerja sama antar karyawan. Penelitian ini bertujuan untuk menganalisis efektivitas penggunaan Microsoft Teams dalam meningkatkan kolaborasi di perusahaan IT. Metode yang digunakan adalah studi literatur dengan mengumpulkan data dari berbagai sumber yang relevan. Hasil penelitian menunjukkan bahwa Microsoft Teams dapat meningkatkan interaksi, efisiensi kerja, dan kepuasan karyawan dalam bekerja secara kolaboratif.
Perancangan Sistem Informasi Perpustakaan Berbasis Web Responsif untuk Meningkatkan Aksesibilitas di SMK Islam Insan Mulia Aldadi Akbar; Agus Kurniawan; Ahmad; Aktsan Takwimi; Arfiannur Chandra; Doni Dermawan; Dzikrie Aditya Budiman; Fajar Al Aizar Kusrianto; Nicolo D. Albergati Sihombing; Shevcenko Radjartha; Okta Irawati
APPA : Jurnal Pengabdian Kepada Masyarakat Vol 4 No 1 (2026): APPA : Jurnal Pengabdian kepada Masyarakat 
Publisher : Shofanah Media Berkah

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Abstract

Perpustakaan sekolah memegang peranan vital dalam mendukung literasi dan pembelajaran siswa. Namun, pengelolaan perpustakaan di SMK Islam Insan Mulia masih dilakukan secara manual menggunakan buku pencatatan untuk mendata koleksi buku, anggota, serta transaksi peminjaman dan pengembalian. Dengan beban operasional melingkupi sekitar 500 eksemplar buku, 700 siswa, dan 20 hingga 30 transaksi harian yang hanya dikelola oleh satu orang petugas, sistem manual ini menyebabkan inefisiensi waktu pencarian (5–10 menit per transaksi), tingginya risiko kesalahan manusia (human error), serta kerentanan terhadap kehilangan data fisik. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk merancang, mengembangkan, dan mengimplementasikan Sistem Informasi Perpustakaan berbasis web responsif guna mengatasi permasalahan tersebut. Metode pelaksanaan mencakup tujuh tahapan sistematis: persiapan, perancangan sistem, pengembangan, pengujian, implementasi, sosialisasi dan pelatihan, serta evaluasi. Hasil implementasi menunjukkan bahwa aplikasi berbasis web yang dikembangkan berhasil mempercepat proses pendataan dan pencarian buku, meminimalisir kesalahan pencatatan, serta meningkatkan kemudahan akses informasi bagi siswa maupun petugas melalui antarmuka Front-End dan Back-End yang terintegrasi. Pelatihan dan pendampingan yang diberikan juga terbukti meningkatkan kapasitas mitra dalam mengoperasikan sistem secara mandiri dan berkelanjutan.
Comparison of the Performance of Machine Learning Classification Algorithms on Phishing URL Detection Ahmad; Sartika Lina Mulani Sitio
Jurnal Inotera Vol. 11 No. 2 (2026): July - December 2026
Publisher : LPPM Politeknik Aceh Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31572/inotera.Vol11.Iss2.2026.ID697

Abstract

The development of internet technology has increased the intensity of digital activities, but it has also been followed by an increase in cybersecurity threats, one of which is phishing attacks through malicious URLs. Phishing is a fraudulent method that is carried out by manipulating users through fake websites that resemble official websites to obtain sensitive information, such as usernames, passwords, and financial data. Conventional blacklist-based detection methods are considered less effective in recognizing new phishing URLs that continue to develop dynamically. Therefore, this study aims to analyze and compare the performance of various machine learning and deep learning algorithms in accurately detecting phishing URLs. The dataset used was obtained from Kaggle with a total of 11,054 data points and 31 features that represent the characteristics of phishing and legitimate URLs. The methods used include Logistic Regression, K-Nearest Neighbor, Support Vector Machine, Naive Bayes, Decision Tree, Random Forest, Gradient Boosting, CatBoost, Extreme Gradient Boosting, and Multilayer Perceptron. The research stages include data preprocessing, exploratory data analysis, data visualization, separation of training and testing data, model training, and performance evaluation using accuracy, precision, recall, and F1-score. The results showed that the Gradient Boosting algorithm provided the best performance with an accuracy of 0.974, an F1-score of 0.977, a recall of 0.994, and a precision of 0.986. The results show that the ensemble learning method is able to detect phishing URLs effectively and can be used to improve artificial intelligence-based cybersecurity systems.
Co-Authors Agus Kurniawan Aktsan Takwimi Aldadi Akbar Angga Firman Hidayat Anggito Gabehalomoan Arfiannur Chandra Doni Dermawan Dwi Ihwanto Dzikrie Aditya Budiman Fajar Al Aizar Kusrianto Indra Kristianto Kazhem Avie AlHakim Umarona Marcel Wang Mohammad Nur Arie Muhammad Santoso Nicolo D. Albergati Sihombing Okta Irawati Sartika Lina Mulani Sitio Shevcenko Radjartha