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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Informasi Interaktif Jurnal Manajemen Informatika dan Sistem Informasi Jurnal Informatika dan Rekayasa Elektronik Journal of Information Systems and Informatics JISA (Jurnal Informatika dan Sains) Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) Journal of Applied Data Sciences Jutsi: Jurnal Teknologi dan Sistem Informasi Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer J-Com (Journal of Computer) Jurnal Ranah Publik Indonesia Kontemporer (Rapik) Journal Automation Computer Information System (JACIS) Bulletin of Information Technology (BIT) Transformasi Ilmu Komputer untuk Masyarakat Jurnal Informatika Teknologi dan Sains (Jinteks) DEVOTE: Jurnal Pengabdian Masyarakat Global Aspirasi : Publikasi Hasil Pengabdian dan Kegiatan Masyarakat Jurnal Insan Pengabdian Indonesia JPEMAS: Jurnal Pengabdian Kepada Masyarakat Edu Komputika Journal Pekayunan
Ahmad Tantoni
STMIK Lombok
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Public Health Social Sciences Other

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CLaGAtt: A Hybrid CNN-LSTM-GRU-Attention Model for Stunting Classification Based on Anthropometric Sequences Sofiansyah Fadli; Ahmad Tantoni; Novia Arista; M. Khairul Anam; Muhammad Bambang Firdaus
Journal of Applied Data Sciences Vol 7, No 3: September 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i3.1454

Abstract

Stunting is a chronic nutritional problem that requires accurate early identification because it affects child growth, cognitive development, and long-term human capital. This study adapts the CLaGAtt model, a hybrid CNN–LSTM–GRU–Attention architecture, for stunting classification using anthropometric sequence data. Rather than proposing a new deep learning architecture, the main contribution of this study lies in adapting the existing CLaGAtt framework through an integrated preprocessing pipeline, sequence construction strategy, class balancing using SMOTE, and an evaluation protocol specifically designed for stunting prediction. The preprocessing pipeline included irrelevant-column removal, data transformation, label encoding, standard scaling, class balancing using SMOTE, and sequence generation with a time step of five and a step of one. Three train–test split scenarios were evaluated, namely 90:10, 80:20, and 70:30. Experimental results showed that the 90:10 split produced the best performance, with 91.42% accuracy, 91.50% precision, 91.50% recall, and 91.43% F1-score. The 80:20 and 70:30 scenarios achieved 87.14% and 85.71% accuracy, respectively, indicating that larger training proportions improved model generalization in the available dataset. These findings suggest that the adapted CLaGAtt framework can effectively integrate convolutional feature extraction, sequential learning, and temporal attention for stunting classification from structured anthropometric data. Future work should validate the model on external datasets and integrate regional visualization to support priority intervention mapping.
Enhancing User Satisfaction and Loyalty in MSMEs: The Role of Accounting Information Systems Khairul Imtihan; Mardi Mardi; Ahmad Tantoni; Wire Bagye; Muhammad Fauzi Zulkarnaen
Journal of Information System and Informatics Vol 7 No 1 (2025): March
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i1.1044

Abstract

This study examines the impact of Accounting Information System (AIS) attributes on User Satisfaction, Decision-Making, and Loyalty among Micro, Small, and Medium Enterprises (MSMEs). The research evaluates how Content, System Quality, Information Quality, and User Characteristics influence satisfaction and decision-making, ultimately shaping user loyalty. A quantitative approach utilizing Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to analyze responses from 62 MSME operators in East Lombok, Indonesia. The findings indicate that Content and System Quality significantly enhance User Satisfaction and Decision-Making, which in turn mediate their effects on User Loyalty. Contrary to conventional expectations, Information Quality has a minimal impact, suggesting that MSMEs prioritize system usability and functionality over informational attributes. The study reinforces the critical mediating roles of satisfaction and decision-making, highlighting how system attributes influence behavioral outcomes. In practical terms, AIS should be designed with simplicity, reliability, and relevance to MSME needs, ensuring ease of adoption and operational efficiency. Policymakers are encouraged to promote digital literacy and provide affordable AIS solutions to accelerate adoption among MSMEs. Additionally, the study suggests that future research explore broader cultural and organizational dynamics affecting AIS adoption and employ mixed-method approaches for deeper insights into user behavior.
DDoS ATTACK MITIGATION WITH INTRUSION DETECTION SYSTEM (IDS) USING TELEGRAM BOTS Mohammad Taufan Asri Zaen; Ahmad Tantoni; Maulana Ashari
JISA(Jurnal Informatika dan Sains) Vol 4, No 2 (2021): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v4i2.1043

Abstract

 In the current IS/IT era, service to consumers is an absolute must to be prepared to survive in business competition. Physical and logical attacks with the aim of disrupting information technology services for individuals/agencies/companies or reducing the performance of IS/IT used. The development of IoT in the industrial revolution 4.0, which is all online, is a challenge in itself, from a negative point of view, all of them are able to carry out attacks on ISP servers, often carried out by hackers. DDoS (Distributed Denial of Service) attacks are the most common attacks. The development of software for DDoS attacks is very much on the internet, including UDP Unicorn software to attack very easily and can be done by anyone. Software for real-time monitoring of DDoS attacks, one of which is the Telegram bot. Telegram is a messaging system centered on security and confidentiality, while bots are computer programs that do certain jobs automatically. Telegram bot is free, lightweight and multiplatform. In the case study, this research contains 10 access points to the internet that will be mitigated from DDoS attacks. In this study, it was found that DDoS attacks caused traffic to become very high/congested by fulfilling upload traffic so that legitimate traffic users could not access the internet, connection to the internet was slow, the traffic was also unnatural, making it unable to connect to wireless devices and making Mikrotik  login page becomes unable to appear. The purpose of this study is to mitigate DDoS attacks with the help of telegram bots so as to facilitate the notification of DDoS attacks in the event of an attack so that it is fast to deal with and find the perpetrators of the attack. The conclusion of this study is that DDoS attacks using UDP unicorn software resulted in a traffic spike of 53.5 Mbps on the upload traffic side, causing traffic for legitimate/authenticated users to slow down. By using telegram bots to know DDoS attacks occur in real time with a success rate of attack detection up to 100% notifications on telegram bots. Mitigation of DDoS attacks takes steps to track users using the torch feature on the routerboard interface menu, trace internet connection lines using wired or wireless transmission media, and ensure always monitoring the proxy interface from winbox. 
Co-Authors Ahmad Saprun Haris Anam, M Khairul Arief Setyanto Arifin Hargianto Edi Kurniawan efendi, Budiman Eko Pramono Hairul Fahmi Hairul Fahmi Hasyim Asyari Ilham Kusuma Jaya Indi Febriana Suhriani Khairul Imtihan Kiki Haerani Lalu Mutawalli Lalu Oji Darmaji M. Arif Setiawan M. Hafizi Hanafi Mardi Mardi Maulana Ashari Mohammad Taufan Asri Zaen Muhammad Bambang Firdaus Muhammad Fauzi Zulkarnaen Muhammad Mustakim Novia Arista Novita Susiana Ikhwani Romzi Romzi Sofiansyah Fadli Sri Wahyuni Putri Suherman Apriadi Sumardi Jayanto Wire Bagye Yuliadi Yuliadi