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All Journal Information System for Educators and Professionals : Journal of Information System JSiI (Jurnal Sistem Informasi) Jurnal Linguistik Komputasional Enrichment : Journal of Management JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Infotech: Journal of Technology Information Indonesia Berdaya KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Minfo Polgan (JMP) INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS : Journal of Information System Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) JPMB : Jurnal Pengabdian Masyarakat Berkelanjutan DIGINTEL-AI : DIGital INnovation and inTELligence – AI
Zuhri Halim
Teknik Informatika, Universitas Muhammadiyah Prof. Dr. Hamka, Jakarta
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Library & Information Science Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary Other

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Increasing Digital Literacy Through the Use of Basic Technology for Youth Organizations on Indigenous Plants Suciati, Rizkia; Nurhanifah, Siti; Halim, Zuhri; Andi, Andi
Indonesia Berdaya Vol 5, No 4 (2024)
Publisher : UKInstitute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47679/ib.2024968

Abstract

The use of technology is increasingly widespread and even dominates every human activity. The importance of digital literacy to deal with the negative impacts of technological advances is the basis for digital literacy in environmental and cultural conservation. This community service activity aims to improve digital literacy knowledge through the use of basic technology in the introduction of potential indigenous plants. Community service activities are carried out by empowering 18 youth organization (Karang Taruna). The method used during the activity is project-based learning based on natural history. The initial activity is to provide a pre-test and education on the introduction and use of plant applications. Furthermore, participants practice identifying and processing the information that has been obtained, so that local plant information is created in the form of a QR Code. Finally, an evaluation is carried out by providing a post-test. Training in the use of basic digital literacy technology for indigenous plants can increase the digital literacy knowledge of Karang Taruna’s member from 43.75% to 82.75%. With this increased knowledge, it is hoped that Karang Taruna can utilize basic technology to recognize indigenous plants as a form of environmental conservation and local cultural history.
RANCANG BANGUN SISTEM PERSEDIAAN BARANG MENGGUNAKAN METODE WATERFALL DI TOKO OBAT CITRA CILODONG DEPOK BERBASIS MOBILE APPLICATION Halim, Zuhri; Maulana Irsyad, Teuku Fadhil
Infotech: Journal of Technology Information Vol 11, No 1 (2025): JUNI
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i1.347

Abstract

Currently, inventory management systems are one of the most essential components in stores or warehouses. Toko Citra is a pharmacy located at Jl. Raya Asrama Divif 1 Kostrad, Cilodong, Kec. Cilodong, Depok City, West Java. Established in 2005, the store still relies on manual record-keeping for inventory and receipts, which often results in data entry errors. Additionally, during busy hours, employees are frequently overwhelmed when handling transactions. To address these issues, the researcher developed a system designed to manage stock and transaction data at the store. The system was built using the waterfall development method, with Kodular Creator as the application platform and Google Spreadsheet as the database. After development, the system was tested using black-box testing, including alpha testing by the researcher and beta testing by the store owner and employees. The results showed that the system functions properly and is suitable for daily use by the staff at Toko Citra.
IMPLEMENTASI SISTEM INFORMASI KESEHATAN BERBASIS KADER POSYANDU UNTUK DIGITALISASI DATA KESEHATAN Dodi Syaripudin; Faldy Irwiensyah; Rusdi Doviyanto; Zuhri Halim
Jurnal Pengabdian Masyarakat Berkelanjutan Vol. 2 No. 1 (2026): Jurnal Pengabdian Masyarakat Berkelanjutan (JPMB), Februari 2026
Publisher : Yayasan Nusa Cendekia Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64020/jpmb.v2i1.21

Abstract

Posyandu plays a crucial role in maternal and child health monitoring; however, manual recording systems using KIA/KMS books often lead to data inconsistency, physical damage risks, and delays in reporting health indicators such as stunting. This community service activity was carried out through an approach focused on the development and implementation of a health information system based on Posyandu cadres. This study aims to design and implement a digital health information system to transform data management processes at the Posyandu level to be more accurate, efficient, and integrated. This research employs the Research and Development (R&D) method with the Waterfall development model. The system design is modeled using the Unified Modeling Language (UML), including use case, activity, and class diagrams. Testing was conducted using Black Box Testing for functional validation and User Acceptance Test (UAT) to measure the level of user acceptance.  The results show that the developed information system is 100% functional according to technical specifications. UAT testing among Posyandu volunteers (kader) indicated a satisfaction rate of 88%, categorizing the system as Highly Acceptable. Data digitalization through this system significantly accelerates the data recapitulation process and minimizes input errors, thereby supporting more targeted medical decision-making at the Community Health Center (Puskesmas) level.
KLASIFIKASI JENIS KULIT WAJAH MANUSIA MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK DENGAN ARSITEKTUR MOBILENETV3-LARGE Zuhri Halim; Abdul Fadlil; Herman Yuliansyah
Infotech: Journal of Technology Information Vol 12, No 1 (2026): JUNI
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v12i1.590

Abstract

Facial skin type determination is a critical aspect in the development of digital skincare recommendation systems and technology-based dermatological services. However, skin identification methods that rely on manual assessment still present several limitations, as they are subjective, time-consuming, and highly dependent on the observer’s expertise. To address these issues, this study proposes an automated approach for facial skin type classification using Convolutional Neural Networks (CNNs) with a transfer learning scheme. Three computationally efficient CNN architectures MobileNet, MobileNetV2, and MobileNetV3-Large were employed and evaluated comparatively. This study utilized a dataset consisting of 2,250 facial images categorized into five skin types, namely Combination, Dry, Normal, Oily, and Sensitive. The dataset was divided into 1,800 images for training, 225 images for validation, and 225 images for testing to ensure objective performance evaluation. All images were normalized and resized to 224 × 224 pixels prior to model processing. Model training was conducted using two epoch configurations, specifically 5, 10, 20, 30, 50 and 100 epochs, to examine the effect of training duration on classification performance. The experimental results indicate that increasing the number of training epochs has a positive impact on the accuracy of all evaluated models. Among the three architectures, MobileNetV3-Large achieved the best performance, attaining a test accuracy of 100% at 100 epochs and demonstrating superior generalization capability, particularly in distinguishing skin types with similar visual characteristics, such as Sensitive and Combination. These findings confirm that appropriate CNN architecture selection and training configuration play a crucial role in enhancing facial skin type classification performance and highlight the potential applicability of the proposed approach in mobile-based applications.
Implementasi Machine Learning untuk Deteksi Intrusi pada Jaringan Komputer Dyan Prawita Sari; Zuhri Halim; Irlon Irlon; Bayu Waseso; Saromah Saromah
Jurnal Minfo Polgan Vol. 13 No. 2 (2024): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v13i2.14074

Abstract

Dalam era digital yang semakin berkembang, keamanan jaringan komputer menjadi isu yang sangat penting, terutama dengan meningkatnya ancaman dari serangan siber. Salah satu metode yang efektif dalam mendeteksi ancaman tersebut adalah melalui implementasi machine learning. Penelitian ini bertujuan untuk mengembangkan dan mengevaluasi model machine learning yang mampu mendeteksi intrusi pada jaringan komputer secara real-time. Model yang diusulkan menggunakan teknik supervised learning, di mana dataset yang berisi lalu lintas jaringan normal dan lalu lintas yang mengandung serangan digunakan untuk melatih algoritma. Algoritma yang dipertimbangkan meliputi Decision Tree, Random Forest, dan Support Vector Machine (SVM). Penelitian ini juga melakukan analisis komparatif untuk menilai kinerja masing-masing algoritma dalam hal akurasi, presisi, recall, dan waktu pemrosesan. Hasil eksperimen menunjukkan bahwa model machine learning yang diterapkan mampu mendeteksi berbagai jenis serangan dengan tingkat akurasi yang tinggi, mencapai lebih dari 95% pada dataset uji. Selain itu, Random Forest terbukti menjadi algoritma yang paling efektif dalam mendeteksi intrusi dengan keseimbangan terbaik antara akurasi dan waktu pemrosesan. Implementasi sistem ini diharapkan dapat meningkatkan kemampuan deteksi intrusi pada jaringan komputer, sehingga membantu dalam menjaga keamanan data dan mengurangi potensi kerugian akibat serangan siber.
Perbandingan Naive Bayes Classifier dan SVM untuk Analisis Sentimen Desain Seragam Atlet Indonesia pada Media Sosial X di Olimpiade Paris 2024 Azizah Salma Nida; Irwansyah; Ade Davy Wiranata; Zuhri Halim
DIGINTEL-AI : DIGital INnovation and inTELligence – AI Vol. 1 No. 2 (2026): April
Publisher : PT Ajira Karya Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66217/digintel-ai.v1i2.13

Abstract

The Olympics is an international sporting event held every four years and serves as a platform for countries to showcase their athletic capabilities and national identity. One aspect that attracts public attention is the design of athletes' uniforms, which not only have aesthetic value but also support athletic performance. Differences in public perception of these designs generate various opinions expressed on social media X. This study aims to analyze public sentiment toward the design of Indonesian athletes' uniforms at the Paris 2024 Olympics on social media X and to compare the performance of Naive Bayes Classifier and Support Vector Machine algorithms. The dataset consists of textual data collected from social media X and processed through preprocessing stages and split into training and testing data with an 80:20 ratio. The results show that there are 1,014 positive and 728 negative sentiments. Model evaluation indicates that the Naive Bayes Classifier achieved an accuracy of 80.5%, while the Support Vector Machine achieved 94.2%, outperforming the former. These findings demonstrate that the Support Vector Machine is more effective than the Naive Bayes Classifier for sentiment analysis of social media text data related to the design of Indonesian athletes' uniforms at the Paris 2024 Olympics.
Implementasi Dashboard Real-Time Untuk Memantau Proses Pendaftaran Webinar Berbasis Website Adji Prasetyo; Zuhri Halim
Journal of Information System Research (JOSH) Vol 7 No 2 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i2.9214

Abstract

This research aims to develop a web-based information system with an analytical dashboard to improve business process efficiency and campaign evaluation. The research method employs the Waterfall model. The system is developed with a centralized database and is equipped with a data visualization dashboard using Microsoft Power BI, divided into Revenue and Activity pages. The implementation results in a functional website for webinar registration integrated with the database. Alpha and beta testing shows that the system operates according to expected functionality, has an easy-to-understand interface, and assists the registration and monitoring processes. Based on data from 20 user respondents, this registration website system has successfully achieved a very high level of acceptance and satisfaction. An overwhelming majority of respondents (90% to 100%) rated the website as responsive, fast, very helpful, easy to understand, and providing a good impression. Although there is slight room for improvement in operational ease (with 35% stating it is not difficult, while the remainder were possibly neutral or disagreed), the overall survey results prove that this system functions very effectively as a decision-support tool for management, as well as a successful and positive medium for interaction with prospective registrants. It is concluded that this system has successfully become an effective decision-support tool for management through periodic reporting.
Co-Authors Abdul Fadlil Ade Davy Wiranata Adji Prasetyo Affandi, Irfan Ricky Ananda Prasta Andi Andi Anwar Hidayat Ayu Latifah Alfisyahrin Azizah Salma Nida Bayu Waseso Dodi Syaripudin Dyan Prawita Sari Faldy Irwiensyah Firman Noor Hasan Hanif, Isa Faqihuddin Herman Yuliansyah Irlon Irlon Irwansyah Kraugusteeliana Kraugusteeliana Maulana Irsyad, Teuku Fadhil Muhammad Fatkhur Rahman Muhammad Ridwan Ngurah Pandji Mertha Agung Durya Nunik Pratiwi Rusdi Doviyanto Saromah Saromah Sinduningrum, Estu Siti Nurhanifah, Siti Suciati, Rizkia Suherlan Suherlan