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All Journal Jurnal Teliska PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic International Journal of Artificial Intelligence Research JTERA (Jurnal Teknologi Rekayasa)
Agung, Muhammad Zakuan
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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PERANCANGAN DISASTER RECOVERY PLAN SISTEM INFORMASI AKADEMIK DENGAN PENDEKATAN KERANGKA KERJA NIST 800-34 Agung, Muhammad Zakuan
JTERA (Jurnal Teknologi Rekayasa) Vol 4, No 2: December 2019
Publisher : Politeknik Sukabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (701.965 KB) | DOI: 10.31544/jtera.v4.i2.2019.157-166

Abstract

Politeknik Negeri Sriwijaya telah memiliki Sistem Informasi Akademik yang terintegrasi bernama SISAK POLSRI. Terdapat 8 (delapan) sub sistem di dalamnya yang meliputi Sistem Informasi Akademik (SIAK), Sistem Informasi Bimbingan Akademik (SIBA), Learning Management System Politeknik Negeri Sriwijaya (LMS Polsri), E-Complaint Politeknik Negeri Sriwijaya, E-Library Politeknik Negeri Sriwijaya, Sistem Informasi Kepegawaian (SIMPEG), Sistem Informasi Alumni dan Tracer Study (SIAT), dan Sistem Pendaftaran dan Pendataan  Mahasiswa Baru (E-Regist). SISAK POLSRI merupakan hal yang vital dalam keberlangsungan operasional Politeknik Negeri Sriwijaya, sehingga diperlukan suatu upaya preventif. Salah satu upaya yang dapat dilakukan adalah dengan merancang dokumen Disaster Recovery Plan yang bertujuan untuk menjaga keberlangsungan sistem, ketika sistem telah terkena dampak ancaman. Tahapan dalam perancangan Disaster Recovery Plan dengan pendekatan kerangka kerja NIST 800-34 yang diinisiasi oleh Risk Assessment, Business Impact Analysis dan Strategy Recovery. Hasil dari penelitian ini berupa dokumen  Disaster Recovery Plan terhadap 9 ancaman dan 8 sub sistem SISAK POLSRI.
Vehicle Class Prediction at Toll Gate Using Deep Learning Nisa, Suci Lutfia; Soim, Sopian; Agung, Muhammad Zakuan
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 12 No. 2 (2024): September 2024
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v12i2.9833

Abstract

In the era of digitalization and automation, efficiency in the traffic management system at toll gates is very important. One of the efforts to improve this efficiency is to develop an automatic vehicle class detection system using deep learning technology, especially Convolutional Neural Network (CNN). This research aims to design and implement a CNN model that can identify and classify the types of vehicles passing through toll gates. The model development process includes collecting and annotating vehicle image data, data pre-processing, and CNN model training and testing. The evaluation results show that the developed model can achieve an accuracy of about 96% in detecting vehicle classes, so it can be integrated with the toll gate system to increase the speed and accuracy in the vehicle classification process. Thus, this solution is expected to reduce the waiting time of toll users and improve operational efficiency.
Personalized Product Recommendations Using Restricted Boltzmann Machines To Overcome Cold-Start Challenges On A Niche Coffee E-Commerce Platform Hesti, Emilia; Handayani, Ade Silvia; Suzanzefi, Suzanzefi; Agung, Muhammad Zakuan; Rosita, Ella; Asriyadi, Asriyadi; Kaila, Afifah Syifah; Afifah, Luthfia; Ardiansyah, M.
International Journal of Artificial Intelligence Research Vol 9, No 1.1 (2025)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v9i1.1.1551

Abstract

This paper examines the use of a Restricted Boltzmann Machine (RBM) to provide personalized product recommendations on a niche coffee e-commerce platform facing cold-start conditions. We train RBM variants on a binary transaction matrix derived from 100 simulated user transactions and evaluate four hidden-unit configurations (3, 5, 10, 15) using 5-fold cross-validation. Models were trained with Contrastive Divergence (CD-1) and assessed primarily by Mean Squared Error (MSE) for reconstruction fidelity, complemented by ranking metrics (Precision@3, NDCG@3). The 10-hidden-unit configuration achieved the best balance of reconstruction and ranking performance, with an average test MSE ? 0.0454, outperforming popular-item (MSE: 0.0802) and random (MSE: 0.0760) baselines. While the RBM demonstrates strong capability in modeling latent user preferences under sparse data, ranking metrics expose limitations when predicting exact top-N items in extremely sparse cases. The study highlights practical implications for early-stage niche marketplaces and suggests integrating content signals or hybridization to further improve top-N recommendation quality.
SMARTBAND TRACKER UNTUK ANAK USIA DIBAWAH 6 TAHUN MENGGUNAKAN WEMOS D1 DENGAN MONITORING MELALUI SMARTPHONE Syafitri, Dhea; Aryanti, Aryanti; Agung, Muhammad Zakuan
JURNAL TELISKA Vol 18 No III (2025): TELISKA November 2025
Publisher : Teknik Elektro Polsri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.17761317

Abstract

Smartband tracker is designed to monitor the child's location directly through the blynk application on the smartphone. To make this smartband requires several components, namely the Wemos D1 Mini as the brain center of the smartband control device, GPS is used to determine the position point of the child's whereabouts, the battery functions as a power supply so that the smartband can operate independently, the Battery Mangament System functions as a backup battery life and the Switch is used as an On / Off button. This tool works in a way, if the red LED flashes it means the GPS has obtained a coordinate point where the results can be seen in the blynk application which can display the location point of the child's whereabouts, displaying coordinate points such as latitude, longitude, and speed. In this study, testing was carried out at 5 location points. The results of the study showed that speed variations were greatly influenced by the duration and intensity of movement, not only by the distance traveled. High speed is recorded at short distances when fast movement occurs, namely point 1 to point 6, while low speed occurs even though the distance is long, when the movement is slow, namely at point 1 to point 5. After testing the tool, the results show that the smartband can work well and can determine the location point in real-time and the advantage of this tool is that it has a buzzer feature that can be turned on via the blynk application on the smartphone where this buzzer will make a sound when activated. Key words : Smartband, IoT, Wemos D1, GPS Tracker, Children, Smartphone, Monitoring
Co-Authors Ade Silvia Handayani Afifah, Luthfia Aryanti Aryanti Asriyadi Asriyadi Emilia Hesti Kaila, Afifah Syifah M. Ardiansyah Nisa, Suci Lutfia Rosita, Ella Sopian Soim, Sopian suzan zefi Syafitri, Dhea