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Wandi Syahindra
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Arcitech: Journal of Computer Science and Artificial Intelligence
Published by Institut Agama Islam Negeri Curup
ISSN : 29623669     EISSN : 29622360     DOI : http://dx.doi.org/10.29240/arcitech
Core Subject : Science,
Computer Science & IT
Arcitech: Journal of Computer Science and Artificial Intelligence, is an Open Access and peer-reviewed journal published by the State Islamic Institute (IAIN) Curup. This journal focuses on the field of computer science and artificial intelligence covering all aspects of information technology, computer science, computer engineering, information systems, Software Engineering and its development, software engineering Computer networks, IoT, security systems, Simulation Modeling and Applied Computing, Computing High Performance, Image and speech processing, big data and data mining, and artificial intelligence. The journal is published by Institut Agama Islam Negeri (IAIN) Curup, online and printed twice a year, in June and December.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 9 Documents
 1 
Search results for , issue "Vol. 5 No. 1 (2025): June 2025" : 9 Documents clear
Optimasi Infrastruktur Wi-Fi dan Manajemen Bandwidth di Sekolah Menengah Pertama Menggunakan Teknologi Mikrotik Ramayanti, Desi; Saputra, Vega
Arcitech: Journal of Computer Science and Artificial Intelligence Vol. 5 No. 1 (2025): June 2025
Publisher : Institut Agama Islam Negeri (IAIN) Curup

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29240/arcitech.v5i1.12408

Abstract

The increasing demand for reliable and high-performance Wi-Fi networks in educational institutions necessitates efficient infrastructure management. However, many schools still face issues such as poor signal strength and inefficient bandwidth allocation. This study aims to optimize Wi-Fi network infrastructure and bandwidth management using Mikrotik technology, addressing these limitations through strategic access point (AP) placement, Queue Tree-based bandwidth allocation, and real-time monitoring. A mixed-methods approach was used, combining quantitative performance measurements and qualitative user feedback. Results show significant improvements, with signal strength increasing from -83 dBm to -34 dBm, download speeds reaching 41.52 Mbps, and reduced latency in high-traffic areas. These findings suggest that proper infrastructure design and bandwidth management strategies can enhance network stability and efficiency in educational environments. This study contributes to the field by providing a practical model for Wi-Fi optimization in schools, potentially benefiting similar institutions globally.
Sistem Sirkulasi dan Keamanan Buku pada Perpustakaan Menggunakan Radio-Frequency IDentification berbasis IoT via WhatsApp Harlian Navi; Nuroji
Arcitech: Journal of Computer Science and Artificial Intelligence Vol. 5 No. 1 (2025): June 2025
Publisher : Institut Agama Islam Negeri (IAIN) Curup

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29240/arcitech.v5i1.13337

Abstract

The book lending process in conventional libraries is still done manually, causing queues, data input errors, and lack of operational efficiency. This technology relies on desktop or web-based digital systems, without integrating IoT technology and real-time communication. Therefore, this research proposes the development of an Internet of Things (IoT)-based book lending system integrated with WhatsApp API and RFID system to improve circulation efficiency and book security. This research uses the prototyping method so that development can be adjusted iteratively to user needs. The system was tested using the black-box testing method and showed a 100% success rate in all test scenarios. This research is an application of the integration of IoT and instant messaging platforms in the context of library management, which has not been widely raised in previous studies, and produces a prototype that is applicable to the scale of educational institutions.
Analisis Wilayah Prioritas Pembangunan di Provinsi Jawa Timur Berdasarkan Indikator Sosial Menggunakan Metode K-Means Clustering Asyafiiyah, Gita Rohma Utami; Widyastuti, Artika; Andriani, Friska
Arcitech: Journal of Computer Science and Artificial Intelligence Vol. 5 No. 1 (2025): June 2025
Publisher : Institut Agama Islam Negeri (IAIN) Curup

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29240/arcitech.v5i1.13488

Abstract

Development is a key indicator of a region's progress; however, regional disparities remain a pressing issue due to uneven distribution of development. This study employs a data mining approach using the K-Means Clustering method. The objective is to classify priority development areas in East Java Province based on various social indicators, including total population, population growth rate, population density, Human Development Index (HDI), unemployment rate, and average years of schooling (AYS). Unlike previous studies, this research adopts a more comprehensive data-driven approach. The results show that K-Means successfully classifies regions into two clusters: priority and non-priority. A Silhouette Score of 0.45 indicates a fairly good level of cluster separation. Most of the regions in the priority cluster are regencies, while the non-priority cluster predominantly consists of urban areas. These findings confirm that K-Means Clustering is an effective decision-support tool for identifying priority development areas through data-based analysis.
Analisis Komparatif Performa AES-GCM dan ChaCha20-Poly1305 dalam Enkripsi Dokumen PDF Berbasis AEAD Patria, Muhammad; Andriati, Dea Andini
Arcitech: Journal of Computer Science and Artificial Intelligence Vol. 5 No. 1 (2025): June 2025
Publisher : Institut Agama Islam Negeri (IAIN) Curup

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29240/arcitech.v5i1.13645

Abstract

Digital transformation in electronic document services demands encryption mechanisms that are not only cryptographically secure but also performance-efficient. While AES-GCM and ChaCha20-Poly1305 are widely adopted AEAD algorithms, prior research has largely focused on their use in communication protocols or IoT devices, rather than in encrypting PDF documents. This study addresses that gap by empirically comparing both algorithms in real-world digital document processing scenarios. A quantitative experimental method was applied across two scenarios: mass processing of 5,000 small-to-medium PDF files (100KB–8MB), and individual processing of large files (1MB–200MB). Five performance metrics were analyzed: encryption time, decryption time, total processing time, stability, and throughput. Results show that AES-GCM consistently outperformed ChaCha20-Poly1305 across all metrics, offering faster processing and greater stability. Both algorithms produced a constant file size overhead of 28 bytes, which was negligible in terms of storage efficiency. This study contributes to the literature by providing empirical evidence to guide the selection of encryption algorithms in high-performance digital document storage systems.
Systematic Literature Review (SLR) pada Aplikasi Process Mining dalam Transformasi Digital Proses Bisnis Putra, Yusran Panca; Okka Adittio Putra; Willi Novrian
Arcitech: Journal of Computer Science and Artificial Intelligence Vol. 5 No. 1 (2025): June 2025
Publisher : Institut Agama Islam Negeri (IAIN) Curup

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29240/arcitech.v5i1.13888

Abstract

Digital transformation compels organizations to enhance the efficiency and transparency of their business processes. Process mining has emerged as a pivotal approach that leverages event logs from information systems to evaluate and improve processes in a data-driven manner. This study aims to conduct a Systematic Literature Review (SLR) of existing research exploring the application of process mining in supporting business process digital transformation. Relevant literature was retrieved from the Scopus database and filtered using rigorous inclusion and exclusion criteria, resulting in ten primary studies analyzed through the PICOS framework and PRISMA diagram. The findings indicate that process discovery, heuristic mining, and fuzzy mining are the most commonly employed techniques, with tools such as ProM and Disco frequently utilized. Research trends show increasing integration of process mining with artificial intelligence, simulation, and process automation technologies. However, several challenges remain, including limited data log quality and availability, lack of cross-system integration, and minimal validation in real-world settings. This study highlights the strategic role of process mining as a key enabler of digital transformation by enhancing efficiency, process visibility, and data-driven decision-making, while also providing a research landscape and future development directions in the domain.
Perancangan Ui/Ux Website Safe Tangkinspec Dengan Design Thinking: Case Study Pertamina Integrated Terminal Kendari Chairunnisa, Fadhillah; Faqihuddin Hanif, Isa
Arcitech: Journal of Computer Science and Artificial Intelligence Vol. 5 No. 1 (2025): June 2025
Publisher : Institut Agama Islam Negeri (IAIN) Curup

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29240/arcitech.v5i1.13935

Abstract

This study aims to design a web-based User Interface (UI) and User Experience (UX) for the Safe Tangkinspec system as a digital solution for the inspection process of tanker vehicles at PT Pertamina Integrated Terminal Kendari. The previous inspection process, which relied on manual procedures using physical documents (hardcopy), was prone to human error, document loss, high operational costs, and delays in record-keeping. The Design Thinking methodology was applied through five stages: empathize, define, ideate, prototype, and test. This approach allowed for the identification of user needs and the development of a web-based solution with key features including digital forms, history tracking, schedule notifications, and a real-time dashboard. Usability testing using the System Usability Scale (SUS) yielded a score of 88%, categorized as “Excellent,” demonstrating that the interface is intuitive and effective for operational staff, and supports sustainable digital transformation in the energy sector. This research provides a practical contribution to the development of user-centered digital interfaces within the context of industrial infrastructure.
Klasifikasi Otomatis Tingkat Kerusakan Retak Bangunan pada Citra Digital Menggunakan MobileNetV2 dan Augmentasi Data Ricky Putra Sardika; Widhiarso, Wijang
Arcitech: Journal of Computer Science and Artificial Intelligence Vol. 5 No. 1 (2025): June 2025
Publisher : Institut Agama Islam Negeri (IAIN) Curup

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29240/arcitech.v5i1.13938

Abstract

Crack detection in buildings is a crucial step in maintaining structural integrity at an early stage and preventing further damage. This study aims to improve the accuracy of crack severity classification in digital images by applying five on-the-fly data augmentation techniques (flip, rotate, zoom, translation, and contrast) combined with the MobileNetV2 architecture. The augmentation techniques are performed dynamically during the training process without storing the transformed images, making the process more efficient in terms of storage, computation time, and adaptability to data variations. This study utilized a dataset of 900 images and achieved a classification accuracy of 93%, which is higher than the previous approach using MobileNetV1 with offline augmentation that only reached 89%. Previous research was limited to static augmentation approaches and less efficient CNN architectures. This study addresses those limitations by integrating dynamic augmentation and a lightweight architecture. It contributes to enhancing the efficiency and accuracy of crack image classification models in the context of limited data and low-computation systems, with strong potential for implementation in automated detection systems on mobile or edge computing devices.
Perancangan Teknologi Radio Frequency Identification Dalam Sistem Presensi Peserta Didik Berbasis Internet of Things di Sekolah Menegah Pertama Sejahtera 2 Cileungsi Yusuf Widsono, Maulana; Nuroji
Arcitech: Journal of Computer Science and Artificial Intelligence Vol. 5 No. 1 (2025): June 2025
Publisher : Institut Agama Islam Negeri (IAIN) Curup

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29240/arcitech.v5i1.13968

Abstract

The manual student attendance system at SMP Sejahtera 2 Cileungsi presents several inefficiencies, such as susceptibility to recording errors, time-consuming procedures, and difficulties in accurately summarizing attendance data. Previous studies have proposed RFID and IoT-based systems to improve efficiency, yet most lack features for real-time parental notification. This study aims to develop an automated student attendance system using Radio Frequency Identification (RFID) integrated with the Internet of Things (IoT) and a Telegram bot for immediate communication with parents. The system was developed using the prototyping method, allowing for iterative refinement based on user needs. Attendance is recorded through RFID cards tapped on a reader device, with data stored in a database and exportable to PDF and Excel formats. Black box testing was conducted to validate system functionality. The results indicate that the system enhances accuracy, efficiency, and parental involvement by providing real-time updates. This research contributes to smart education technology by offering a scalable and interactive attendance model that supports administrative digital transformation in schools.
Implementasi Chatbot Berbasis Large Language Model Untuk Pencarian Skripsi Mahasiswa Terintegrasi dengan Whatsapp Hasbi, Muhammad Adryan; Imanda, Rahmi; Fathan Fauzan, Muhammad
Arcitech: Journal of Computer Science and Artificial Intelligence Vol. 5 No. 1 (2025): June 2025
Publisher : Institut Agama Islam Negeri (IAIN) Curup

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29240/arcitech.v5i1.13974

Abstract

Students often face difficulties in finding relevant thesis references, which can hinder the completion of their final projects and delay graduation. This study aims to develop a chatbot using a Large Language Model (LLM) integrated with WhatsApp as an interactive and efficient solution for academic reference search. A total of 795 classified thesis documents were collected from the Faculty of Industrial Technology and Informatics, UHAMKA. The system was built using the LangChain framework, including Setting Table Schema, Semantic Search, Rank Result, and Natural Language Interface for Databases. Implementation results showed that the chatbot successfully responded to natural language queries with 100% accuracy. User Experience Questionnaire (UEQ) evaluations indicated strong positive responses, with Clarity (2.08) and Accuracy (2.00) achieving “Excellent” ratings indicate high levels of efficiency in conducting thesis searches. This research demonstrates the effective application of LLMs in conversational academic search systems and offers a foundation for the development of similar services in other higher education institutions.

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