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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 76 Documents
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Perencanaan Strategis Sistem Informasi Pada PT. Cakra Prima Nusantara Menggunakan Metode Ward and Peppard Nicholas Roy Biantoro; Dicky Pratama
Arcitech: Journal of Computer Science and Artificial Intelligence Vol. 6 No. 1 (2026): June 2026
Publisher : Institut Agama Islam Negeri (IAIN) Curup

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29240/arcitech.v6i1.17217

Abstract

Prior studies applying the Ward and Peppard framework to logistics firms have been confined to standalone, internally-scoped ecosystems, leaving a research gap in cross-organizational IS/IT alignment with a national principal platform. This study addresses that gap by formulating a Strategic Information Systems Plan (SISP) for PT Cakra Prima Nusantara, an authorized distributor of Pupuk Sriwidjaja in South Sumatra, whose operations suffer from data fragmentation due to manual inventory recording, an unintegrated accounting system, and fleet coordination reliant solely on instant messaging. Employing a qualitative case study approach, data were collected through structured interviews, field observation, and document review, then analyzed using the Ward and Peppard framework encompassing Value Chain, PESTEL, SWOT, Critical Success Factors (CSF), and McFarlan Strategic Grid. The study produces an IS/IT blueprint — the Cakra Integrated Distribution System (CIDS) — integrating all internal operational units via cloud architecture and synchronizing fertilizer quota data in real-time with the principal's Distribution Planning and Control System (DPCS) through an API Gateway. This research scope covers strategic planning up to the roadmap and application portfolio stage, not system implementation. The principal contribution to SISP literature lies in demonstrating how the Ward and Peppard framework can be adapted for inter-organizational IS alignment within subsidized commodity distribution, a context underexplored in existing studies.
Analisis IT Service Management (ITSM) Menggunakan Framework ITIL V4 pada PT. PBM Bahari Raharja Permai Fachrizal Fadhil Oktafian; Dicky Pratama
Arcitech: Journal of Computer Science and Artificial Intelligence Vol. 6 No. 1 (2026): June 2026
Publisher : Institut Agama Islam Negeri (IAIN) Curup

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29240/arcitech.v6i1.17251

Abstract

Information technology plays an important role in supporting organizational operations, including in the cargo handling and logistics sector. However, studies on the implementation of ITIL V4 in logistics companies that integrate ERP Orlansoft and Inventory Management applications remain limited. This study aims to analyze the maturity level of IT service management at PT. PBM Bahari Raharja Permai using the ITIL V4 framework. The research methods include observation, interviews, questionnaires distributed to 13 respondents, SWOT analysis, and RACI mapping. The analysis focuses on the domains of Service Desk, Incident Management, Monitoring and Event Management, and Continual Improvement. The novelty of this study lies in the application of the ITIL V4 framework to evaluate IT services in a cargo handling company utilizing ERP Orlansoft and Inventory Management applications to support its operations. The results indicate that all domains achieved Level 4 (Managed), with scores of 3.85 for Service Desk, 3.96 for Incident Management, 3.74 for Monitoring and Event Management, and 3.73 for Continual Improvement. These findings provide an important basis for improving IT service quality in a structured manner and serve as a reference for ITIL V4 implementation in the logistics sector.
Analisis Incident Management dan Service Desk Menggunakan Framework ITIL V4 pada Layanan KIR Dinas Perhubungan Kota Palembang Andry Achmad Fadilla; Muhammad Rachmadi
Arcitech: Journal of Computer Science and Artificial Intelligence Vol. 6 No. 1 (2026): June 2026
Publisher : Institut Agama Islam Negeri (IAIN) Curup

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29240/arcitech.v6i1.17305

Abstract

The rapid development of information technology has encouraged government institutions to continuously improve the quality of digital-based public services, including vehicle inspection (KIR) services at the Palembang City Transportation Agency. Based on observations and interviews, several challenges were identified in the management of information technology services, including the absence of well-documented Standard Operating Procedures (SOPs), incident handling processes that are still carried out manually, and the suboptimal performance of service functions in responding to user complaints. This study aims to evaluate IT service management using the ITIL V4 framework, focusing on the Incident Management and Service Desk practices. The research methods employed include observation, interviews, questionnaire distribution to 17 respondents, maturity level analysis, gap analysis, RACI analysis, and SWOT analysis. The results indicate that the maturity level of Incident Management is 1.69, while Service Desk achieves a score of 1.54, both of which fall within the Repeatable level. Furthermore, the gap analysis reveals a difference of 0.31 for Incident Management and 0.46 for Service Desk compared to the targeted maturity level. The SWOT analysis also shows that the implementation of the KIR application has contributed positively to improving the efficiency of public services. However, several weaknesses remain, including the lack of standardized SOPs, the absence of a ticketing system, and a high dependency on vendors for IT service management. Based on these findings, the recommended improvements include the development of SOPs, implementation of a ticketing system, establishment of a more structured Service Desk function, and enhancement of IT personnel competencies. This study contributes by providing an ITIL V4-based IT service evaluation model integrated with RACI and SWOT analyses to support the improvement of digital public service quality within government institutions.
Analisis Komparatif Algoritma Naïve Bayes dan XGBoost untuk Mengklasifikasikan Performa Akademik Mahasiswa Berdasarkan Tingkat Ketergantungan AI Aryanti Aryanti; Juriawan Raja Saputra; Taufik Permana; Putri Nabila; Ibnu Asrafi
Arcitech: Journal of Computer Science and Artificial Intelligence Vol. 6 No. 1 (2026): June 2026
Publisher : Institut Agama Islam Negeri (IAIN) Curup

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29240/arcitech.v6i1.17321

Abstract

While Artificial Intelligence (AI) integrates into higher education to streamline information retrieval, comprehension, and academic task completion, over-reliance on these tools may jeopardize student outcomes. Extant literature predominantly examines AI adoption rates, dependency levels, and user sentiments; however, comparative analyses of machine learning models for classifying academic performance relative to AI usage intensity remain scarce. To address this gap, this study evaluates and compares the efficacy of Naïve Bayes and XGBoost algorithms in predicting student performance based on their AI engagement. Utilizing the Academic Outcomes & AI Dependency Analysis Dataset—comprising 8,000 instances and 26 features—the methodology encompasses data preprocessing, normalization, partitioning, model training, and evaluation via accuracy, precision, recall, and F1-score. The empirical results demonstrate that XGBoost outperforms Naïve Bayes, achieving a superior accuracy of 84.17% compared to 79.03%. Consequently, XGBoost proves to be a more robust model for classifying academic performance driven by AI usage, offering valuable insights for the advancement of educational data analytics.
Analisis Pengelompokan Wilayah Berdasarkan Karakteristik Sosial Ekonomi Menggunakan K-Means dan Simple Additive Weighting (Saw) untuk Penentuan Prioritas Pembangunan di Sumatera Utara Elida Silaban; Chatrine Zefania Manurung
Arcitech: Journal of Computer Science and Artificial Intelligence Vol. 6 No. 1 (2026): June 2026
Publisher : Institut Agama Islam Negeri (IAIN) Curup

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29240/arcitech.v6i1.17129

Abstract

Regional development in North Sumatra Province still shows differences in socio-economic conditions between districts/cities, so that objective and data-based development priority determination is needed. This study aims to group regions based on socio-economic characteristics and determine development priorities using the K-Means Clustering and Simple Additive Weighting (SAW) methods. The study used secondary data from the Central Statistics Agency with variables such as poverty rate, open unemployment rate, human development index, life expectancy, average length of schooling, and gross regional domestic product. The results show that the K-Means method produces three regional clusters: developing regions, underdeveloped regions, and developed regions. The underdeveloped region cluster consists of Nias Regency, South Nias, West Nias, and North Nias, while Medan City is the most developed region. The results of the SAW method indicate that West Nias Regency is the main development priority. The integration of the K-Means and SAW methods can produce more structured and objective regional groupings and development priorities.
Model Klasifikasi Tingkat Kematangan Sayur Hijau Menggunakan Ekstraksi Fitur Warna dan Convolutional Neural Network Rini Widyastuti; Firna Yenila; Eko Syaputra; Wandi Syahindra; Murlena
Arcitech: Journal of Computer Science and Artificial Intelligence Vol. 6 No. 1 (2026): June 2026
Publisher : Institut Agama Islam Negeri (IAIN) Curup

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29240/arcitech.v6i1.17403

Abstract

The maturity level of green vegetables is an important factor affecting product quality, market value, and shelf life. Maturity identification is generally performed visually based on leaf color changes, making the assessment subjective and potentially inconsistent. This study aims to develop a classification model for green vegetable maturity levels using a combination of color feature extraction and a Convolutional Neural Network (CNN) to provide a more objective and accurate system. The research began with image acquisition of green vegetables categorized into three maturity levels: immature, mature, and overripe. Preprocessing included image resizing, normalization, and segmentation. Color feature extraction was performed using RGB and HSV color spaces to represent maturity conditions. The dataset was divided into training and testing sets with a 90:10 ratio and processed using a CNN architecture. Model performance was evaluated using accuracy, precision, recall, and F1-score. Results showed that the proposed model achieved 95.2% accuracy, 94.8% precision, 95.6% recall, and 95.1% F1-score. These findings indicate that combining color features and CNN effectively supports automated vegetable sorting and quality control systems.

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