SAGA: Journal of Technology and Information System

Design of a Web-Based Point of Sale System for Transaction Recording at Sumber Rejeki Store

2026-02-13T04:16:22+00:00

The use of manual transaction recording in Micro, Small, and Medium Enterprises (MSMEs) often causes data inaccuracies, inefficient transaction processes, and difficulties in inventory monitoring. Toko Sumber Rejeki Karangbener Kudus is an MSME that still applies handwritten sales records, leading to limited transaction documentation and delayed reporting. This study aims to design a web-based Point of Sale (POS) system to support sales transactions, inventory management, and sales reporting. The study employs a Research and Development (R&D) approach using the Waterfall model. Data were collected through observation of transaction activities, interviews with the store owner, and a literature review related to POS systems and MSME digitalization. System design was carried out using structured modeling, including use case diagrams, activity diagrams, data flow diagrams, entity relationship diagrams, sequence diagrams, and user interface design. The developed system provides role-based access for cashiers, administrators, and owners. Cashiers handle sales transactions and cash sessions, administrators manage product and stock data, and owners monitor sales reports. The proposed system is expected to reduce recording errors, streamline transaction processes, and improve data organization, serving as a practical solution for MSMEs transitioning from manual to digital transaction recording.

Web-Based Hotel Inventory Information System at Guna Wijaya Hotel Pati

2026-02-13T03:58:48+00:00

Inventory management at Hotel Guna Wijaya currently relies on manual ledgers, leading to inaccurate real-time data and risks of record loss. Key challenges include difficult stock monitoring and delayed reporting due to manual recapitulation. This study develops a web-based inventory information system to enhance transparency, stock accuracy, and reporting efficiency using the Waterfall model: requirements analysis, system design, implementation, and testing. System design utilized Unified Modeling Language (UML), while testing employed Black Box and User Acceptance Testing (UAT) focusing on Role-Based Access Control (RBAC). Results demonstrate that the system successfully prevents data duplication through a Double-Check Validation feature on item names and locations. The digitalization significantly reduces report generation time from days to seconds using a Reporting Engine integrated with WhatsApp and Email. Furthermore, the Safety Stock Alert feature effectively provides early warnings to prevent shortages. Overall, the system improves monitoring, maintains data integrity, and supports efficient managerial decision-making at Hotel Guna Wijaya.

Building Smart Learners: AI-Deep Learning, Digital Literacy, and Self-Regulation as Predictors of IPAS Outcomes

2026-03-03T13:16:38+00:00

The rapid advancement of digital technology has made it imperative to adopt innovative instructional approaches in elementary-level IPAS (Natural and Social Science) education in Indonesia. Baseline data from Cluster 2, Pule District revealed that only 40.19% of Grade VI students met the minimum mastery criterion (KKM) in 2024/2025. This study examines the effects of AI-based IPAS learning through deep learning (X1), digital literacy (X2), and learning independence (X3) on student learning outcomes (Y) using a quantitative correlational non-experimental design. A proportional random sample of 129 students was drawn from 190 Grade VI students across 12 elementary schools. Data were analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM) using SmartPLS 4.0. The measurement model confirmed satisfactory convergent validity (all AVE > 0.50), discriminant validity (Fornell–Larcker criterion), and composite reliability (all CR > 0.90). The structural model yielded R² = 0.784, indicating that the three variables jointly explain 78.4% of the variance in learning outcomes (GoF = 0.752, very high). All four hypotheses were accepted: AI-Deep Learning (β = 0.324, t = 4.872, p < 0.05), Digital Literacy (β = 0.287, t = 4.215, p < 0.05), Learning Independence (β = 0.412, t = 6.134, p < 0.05), and their simultaneous effect (F = 124.567, p < 0.05). Learning independence emerged as the dominant predictor (f² = 0.892). These findings advocate for an integrated digital-autonomous learning ecosystem as a systemic response to persistent IPAS underachievement in Indonesian elementary schools.

The Role of School Principals in Implementing Deep Learning at Elementary Schools in Panggul District, Trenggalek

2026-03-03T13:23:47+00:00

Twenty-first-century learning demands that elementary schools develop learning processes that are not merely oriented toward content mastery but also toward deep understanding and higher-order thinking skills. The deep learning approach is considered relevant because it emphasizes meaningful, reflective, and applicable learning. This study aims to analyze the role of school principals in implementing deep learning at elementary schools in Panggul District, Trenggalek Regency. A qualitative descriptive approach was employed, with data collected through in-depth interviews, classroom observation, and documentary analysis involving school principals and teachers. Data analysis followed the interactive model of Miles and Huberman, encompassing data reduction, data display, and conclusion drawing, with data validity assured through source and technique triangulation. Findings reveal that school principals serve as instructional leaders through planning, implementation, and academic supervision functions. Support was provided through the formulation of school policies, strengthening of learning planning, facilitation of teacher collaboration, and provision of professional support. However, academic supervision still tends to focus on administrative aspects and has not fully emphasized the quality of the classroom learning process. This study underscores the importance of strengthening instructional leadership and process-based academic supervision to ensure the sustainable implementation of deep learning at the elementary school level.

The Influence of AI Coding and Technology Tools on Human Resource Readiness Through Digital Literacy

2026-03-06T14:31:50+00:00

The era of Society 5.0 demands the integration of technology and character building in education to prepare superior human resources (HR). However, preliminary observations at public elementary schools in Rejotangan District reveal a gap between policy and reality, characterized by low digital literacy and limited availability of AI-based learning tools. This study aims to analyze the influence of AI Coding-based learning implementation and the availability of technological devices on the readiness of intelligent and competitive HR, mediated by students' digital literacy in science and social studies (SASS). This research employs a quantitative approach with an associative design. The population comprises 319 Grade 5 students, with a sample of 178 students determined using the Slovin formula and proportional stratified random sampling. Data analysis utilizes Structural Equation Modeling (SEM-PLS). The findings indicate that both AI coding learning and device availability significantly influence HR readiness through digital literacy as a mediator. This research provides a model for integrating AI coding in elementary education.