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Smatika Jurnal : STIKI Informatika Jurnal
Published by Universitas Bhinneka Nusantara
ISSN : 20870256     EISSN : 25806939     DOI : https://doi.org/10.32664/smatika
Core Subject : Science,
Computer Science & IT
SMATIKA: STIKI Informatika Jurnal is a journal published by Lembaga Penelitian & Pengabdian kepada Masyarakat (LPPM) of Universitas Bhinneka Nusantara Malang. The scope of this journal in the field of Computer Science, Information Systems, and Information Management.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 274 Documents
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Analisis Perbandingan Kinerja Algoritma Machine Learning Untuk Classifikasi Kesehatan Mental Mahasiswa Chanafy, Muhammad; Sulistiani, Heni
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 01 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i01.2080

Abstract

Mental health issues among college students are a critical issue that requires data-driven approaches to detect early treatment needs. This study aims to analyze and compare the performance of three machine learning algorithms: Naive Bayes, K-Nearest Neighbor (K-NN), and Decision Tree in classifying college students' mental health treatment needs based on an open survey dataset. The study was conducted systematically using RapidMiner software, with data preprocessing, model training, testing, and performance evaluation using accuracy, precision, and recall metrics. The test results showed that the Naive Bayes algorithm produced an accuracy of 78.85%, a precision of 75.96%, and a recall of 72.84%. K-NN performed better with an accuracy of 82.62%, a precision of 80.83%, and a recall of 77.37%. Meanwhile, the Decision Tree algorithm performed best with an accuracy of 88.32%, a precision of 86.77%, and a recall of 85.80%. In addition to its high performance, Decision Tree also offers advantages in interpreting results through its decision tree structure, which illustrates the role of variables such as employment status (self_employed), family history (family_history), survey completion time (timestamp), and care options (care_options) in the classification process. Decision Tree can be concluded as the most effective classification model for detecting student mental health needs in this data context. These findings are expected to serve as a reference in the development of machine learning-based early detection systems to support mental health policies and interventions in higher education settings.
Analisis Sentimen Ulasan Game Lokapala pada Google Play Menggunakan Algoritma SVM Abrar, Erlangga Hikmal; Ariyanti, Novia; Sumarno
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 01 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i01.2081

Abstract

This study aims to analyze user sentiment towards the Lokapala game through reviews collected from the Google Play Store. Lokapala is a local MOBA game developed by Anantarupa Studios that integrates Indonesian cultural elements. A quantitative approach is employed using the Support Vector Machine (SVM) algorithm to classify user reviews into positive and negative sentiments. Data were collected using the google-play-scraper library and preprocessed through several stages, including cleaning, case folding, word normalization using kamuskatabaku.xlsx, tokenizing, stopword removal, and stemming with the Sastrawi library. Reviews were labeled based on user ratings and split into training and testing datasets. Model testing results show an accuracy of 83%, with the highest precision of 0.85 for the positive class, recall of 0.93, and f1-score of 0.89. Additionally, WordCloud visualization revealed frequently occurring words such as "bagus" (good), "main" (play), "tolong" (please), and "banget" (very), reflecting both praise and technical complaints from users. These findings demonstrate that SVM is effective for sentiment analysis of user reviews and can provide valuable insights for developers in improving the quality of local games.
Development of a Virtual Mentor Integrated with Retrieval-Augmented Generation Artificial Intelligence for Project-Based Learning Baskara, Dwi Soca; Muttaqin, Nabil; Purwodani, Dio Lingga
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 01 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i01.2258

Abstract

Project-Based Learning (PjBL) is a learning model that can enhance the quality of higher education, particularly in developing critical thinking, creativity, and collaboration skills. However, implementing PjBL often faces challenges such as limited resources and the need for intensive guidance from lecturers. To overcome these challenges, Artificial Intelligence (AI) technology offers great potential, although traditional AI systems often provide responses that are less relevant to the context of the learning material. The Retrieval-Augmented Generation (RAG) technique in AI can serve as a solution, enabling the system to generate more accurate and contextually relevant responses. By utilizing data sources such as course materials, RAG can enhance the relevance of AI responses in supporting project-based learning. It is expected that developing an AI-based virtual mentor using the RAG approach can optimize students’ PjBL experiences. Specifically, this virtual mentor is designed to provide contextual guidance, help students overcome project-related challenges, and foster independent learning, thereby improving the quality and effectiveness of PjBL in higher education.
Design of an Automated Verification to Improve the Efficiency and Optimization of IPR Management Rismawati, Mei; Baskara, Dwi Soca
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 01 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i01.2162

Abstract

Copyright is an essential element of innovation in academic and educational environments. However, the current manual verification and management process of Intellectual Property Rights (IPR) is highly inefficient, particularly in institutions such as Universitas Negeri Malang, which face delays and data duplication due to paper-based workflows. To address this issue, this study aims to develop an Automated Copyright Verification System based on Multi-Agent Artificial Intelligence to enhance efficiency and optimize IPR management. The proposed system, developed using a Prototype Model, leverages an agent-based architecture to model IPR verifiers with distinct functions and objectives. These agents are supported by Vision Language Models (VLM) and Natural Language Processing (NLP). Its key features include ID card data compliance checks and automated text recognition using VLM. The implementation of this system is expected to reduce staff workload, accelerate responses, and ensure data accuracy in IPR management, supporting a sustainable innovation ecosystem.
Design and Development of a Multi-Agent Artificial Intelligence-Based Financial Planner for Institutional Financial Management Optimization Kartika, Intan Dina; Baskara, Dwi Soca; Hardika
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 01 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i01.2167

Abstract

Institutional financial management often faces optimization challenges due to limited understanding of influencing factors, difficulties in data integration, and the lack of human expertise. These constraints hinder the identification of opportunities, risk management, and sustainability. An adaptive and automated financial planning system is required. This study proposes the design of an Artificial Intelligence (AI)-based system for automated financial planning aligned with institutional standards. The system addresses these challenges by integrating financial needs analysis, standardized cost references, and automated budget summary preparation. Using a prototyping approach, the system employs AI agents to conduct in-depth analysis and produce comprehensive budgets. The proposed system leverages RAGflow, an open-source Retrieval-Augmented Generation (RAG) engine that uses deep document understanding to provide truthful question-answering from complex data.
Pengembangan Sistem ERP Berbasis Web Menggunakan Next.js dan Laravel: Pendekatan Prototyping SDLC Andreas Natanael Irawan; Permana Sanusi, Amadea
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 01 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i01.2174

Abstract

The development of information technology encourages companies to digitize business processes to improve the efficiency and accuracy of data management. CV AS Nusa Trans (CV ANT), a land transportation service company, still uses manual spreadsheet-based recording scattered across multiple links, causing problems such as data duplication, information delays, and difficulties in preparing reports. This research aims to develop a web-based Enterprise Resource Planning (ERP) system as an integrated digital solution to support company operations. The development was carried out using the System Development Life Cycle (SDLC) Prototyping model approach, which allows user involvement from the early stages through an iterative process. Next.js is used as a front-end framework to produce a responsive and fast interface display, while Laravel is used as a back-end to ensure a secure and organized business logic structure. The system design process includes observation, requirements analysis, system modeling and iterative prototype implementation. The developed ERP system integrates invoice management, fleet management, customer data, and an operational calendar into a single centralized platform. To evaluate system usability, the System Usability Scale (SUS) method was applied involving two main user roles: Admin and Owner. The evaluation results indicate an average SUS score of 93.75, which falls into the Excellent Usability category, demonstrating that the system is easy to learn, efficient to use, and well accepted by users. This research contributes scientifically by demonstrating the effectiveness of combining the SDLC Prototyping approach with modern Web Application technologies (Next.js and Laravel) in the development of an ERP system, particularly within the land transportation service sector.
Pengembangan Sistem Point of Sales Berbasis Laravel Filament Menggunakan Metode Pengembangan Aplikasi Cepat Syafi Razzaq, Farid; Rizki Jatmiko, Andriyan
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 01 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i01.2177

Abstract

Digital transformation is increasingly essential for improving operational efficiency and data accuracy in Micro, Small, and Medium Enterprises (MSMEs). However, MSMEs often face a dual challenge: the need for rapid system implementation and the limited technical literacy of system users, which creates a gap between complex system requirements and practical usability. This study applies and evaluates the effectiveness of the Rapid Application Development (RAD) methodology in developing a web-based Point of Sale (POS) system tailored to MSME operational characteristics. The research adopts an applied, design-oriented approach, emphasizing iterative prototyping and continuous user involvement to reduce adoption barriers. Rather than focusing on feature completeness, the study examines how RAD supports system usability and user acceptance among non-technical users. The proposed system was evaluated using the System Usability Scale (SUS) involving users with different operational roles. The results indicate that the iterative nature of RAD effectively bridges the gap between system complexity and user capability, as reflected by an average SUS score of 76.66, categorized as “Good”. These findings provide empirical evidence that RAD is a suitable development approach for MSME information systems, particularly in contexts requiring rapid deployment and high usability, and contribute to applied information systems research by highlighting the role of user-centered iteration in improving system acceptance.
Perancangan dan Pengembangan Sistem Terintegrasi untuk Pemesanan dan Analisis Penjualan Kurdi Maulana Bintang, Mohammad; Rizki jatmiko, Andriyan
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 01 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i01.2179

Abstract

This study presents the design and development of an integrated ordering and sales analysis system for Kaluna Living, a micro-enterprise specializing in handcrafted ceramic home goods. Prior to the system development, business operations relied on manual workflows for recording orders, processing custom product requests, and preparing monthly sales reports. These procedures resulted in slow transaction handling, higher risk of inconsistent data, and limited business visibility. The system was developed using the SDLC Prototyping model to enable iterative refinement through continuous user feedback. To evaluate usability, the System Usability Scale (SUS) was applied to representative user roles (customer, admin, and owner). The evaluation yielded an average SUS score of 81.66, which falls into the Excellent (Above Average) usability category, indicating that the system is perceived as easy to use, consistent, and learnable. The system supports centralized ordering workflows, custom request handling with image upload, and sales insight visualization that summarizes monthly revenue and order volume. The findings suggest that iterative prototyping contributes to usability improvements by refining navigation flow, clarifying form structures, and supporting streamlined operational workflows. This research contributes to applied system development for micro-enterprises by demonstrating how integrated digital ordering and analytics can improve operational efficiency and decision support in handcrafted product businesses.
Measuring Service Quality and User Satisfaction of Universitas Terbuka’s Ruang Baca Virtual (RBV) Using SERVQUAL and EUCS Trihapningsari, Denisha; Astuti Aprijani, Dwi; Anglingsari Putri , Mayang; Leviany, Fonda
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 01 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i01.2183

Abstract

This study aims to measure the service quality and user satisfaction of the Ruang Baca Virtual (RBV) application within Universitas Terbuka’s (UT) digital library and to identify priority dimensions requiring improvement. A quantitative survey approach was employed using two structured questionnaires based on the SERVQUAL and End User Computing Satisfaction (EUCS) models. SERVQUAL was applied to assess five dimensions of service quality (tangibles, reliability, responsiveness, assurance, and empathy), while EUCS evaluated five dimensions of user satisfaction (content, accuracy, format, ease of use, and timeliness). The SERVQUAL gap analysis was conducted using a percentage comparison approach against the ideal score to determine priority improvement areas. The research included 100 participants, where 50 respondents evaluated service quality using the SERVQUAL method, and the remaining 50 respondents measured user satisfaction using the EUCS approach. The results indicate that all SERVQUAL and EUCS dimensions fall within the “satisfied” category. Empathy and reliability emerged as key strengths in service quality, while ease of use and accuracy were identified as main strengths in user satisfaction. However, responsiveness and assurance (SERVQUAL), as well as format and timeliness (EUCS), exhibited relatively larger gaps, indicating areas requiring improvement. These findings provide a comprehensive descriptive evaluation of RBV performance and offer strategic insights for enhancing digital library services in distance learning environments.
Development of Hetrik Mobile Application in Iot-Based Electricity Management for Boarding Houses Moch. Azam Firmansyah; David Marcus, Ronald
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 01 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i01.2197

Abstract

Inefficient electricity usage is a common issue in boarding houses due to limited transparency in consumption data and the absence of integrated real-time monitoring systems. To address this problem, this study proposes an Internet of Things (IoT)-based mobile application called Hetrik to support more transparent and efficient electricity management. The research aims to design and implement an integrated system architecture that connects IoT-based sensing hardware with a digital user interface for monitoring and managing electricity consumption. The system was developed using the Agile development method, consisting of requirement analysis, system design, development, testing, implementation, evaluation, and deployment stages. The hardware architecture integrates an ESP32 microcontroller with ACS712 current sensors and ZMPT101B voltage sensors to capture real-time electricity consumption data. The mobile application was developed using React Native for the front-end and Laravel for the back-end and cloud database. A key contribution of this research is the design and validation of a QR-to-Device scanning mechanism, which enables dynamic mapping between IoT device identities and user accounts while supporting an automatic prepaid electricity payment system. System implementation produced five core modules: power monitoring dashboard, transaction system, usage history, profile management, and device scanning. Functional testing using the Black Box method and User Acceptance Testing (UAT) confirmed that the system operates according to technical specifications and is suitable for real operational environments. The proposed system demonstrates the potential to reduce electricity waste in boarding houses by up to 30% through data-driven energy monitoring and management.

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