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Jurnal Armada Informatika
Published by STMIK Methodist Binjai
ISSN : 25980416     EISSN : 2615689X     DOI : https://doi.org/10.36520/jai.v8i2.130
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering
Jurnal Armada Informatika, an Indonesian national journal, publishes high quality research papers in the broad field of Informatics and Computer Science, which encompasses software engineering, information system development, computer systems, computer network, algorithms and computation, and social impact of information and telecommunication technology.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 188 Documents
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Design and Development of a Web-Based Information System for the Talent Internship Program Wahda; Ryan Setiawan; Anisah
Jurnal Armada Informatika Vol 10 No 1 (2026): Juni
Publisher : STMIK Methodist Binjai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36520/jai.v10i1.284

Abstract

The Talent Internship Program at the Aceh Transportation Agency is currently managed manually, resulting in delays in data processing, recording errors, and difficulties in monitoring participant activities. This study aims to design and develop an integrated web-based Information System for the Talent Internship Program to improve the efficiency, effectiveness, and accuracy of internship administration management.The research employed the Prototyping method, covering requirements gathering, design, prototype development, iterative evaluation, and system implementation. The system was built using PHP, JavaScript, Bootstrap framework, and MySQL database. System testing was conducted using the Black Box Testing method.The results show that the developed system successfully integrates all administrative processes—including registration, attendance, logbook, assignments, reports, assessment, and certification—into a single web-based platform with four user roles (Intern, Mentor, Admin, and Leader). The system functions well according to user requirements and significantly accelerates administrative processes while improving real-time monitoring quality.Conclusion: The implementation of this system makes the management of the Talent Internship Program at the Aceh Transportation Agency more effective, efficient, structured, and supportive of digital transformation in government institutions.Keywords: Internship Information System, Talent Internship Program, Web-Based Application, Prototyping Method, Black Box Testing
Analysis of Shopee PayLater Acceptance Using The Technology Acceptance Model (TAM) Among Students at Indragiri Islamic University Riska; Usman
Jurnal Armada Informatika Vol 10 No 1 (2026): Juni
Publisher : STMIK Methodist Binjai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36520/jai.v10i1.285

Abstract

Buy now pay later services such as Shopee PayLater are increasingly being adopted by university students as a digital payment alternative, even though this phenomenon often collides with consumptive behavior and the low financial literacy of its users. This study aims to analyze the acceptance level of Shopee PayLater usage among students at Universitas Islam Indragiri by applying the Technology Acceptance Model (TAM) framework. This quantitative research utilizes primary data collected from 89 student respondents through a purposive sampling technique. The data were analyzed through multiple linear regression using IBM SPSS Statistics to test the significance of the Perceived Usefulness (PU), Perceived Ease of Use (PEOU), and Attitude (ATT) variables on the intention to use or Behavioral Intention (BI). Based on the statistical test results, it was found that perceived usefulness (PU) and perceived ease of use (PEOU) do not have a partially significant effect on the intention to use the service. Conversely, the attitude (ATT) variable proved to have a positive and the most significant influence on students' behavioral intention. Simultaneous testing confirmed that the three independent variables collectively influence the intention to use, with the regression model capable of explaining 74.6% of the total variance (R² = 0.746). The conclusion of this study asserts that user attitude plays a crucial role and serves as the most dominant determining factor in driving students to continue utilizing the Shopee PayLater service, outweighing considerations regarding the usefulness and ease of the application itself
Expert System for Diagnosing Post-Flood Diseases Using the Certainty Factor Method Based on Mobile Application David Chandra
Jurnal Armada Informatika Vol 10 No 1 (2026): Juni
Publisher : STMIK Methodist Binjai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36520/jai.v10i1.286

Abstract

The post-flood condition is a critical phase highly susceptible to disease outbreaks such as Diarrhea, Dengue Hemorrhagic Fever (DHF), Leptospirosis, Skin Diseases, and Acute Respiratory Infections (ARI). In these emergency situations, the speed and accuracy of diagnosis are determining factors for victims' safety. However, the reality on the ground shows that access to medical experts is often cut off due to damaged infrastructure, coupled with an unbalanced doctor-to-refugee ratio in disaster shelters. This study aims to develop a mobile-based (Android) expert system for post-flood disease diagnosis that can operate offline (offline-first architecture). This system applies the Certainty Factor method to handle the uncertainty of symptoms experienced by users, thereby providing an accurate percentage of disease confidence levels comparable to an initial diagnosis by a medical expert. The testing results show that the system successfully identified the five diseases with an accuracy rate of 88.5% based on 50 real-case test data. Usability testing using the System Usability Scale (SUS) yielded a score of 78, meaning the application is in the acceptable category and is easy to use by laypeople in disaster-prone areas.
Web-Based 360 Virtual Tour Prototype Using the Waterfall Method: A Promotional Solution for Aura Boarding House in Riau Province Nurul Qolbi; Abdullah
Jurnal Armada Informatika Vol 10 No 1 (2026): Juni
Publisher : STMIK Methodist Binjai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36520/jai.v10i1.289

Abstract

This study aims to design a web-based digital marketing platform prototype for the Aura Boarding House (kost putri) in Tembilahan, Riau, utilizing the Waterfall method and the Pannellum panorama viewer. The primary problem faced by the owner is suboptimal digital promotion despite its highly strategic location near campuses, schools, and community activity centers. The research methodology focuses on the system analysis and design phases. Requirement data were gathered through direct observation, informal interviews with the owner, and facility documentation using an iPhone 13 camera. The results of this design-phase study consist of system requirement documents, a one-page website structure, interface designs, a six-scene virtual tour storyboard, a booking procedure via Google Form integrated with Google Sheets, a monthly billing reminder blueprint via WhatsApp, and testing scenarios utilizing the black-box method. This study concludes that the marketing media design featuring a 360-degree virtual tour can deliver boarding house information transparently, clearly, and economically, serving as a concrete blueprint ready for full implementation in the subsequent thesis development stage
Classification of Chicken Egg Price Patterns at Partner Farms Using the C4.5 Method Kristin Lourensi Sitompul; Petti Indrayati Sijabat; Puteri Fajar Addini; Risda Sariah Cristina Siringo-ringo; Syahnaila Mayza Kirana
Jurnal Armada Informatika Vol 10 No 1 (2026): Juni
Publisher : STMIK Methodist Binjai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36520/jai.v10i1.290

Abstract

This study aims to classify chicken egg price patterns at Sunardi Farm from July 2021 to August 2025 using a data mining method based on the C4.5 algorithm. Changes in chicken egg prices, which are influenced by various factors—including production volume, feed costs, and major holiday periods—often create uncertainty for farmers when making decisions regarding production and marketing. The research data consisted of 50 historical data points comprising several price-determining attributes and grouped into two classes: Medium and High. The C4.5 algorithm was applied by building a decision tree model based on the gain ratio to identify the attributes with the most significant influence on price changes. The results indicate that production volume is the primary factor influencing chicken egg price patterns, with the number of major holidays serving as a supporting factor. The resulting classification model achieved an accuracy rate of 80%, indicating that the C4.5 algorithm is quite effective in classifying chicken egg price patterns. The resulting decision rules are expected to serve as a basis for decision-making regarding production planning, sales strategies, and distribution management at Sunardi Farm.
Optimizing the Determination of Tutor Professionalism Fields Based on the PROMETHEE Method at LPK2 Pascom Medan Eferoni Ndruru; Fince Tinus waruwu; Mardiah Nasution; Arfiana Agustiana Tarigan
Jurnal Armada Informatika Vol 10 No 1 (2026): Juni
Publisher : STMIK Methodist Binjai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36520/jai.v10i1.295

Abstract

The alignment between tutors' professional expertise and their competencies is a key factor in creating effective learning processes at LPK2 Pascom Medan, a computer education and training institution. The current practice of assigning tutors to teaching fields relies primarily on managerial judgment, resulting in decisions that may not be entirely objective due to the need to consider multiple criteria, including educational background, teaching experience, professional certifications, technical competence, and performance evaluation results. This complexity necessitates a systematic approach to support decision-making. This study aims to design and implement a Decision Support System for determining tutors' professional specialization by applying the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE). The PROMETHEE method was selected because it can evaluate and rank alternatives based on multiple criteria through the calculation of leaving flow, entering flow, and net flow values. The research methodology consists of problem identification, data collection through observation, interviews, and documentation, determination of evaluation criteria and their respective weights, followed by the calculation and ranking of alternatives using the PROMETHEE method. The expected outcome is a Decision Support System capable of providing objective, consistent, and transparent recommendations for assigning tutors to appropriate professional fields. The proposed system is expected to improve the accuracy of tutor placement, enhance the quality of learning, and serve as a valuable reference for human resource management in education and training institutions.
Stock Price Prediction In Indonesia Using Deep Learning With Long Short-Term Memory Algorithm Kevin; Octara Pribadi; Leony Hoki
Jurnal Armada Informatika Vol 10 No 1 (2026): Juni
Publisher : STMIK Methodist Binjai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36520/jai.v10i1.221

Abstract

Stock price prediction is one of the complex problems in the financial world because it is non-linear and influenced by many external factors. This study aims to apply the Long Short-Term Memory (LSTM) algorithm, a variant of Recurrent Neural Network (RNN) within the Deep Learning framework, to predict the closing price of banking sector stocks in the Indonesian capital market. The data used comes from five major banking issuers on the Indonesia Stock Exchange, namely BBCA, BBTN, BBRI, BBMRI, and BBNI, obtained from the Kaggle platform. The method used is a literature study by reviewing relevant literature related to the application of LSTM to financial time series data. The main parameter configurations include 50 hidden units, 100 epochs, a batch size of 32, a learning rate of 0.001, and a ReLU activation function with Adam optimizer. Model evaluation was carried out using the Root Mean Square Error (RMSE) metric of 6.61%, Mean Absolute Error (MAE) of 1.74%, Mean Square Error (MSE) of 43.69%, and a coefficient of determination R² of 0.718. The results show that the LSTM model is able to produce predictions close to actual values, reduce the risk of overfitting, and can be used as an investment decision-making tool for investors in the Indonesian stock market.
Evaluation of User Acceptance of Online Transportation Applications Using User Acceptance Testing Muhammad Arizal Dwisakti; Suci Ramadhani; Pristiwanto
Jurnal Armada Informatika Vol 10 No 1 (2026): Juni
Publisher : STMIK Methodist Binjai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36520/jai.v10i1.278

Abstract

This study evaluates user acceptance of online transportation applications using a questionnaire-based User Acceptance Testing (UAT) approach. The assessment covers vehicle ordering, location tracking, payment, navigation, processing speed, ease of use, comfort, and accessibility. Data were collected online from 30 active users through ten statements measured on a five-point Likert scale. Instrument validity was examined using the Pearson Product Moment correlation, while internal consistency was assessed using Cronbach’s Alpha. All items exceeded the critical correlation value of 0.361, with coefficients ranging from 0.4039 to 0.7380. The Alpha coefficient of 0.8148 indicated good instrument reliability. The observed score was 1,214 out of a maximum of 1,500, producing a UAT percentage of 80.93%. Under the interpretation interval adopted in this study, the application category was very feasible and reflected a high level of user acceptance. However, the result represents aggregated user perceptions and does not demonstrate that every function is technically error-free. The findings provide an initial evaluation, while future work should examine a specific application through controlled task scenarios, a larger sample, and item-level analysis.
A Multi-Role Web-Based Customer Relationship Management (CRM) Information System Using the Agile Method at Telkom Witel Lampung–Bengkulu Muhammad Ikhsan; Intan Nur Laila; Rahayu Indah Lestari; Anindita Tri Mulia; Allwine
Jurnal Armada Informatika Vol 10 No 1 (2026): Juni
Publisher : STMIK Methodist Binjai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36520/jai.v10i1.282

Abstract

This study discusses the development of a web-based Customer Relationship Management (CRM) Information System at PT Telekomunikasi Indonesia, Tbk Witel Lampung-Bengkulu by integrating three main roles: Admin, Government Service, and Shared Service General Support. The main problem identified is that user data, regional data, project opportunities, marketing activities, customer data, customer interactions, and payment monitoring were still mostly managed manually using Microsoft Excel, which could cause data duplication, reporting delays, and input errors. This study applied the Agile method through planning, design, development, testing, deployment, and review stages. The system was developed using PHP with the Laravel framework, MySQL database, and Bootstrap to create a responsive user interface. The developed features include login, user management, regional data management, dashboard, Government Service project opportunity management, marketing activity records, customer data, interaction history, payment monitoring, filters, import, export, and user profile. System testing was conducted using Black Box Testing and User Acceptance Testing to ensure that each function met user requirements. The resulting system integrates administration, government sales, and customer collection processes into one platform, making data more centralized, monitoring faster, and reporting more accurate and well documented.
Implementation of the Apriori Algorithm to Identify Sales Patterns at YES 248 Store Damiana Desrimawarni Waruwu; Porlina Hulu; Berto Nadeak
Jurnal Armada Informatika Vol 10 No 1 (2026): Juni
Publisher : STMIK Methodist Binjai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36520/jai.v10i1.287

Abstract

YES 248 Store generates daily sales transaction data that have primarily been retained as administrative records, leaving relationships among products underutilized in decision-making. This study identifies consumer purchasing patterns by applying the Apriori algorithm to 20 transactions recorded in April 2026 and involving five products. The data were cleaned, product names were standardized, and each transaction was transformed into an itemset. The minimum support and minimum confidence thresholds were set at 30% and 60%, respectively. The analysis produced three frequent 1-itemsets: Milo Activ-Go with 80% support, 5Days Croissant Choco with 65%, and Ovaltine UHT with 45%. The combination of 5Days Croissant Choco and Milo Activ-Go achieved the highest pair support at 60%, whereas the three-product combination achieved 35% support. The highest-confidence rule was {5Days Croissant Choco, Ovaltine UHT} => {Milo Activ-Go} at 100%, while the strongest single-antecedent rule was 5Days Croissant Choco => Milo Activ-Go at 92.31%. These findings can support product bundling, shelf arrangement, and inventory prioritization. Nevertheless, the results remain exploratory because the number of analyzed transactions is limited.

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