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INDONESIA
Jurnal Mandiri IT
Published by Institute of Computer Science
ISSN : 23018984     EISSN : 28091884     DOI : https://doi.org/10.35335/mandiri
Core Subject : Science, Education,
Computer Science & IT Library & Information Science Mathematics
The Jurnal Mandiri IT is intended as a publication media to publish articles reporting the results of Computer Science and related research.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 3 Documents
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Search results for , issue "vol. 15 no. 2 (2026): computer science and field." : 3 Documents clear
Sentiment analysis of public opinion toward government regulations concerning the implementation of tabungan perumahan rakyat (Tapera) using the convolutional neural network (CNN) model on social media X M. Iqbal Noviansyah; Kusrini Kusrini
Jurnal Mandiri IT Vol. 15 No. 2 (2026): Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v15i2.559

Abstract

Sentiment analysis is one of the applications of Natural Language Processing (NLP) for identifying public opinion on social media. Although previous studies on Tapera sentiment analysis have applied conventional machine learning and transformer-based approaches, limited attention has been given to integrating automatic lexicon-based sentiment labeling with semantic word representation and deep learning classification within a unified framework. This study proposes an approach that integrates the Indonesian Sentiment Lexicon (InSet), Word2Vec, and Convolutional Neural Network (CNN) to classify public sentiment toward the Tabungan Perumahan Rakyat (Tapera) policy on social media X. A total of 1,291 tweets were processed through the preprocessing stage and automatically labeled using InSet. Word2Vec was employed to construct semantic word representations that were used as the initial weights of the CNN embedding layer. The proposed model was evaluated using four hold-out data split scenarios and compared with BiLSTM and Random Forest. The experimental results showed that the 80:20 configuration achieved the best performance with an accuracy of 74.52%, outperforming BiLSTM (71.43%) and Random Forest (69.88%). The novelty of this study lies in integrating automatic sentiment labeling using the Indonesian Sentiment Lexicon (InSet), semantic representation through Word2Vec, and CNN-based classification within a unified framework, together with an empirical evaluation of different train-test split ratios for Tapera policy sentiment analysis. These findings demonstrate that the proposed approach provides competitive sentiment classification performance while reducing dependence on manual sentiment annotation.
Development of A Web-Based Study Program Accreditation Monitoring Information System for The Information Systems and Technology Study Program at Universitas Muhammadiyah Kotabumi Intan Addies Adila; M Abu Jihad Plaza R
Jurnal Mandiri IT Vol. 15 No. 2 (2026): Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v15i2.571

Abstract

Study program accreditation requires structured management of documents, progress monitoring, task allocation, validation, deadline control, and report preparation. At the Information Systems and Technology Study Program, Universitas Muhammadiyah Kotabumi, the previous accreditation monitoring process faced several challenges, including scattered document storage, difficulties in monitoring the progress of each criterion, and unintegrated document coordination and retrieval. This study aims to develop a web-based study program accreditation monitoring information system capable of integrating document management and monitoring processes within a centralized system. System development was carried out through the stages of requirements identification, data collection, prototype design, design evaluation and refinement, implementation, and system testing. The system was implemented using Laravel, PHP, Bootstrap, and MySQL, with UML used for system design. The developed features include a monitoring dashboard, document management, progress monitoring for each accreditation criterion, timeline management, reminders and notifications, document verification, document search, audit trail, document versioning and revision, and reporting. Testing was conducted using the Black Box Testing method on the main system functions, including the monitoring dashboard, accreditation progress monitoring, document search, document verification, and report generation. The test results show that all tested functions produced outputs consistent with the predefined test scenarios and were declared successful. The developed system provides a more centralized accreditation monitoring workflow, enabling document information, progress, verification status, and reports to be managed within a single web-based application environment
Real-Time Counting Web Application for DPD IMM Lampung Elections Using Laravel Muhammad Abdurasyid Dzakirah; Adi Wibowo
Jurnal Mandiri IT Vol. 15 No. 2 (2026): Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Muhammadiyah Student Association (IMM) Lampung at the Regional Deliberation forum is still conducted conventionally using paper ballots, making printing, casting, and counting relatively time-consuming and prone to recording errors, while live result information is not available to participants. This study aims to design and build a Laravel 12-based Real-Time Counting web application equipped with Laravel Reverb/WebSocket to support the election of the Chairperson and Field Coordinator of DPD IMM Lampung. The system was developed using the waterfall method, modeled with Unified Modeling Language (UML), and supported by a MySQL database. The implementation integrates voter-right validation using membership card numbers and tokens, digital ballot casting, anti-double-vote enforcement through a database unique constraint, real-time result broadcasting through the VoteCasted event, and a re-voting mechanism for tied results. Black Box Testing and User Acceptance Testing (UAT) were defined as evaluation procedures for assessing functional suitability and user acceptance. The article presents the testing scenarios and UAT indicators used in the evaluation. The implemented system provides the functional basis for replacing the manual ballot workflow and presenting election results more quickly and transparently The evaluation included 14 Black Box Testing scenarios and UAT with 20 respondents (15 voters/participants and 5 committee/administrator users). The UAT obtained a total score of 706 out of 800, equivalent to 88.25%, categorized as Very Good. The Black Box table documents the 14 functional scenarios and expected outputs; quantitative pass/fail execution totals were not separately recorded in the source testing table

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