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INDONESIA
Sistemasi: Jurnal Sistem Informasi
Published by Universitas Islam Indragiri
ISSN : 23028149     EISSN : 25409719     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Sistemasi adalah nama terbitan jurnal ilmiah dalam bidang ilmu sains komputer program studi Sistem Informasi Universitas Islam Indragiri, Tembilahan Riau. Jurnal Sistemasi Terbit 3x setahun yaitu bulan Januari, Mei dan September,Focus dan Scope Umum dari Sistemasi yaitu Bidang Sistem Informasi, Teknologi Informasi,Computer Science,Rekayasa Perangkat Lunak,Teknik Informatika
Arjuna Subject : -
Articles 920 Documents
 78   79   80   81   82 
Sentiment Analysis on the PT Pertamina Corruption Case using IndoBERT and RCNN Methods Kusoema, Wildan Jaya; Ibrahim, Ichsan
Sistemasi: Jurnal Sistem Informasi Vol 14, No 5 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i5.5392

Abstract

This study aims to evaluate the performance of a hybrid IndoBERT-RCNN model in classifying public sentiment toward the PT Pertamina corruption case, with a focus on how different hyperparameter combinations affect model accuracy. The dataset consists of 10,078 YouTube comments collected via the YouTube Data API, which were then preprocessed, automatically labeled using an Indonesian-language RoBERTa model, and balanced through class distribution techniques including undersampling and contextual embedding-based augmentation with IndoBERT. The model architecture integrates IndoBERT as a feature extractor and RCNN as the classifier, and was tested using various combinations of learning rates and batch sizes. Experimental results show that the optimal configuration was achieved with a learning rate of 2e-5 and a batch size of 16, resulting in an accuracy of 84% and an F1-score of 83%. While the model demonstrated strong performance in classifying negative comments, accuracy for neutral and positive classes was relatively lower due to semantic overlap and ambiguity in user expressions. This study contributes to Indonesian-language sentiment analysis by: 1. Integrating the IndoBERT-RCNN architecture for social-political issues, 2. Systematically evaluating hyperparameter combinations for three-class public opinion data, and 3.Utilizing YouTube comments as a relevant source of informal public discourse. The findings have potential applications in real-time digital public opinion monitoring systems for strategic national issues.
Optimization of the Production Process using the Theory of Constraints (TOC) Method based on Drum-Buffer-Rope (DBR) Improvements Widyarsa, Destiara Nabila; Rochmoeljati, Rr.
Sistemasi: Jurnal Sistem Informasi Vol 14, No 4 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i4.5292

Abstract

One footwear manufacturing company located in Surabaya has experienced an increase in production demand for both women's and men's sandals in recent years. The main issue faced by the company is the presence of bottlenecks at specific workstations due to unbalanced capacity, which disrupts the smooth flow of the production process. To address this issue, the study applies the Theory of Constraints (TOC) method based on the Drum-Buffer-Rope (DBR) concept, in combination with Linear Programming (LP). The research stages include identifying the constraints, exploiting the constraints, subordinating non-constraints, and elevating the constraints. The analysis results indicate that the coating and bonding workstations are the main constraints affecting the system's throughput. To overcome this, overtime was added at these workstations to increase production capacity. The implementation results showed an improvement in throughput from IDR 39,849,260 with 1,594 units to IDR 46,490,330 with 1,860 units, reflecting a 14.3% increase. These findings demonstrate that the application of TOC and DBR can effectively balance the production flow, optimize bottleneck workstations, and enhance overall production throughput.
Implementation of Profile Matching in Evaluating Customer Satisfaction for PT. BKZ Expedition Services marfuah, marfuah; Adam, Steffi; Husin, Abdullah; Tanjaya, David
Sistemasi: Jurnal Sistem Informasi Vol 14, No 4 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i4.5212

Abstract

Evaluation of service satisfaction is essential for decision-making related to efforts to improve service quality. PT. BKZ’s expedition service conducts customer satisfaction evaluations as part of its competitive strategy. The satisfaction assessment for PT. BKZ's import goods delivery service is carried out using five criteria: Reliability, Responsiveness, Assurance, Empathy, and Tangibles. The evaluation process employs the Profile Matching method, which functions to identify the competency gap between actual data values and the predefined profile benchmarks. The questionnaire was distributed online and filled out by PT. BKZ customers. The results indicate that the implementation of the Profile Matching method is effective in supporting decision-making related to service improvement and enhancement strategies at PT. BKZ. The three lowest-scoring criteria that require follow-up action are Empathy (38), Assurance (38.65), and Responsiveness (39.3). These aspects must be improved, particularly among frontline staff at PT. BKZ. The next policy direction should focus on maintaining current staff performance and providing motivation to foster continuous improvement. This can be achieved by offering performance-based bonuses to employees with the highest service satisfaction evaluation scores and providing training programs for those with the lowest performance scores.
Fake News Detection using the Random Forest Algorithm Setyadin, Rahmat Dipo; Winasis, Reza Handaru; Triyono, Gandung
Sistemasi: Jurnal Sistem Informasi Vol 14, No 3 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i3.4995

Abstract

Detecting fake news has become increasingly important in the digital era, where false information can spread rapidly and significantly influence public opinion. The dissemination of fake news can lead to public distrust in the media, economic losses, and even social conflict. This study aims to develop an effective fake news detection system using the Random Forest algorithm approach. The dataset used in this research was collected from the official Kominfo website and includes attributes such as title, description, author, date, category, page, news URL, and image URL. The text preprocessing process involves tokenization, stop word removal, text normalization, and feature extraction using Term Frequency and Inverse Document Frequency (TF-IDF) to generate numerical representations of the textual data. The Random Forest model was evaluated using accuracy, precision, recall, and F1-score metrics to assess its effectiveness in detecting fake news. The results show that the model performed exceptionally well, with k-fold cross-validation (k=5) yielding high average accuracy—Random Forest achieved an accuracy of 0.9890.
Koptihub: A UI/UX Design for Transparent Procurement using a User-Centered Design Approach Satyaninggrat, Luh Made Wisnu; Hamijaya, Prasis Damai Nursyam
Sistemasi: Jurnal Sistem Informasi Vol 14, No 5 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i5.5126

Abstract

The traditional procurement process faces significant inefficiencies and transparency issues, including low efficiency, limited oversight, and challenges in securing competitive supplier engagement and a stable soybean supply. To address these issues, this study aims to design and evaluate Koptihub, a prototype that enhances communication with importers, improves transparency in price comparisons, streamlines stock management, and optimizes transaction monitoring and decision-making. The research employs the User-Centered Design (UCD) approach, integrating User Experience (UX) principles and cooperative member feedback to develop a prototype using Figma. The system's effectiveness, clarity, and user-friendliness were assessed through usability testing with 15 participants using the System Usability Scale (SUS). The prototype incorporates key features such as notifications, incoming offers, price offer status, orders in process, order delivery status, payments, refunds, and a chat function for cooperative-importer communication. The usability test results yielded an SUS score of 82.17, classified as an A grade, indicating high usability and strong user acceptance. These findings confirm that the system effectively supports efficient price selection, order tracking, and enhanced transparency in procurement. This study introduces an innovative e-procurement solution tailored for cooperatives, demonstrating the potential of digital procurement platforms to transform cooperative procurement processes. The proposed model serves as a practical framework that can be adapted by similar cooperatives to improve procurement efficiency and supplier engagement.
The Influence of Promotion, Service Quality, and Electronic Word of Mouth on Customer Loyalty through Customer Satisfaction on the Instagram Account @rooftopin.nesia Fauzan, Muhammad Fairuz; Wedhasmara, Ari; Tania, Ken Ditha; Putra, Apriansyah
Sistemasi: Jurnal Sistem Informasi Vol 14, No 4 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i4.5196

Abstract

The use of social media has become a key strategy in business development in the era of information technology. Rooftopin Café utilizes social media to build relationships with customers; however, its impact on customer loyalty remains uncertain. This study aims to analyze the influence of promotion, service quality, and electronic word of mouth (e-WOM) on customer loyalty, with customer satisfaction as a mediating variable. Using a quantitative approach, data were collected from 120 respondents—customers who have visited Rooftopin Café in Palembang and follow the Instagram account @rooftopin.nesia. The data were analyzed using SmartPLS. The results show that promotion, service quality, and e-WOM have a positive and significant effect on customer satisfaction. Furthermore, customer satisfaction has a positive and significant influence on customer loyalty. In addition, customer satisfaction is proven to mediate the relationship between service quality and customer loyalty, indicating complementary mediation. This implies that service quality affects customer loyalty not only directly but also indirectly through customer satisfaction.
Sentiment Analysis of X Application Users on Bitcoin Using the Naïve Bayes Method Optimized with Particle Swarm Optimization (PSO) Muhammad, Raja Allifin; Haerani, Elin; Wulandari, Fitri; Oktavia, Lola
Sistemasi: Jurnal Sistem Informasi Vol 14, No 4 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i4.5390

Abstract

Advancements in technology and social media have significantly transformed the way individuals express their opinions—one of which is toward decentralized digital currencies that utilize blockchain technology to enable peer-to-peer transactions, such as Bitcoin. This study aims to evaluate user sentiment toward Bitcoin by implementing the Naïve Bayes method optimized with Particle Swarm Optimization (PSO), using data gathered from the X application (formerly Twitter). The data were collected through web scraping of user posts containing the keyword “Bitcoin.” Text preprocessing was performed to enhance data quality, followed by feature extraction using the Term Frequency–Inverse Document Frequency (TF-IDF) approach to convert textual data into numerical representations. Model performance was evaluated using accuracy, precision, recall, and F1-score metrics. Initial results show that the Naïve Bayes classifier performs well in sentiment classification. The integration of PSO as an optimization method improved classification performance from 66.14% to 69.14%. This study contributes to a deeper understanding of public opinion on Bitcoin and demonstrates the effectiveness of combining Naïve Bayes and PSO in text-based sentiment analysis.
Decision Support System for Selecting Village Fund BLT Recipients using ROC and WASPAS Methods Manurung, Marisah Elfrida; Desnelita, Yenny; Hajjah, Alyauma; Duha, Yermias
Sistemasi: Jurnal Sistem Informasi Vol 14, No 4 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i4.4086

Abstract

The Village Fund Direct Cash Assistance (BLT) Program is a government initiative aimed at improving social welfare, reducing inequality, and supporting economically disadvantaged communities. However, in practice, the process of determining BLT recipients often faces issues of subjectivity and lack of transparency. This study aims to develop a Decision Support System (DSS) to assist village authorities in selecting BLT recipients objectively and accurately by utilizing the Rank Order Centroid (ROC) and Weighted Aggregated Sum Product Assessment (WASPAS) methods. The ROC method is used to assign weights to each criterion based on their level of importance, while the WASPAS method is applied to rank the recipient candidates according to the established weights. The DSS is developed as a web-based application to ensure easy access for village administrators. System testing results indicate that the ROC method consistently generates weights that reflect the prioritization of criteria, while the WASPAS method proves effective in producing final rankings of potential recipients. As a result, village leaders can make more objective and targeted decisions in determining BLT beneficiaries.
Design of an Archival Information System for LLDIKTI Region VIII using the Research and Development Method Pamungkas, Dionisius Adi Prabu; Rahardja, Yani
Sistemasi: Jurnal Sistem Informasi Vol 14, No 3 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i3.5160

Abstract

The LLDIKTI Region VIII office is an institution responsible for facilitating and supervising higher education institutions in the Bali and Nusa Tenggara regions, particularly through the UK3 unit in managing archives. Currently, the archival management at the LLDIKTI Region VIII office relies solely on the centralized Electronic Official Document Information System (SINDE) provided by the government, without any local system to support independent backup and digitalization of records. This creates issues when there are disruptions in access to the central system or when more flexible, localized archive management is required. Therefore, there is a need for technology that enables local backup and the digitalization of physical documents into digital formats. This study adopts the Research and Development (R&D) method, emphasizing a balance between theory, design, and implementation based on user needs, existing problems, and user preferences. The result of this study is the design of a web-based User Interface (UI) and User Experience (UX) for the Digital Archive Center Information System of LLDIKTI Region VIII (PADI8). System usability testing was conducted using the System Usability Scale (SUS) method with five respondents, consisting of UK3 archival staff (3 women and 2 men). Data were collected through interviews and direct observation of system usage. The SUS scores were 83.7 from the admin perspective and 83 from the general user perspective. Based on the SUS interpretation criteria, the system falls into Grade A, with an adjective rating of “excellent” and an acceptability range of “acceptable,” indicating a high level of user satisfaction. This system is expected to improve the office’s efficiency, security, and autonomy in digital archive management and serve as an initial step toward sustainable digital transformation within the LLDIKTI Region VIII environment.
Sentiment Analysis of Rohingya Refugees in Aceh using Support Vector Machine (SVM) and Multinomial Logistic Regression Baliputra, Gigih Army Buana; Kacung, Slamet; Santoso, Budi
Sistemasi: Jurnal Sistem Informasi Vol 14, No 3 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i3.5159

Abstract

The rapid development of information technology affects the massive dissemination of information. Social media is one of them, and it contributes to communication and information technology. Information about Rohingya ethnic refugees in Aceh has spread widely on social media. This research aims to analyze public sentiment regarding ethnic Rohingya refugees in Aceh on X and YouTube, categorized into positive, neutral, and negative. This study aims to develop an application that uses the Support Vector Machine (SVM) and Multinomial Logistic Regression techniques to conduct sentiment analysis on public opinion with positive, neutral, and negative classifications regarding Rohingya refugees in Aceh. The 3683 comments collected through web crawling were categorized into positive, negative, and neutral sentiments. The analysis results show that 2112 data were classified as negative sentiments, 1400 as neutral sentiments, and 171 as positive sentiments. Based on the test results, the SVM and Multinomial Logistic Regression methods have similar accuracy of 83.18%. However the SVM method obtained 74.65% precision and 65.15% recall. Meanwhile, the Multinomial Logistic Regression method obtained 75.28% precision and 66.84% recall.

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