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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 40 Documents
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Search results for , issue "Vol 14, No 2 (2025): Sistemasi: Jurnal Sistem Informasi" : 40 Documents clear
Web-based New Student Registration System using User-Centered Design Method Farhan, Burait; Razilu, Zila; Rifai, Sitti Najmia
Sistemasi: Jurnal Sistem Informasi Vol 14, No 2 (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.v14i2.5026

Abstract

This study aims to design and develop a web-based new student registration system using the User-Centered Design (UCD) approach. The UCD method is applied to ensure that the resulting system meets user needs, enhances efficiency, and provides an optimal user experience. This system is designed as a solution to the challenges of manual registration at MIS Hubbul Wathan Toli-Toli, such as document accumulation, long queues, and difficulties in data management. The research stages include observation, interviews, literature review, wireframe design, and design evaluation through usability testing. The test results indicate that the system demonstrates good to excellent usability across the dimensions of Learnability, Efficiency, Memorability, Errors, and Satisfaction, based on a Likert scale analysis (1–5). The system enables a more efficient registration process, reduces data entry errors, and improves user convenience. This study contributes to the development of an information system tailored to user needs and opens opportunities for further enhancements, such as integrating additional features and improving user experience through continuous evaluation.
Productivity Analysis of Production Units using Objective Matrix and Root Cause Analysis Methods Nugroho, Ayyasy; Aryanny, Enny
Sistemasi: Jurnal Sistem Informasi Vol 14, No 2 (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.v14i2.5059

Abstract

PT XYZ is a company engaged in the liquefied petroleum gas (LPG) processing industry. In recent years, the company has faced significant fluctuations in production, deviating from its established targets. This issue has led to a decline in productivity over time. To address this, the study applies the Objective Matrix (OMAX) method to analyze key performance factors measuring LPG productivity from October 2023 to September 2024. The OMAX calculations reveal fluctuations, with the highest achievement recorded in August 2024 at 961.8 and the lowest in February 2024 at 173. Root Cause Analysis (RCA) was conducted to identify the primary causes of productivity decline, uncovering three critical factors: raw materials (Ratio 1), machine operating hours (Ratio 3), and idle machine hours (Ratio 4). These factors significantly contributed to reduced productivity due to unstable feed gas supply, high contamination levels affecting feed gas quality, machine downtime, and insufficient supervision and employee training. To enhance LPG productivity in the future, this study recommends several improvement strategies, including the development of gas exploration and extraction, strengthening raw material quality monitoring systems, implementing a more structured maintenance and repair plan, and providing intensive training programs for workers.
User Satisfaction Analysis of the Muslim Pro Application using PIECES Method anjani, sri; Megawati, Megawati; M.Afdal, M.Afdal; Rahmawita, Medyantiwi
Sistemasi: Jurnal Sistem Informasi Vol 14, No 2 (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.v14i2.5077

Abstract

User satisfaction serves as a benchmark for applications and helps developers improve the quality of future applications. Muslim Pro is an application that provides various services for Muslims. This app is designed to assist Muslims in performing their religious duties more easily and systematically. Numerous negative user reviews about Muslim Pro indicate that user satisfaction regarding the company's performance is still low. The aim of this research is to determine the level of satisfaction with the Muslim Pro application based on user experience. To measure user satisfaction, this study employs the PIECES method, which consists of Performance, Information, Economic, Control, Efficiency, and Service. Data collection was conducted by distributing a questionnaire to 100 active students at UIN Suska Riau who use the Muslim Pro application. The results for each variable received the following average scores: the Performance variable scored 4.38, indicating satisfaction; the Information variable scored 4.27, indicating satisfaction; the Economic variable scored 4.26, indicating satisfaction; the Control variable scored 3.97, indicating satisfaction; the Efficiency variable scored 4.24, indicating satisfaction; and the Service variable scored 4.41, indicating satisfaction. Therefore, the overall average user satisfaction score is 4.25, which indicates a satisfactory level of service provided by Muslim Pro, categorizing it as "satisfied." This means that the Muslim Pro application plays a significant role in enhancing service quality, resulting in user satisfaction and positive feedback.
Design of a Web-based Letter Making Information System for SD Negeri 2 Indonesiana, Tidore Islands City bahta, said d; -, Rahmajati
Sistemasi: Jurnal Sistem Informasi Vol 14, No 2 (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.v14i2.4721

Abstract

The use of Microsoft Word for letter creation is neither effective nor efficient, as it requires a significant amount of time to search for data from printed or digital documents, adjust letter templates, and manually re-enter data, increasing the likelihood of errors. Therefore, a system that can automatically integrate and connect data is needed to streamline the letter creation process. This research develops a Web-Based Letter Information System using the waterfall methodology, which includes stages such as analysis, design, implementation, testing, and maintenance. The final result of this study is a web-based letter information system designed to simplify the letter creation process for staff and students.
Performance Evaluating of Honeyword Generation Methods: Traditional versus AI Alkazzaz, Shahad Abdulkhalik; Mohammed, Saja Jasim
Sistemasi: Jurnal Sistem Informasi Vol 14, No 2 (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.v14i2.4991

Abstract

As the number of people using computers has increased, the risks to digital systems have increased too. That has necessitated the development of new techniques to defend against hackers. Authentication systems based on text passwords are an example of digital systems that face risks through internet use. Therefore, it was necessary to provide security and reliability to users while protecting their passwords. In the authentication database, A technique known as honeywords was used. In the digital world, honeywords are a popular technique used to enhance the security of users' actual passwords and are an additional strong layer of security. The benefit of this technique is its ability to detect unauthorized access attempts to the systems. In this paper, three of the most popular techniques for honeyword generation and other well-known intelligence algorithms are put in comparison using some evaluation metrics to study the performance of each one. The results illustrate a contrast in the performance of different techniques and intelligence algorithms based on the Hamming distance value.
Sentiment Analysis of the Issue of Eliminating the Independent Curriculum using the Naïve Bayes Classifier Algorithm Hidayat, Ainul Haq Nurridha Warahmat; Erfina, Adhitia
Sistemasi: Jurnal Sistem Informasi Vol 14, No 2 (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.v14i2.5039

Abstract

Sentiment analysis regarding the issue of eliminating the Independent Curriculum is a crucial tool for understanding public opinion, particularly among students and teachers, on changes in the education system. This study applies the Naïve Bayes Classifier method to classify positive and negative sentiments from data collected through social media platforms such as YouTube. The collected data undergoes text preprocessing techniques, including cleaning, case folding, tokenization, stopword removal, and stemming, to enhance model accuracy. The analysis is conducted using Python 3.12.3 in Google Colab with the Naïve Bayes Classifier algorithm. The results demonstrate strong performance, with a positive precision of 5% and a recall of 68%, using an 80% training and 20% testing data ratio. Findings indicate that the overall sentiment leans more negative than positive, with the majority of respondents supporting the elimination of the Independent Curriculum. This study validates the effectiveness of the Naïve Bayes method in sentiment analysis and highlights the importance of text preprocessing in improving model accuracy. Furthermore, there is potential for exploring other methods, such as word embedding and deep learning, to enhance model performance. The findings of this study can serve as a valuable reference for policymakers in understanding public opinion before making further decisions in the education sector.
Public Sentiment Analysis of Nadiem Makarim as Minister of Education, Culture, Research, and Technology using Support Vector Machine (SVM) Putri, Shasha Ramadhani; Arifin, Muhammad; Supriyono, Supriyono
Sistemasi: Jurnal Sistem Informasi Vol 14, No 2 (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.v14i2.5067

Abstract

Social media has become a primary platform for expressing opinions on the performance of public officials, including Nadiem Makarim, the Minister of Education, Culture, Research, and Technology. Opinions on Twitter reflect diverse public perceptions, making sentiment analysis essential to understanding these trends. This study aims to analyze public sentiment toward Nadiem Makarim’s performance and optimize sentiment classification models in handling data imbalance. The methodology employs a Support Vector Machine (SVM) with Term Frequency-Inverse Document Frequency (TF-IDF) through three scenarios: tuning TF-IDF parameters, selecting the best SVM kernel, and applying the Synthetic Minority Oversampling Technique (SMOTE) to address data imbalance. Experimental results indicate that the combination of max_features = 2000 and min_df = 2 yields the best F1-score of 68%, with the linear kernel being the most stable. Although SMOTE successfully balances class distribution, accuracy slightly decreases from 68% to 66%.
A Comparative Study of Deep Learning’s Performance Methods for News Article using Word Representations Azhar, Iman Saladin B.; Sari, Winda Kurnia; Gumay, Naretha Kawadha Pasemah
Sistemasi: Jurnal Sistem Informasi Vol 14, No 2 (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.v14i2.5090

Abstract

In natural language processing (NLP), text classification is a crucial task that involves analyzing textual data, which often has high dimensionality. A good word representation is essential to address this challenge, and the word representation using GloVe is one of the popular methods that provides pre-trained word representations in high-dimensional vectors. This research evaluates the effectiveness of three deep learning techniques Convolutional Neural Network (CNN), Deep Neural Network (DNN), and Long Short-Term Memory (LSTM) for online news classification using 300-dimensional GloVe word representations. The CNN model utilizes convolutional and pooling layers to extract local features, the DNN relies on dense layers to learn abstract representations, while the LSTM excels at capturing long-term dependencies between words. The results show that the LSTM model achieved the best accuracy at 93.45%, followed by CNN at 91.24%, and DNN at 90.67%. The superiority of LSTM is attributed to its ability to effectively capture temporal relationships and context, while CNN offers efficiency with faster training times. Although DNN produced solid performance, it is less optimal in understanding word sequences. These findings indicate that LSTM outperforms the other models in online news text classification tasks.
User Evaluation of the Bibit Reksadana Application using the User Experience Questionnaire (UEQ) of Semarang Regency pratama, raihan daffa arya; Tanaamah, Andeka Rocky
Sistemasi: Jurnal Sistem Informasi Vol 14, No 2 (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.v14i2.4832

Abstract

According to data from the Indonesian Central Securities Depository (KSEI), by the end of 2023, the Bibit mutual fund application had reached 4.6 million users. This phenomenon has generated diverse responses from the public, particularly between novice and experienced investors. This study aims to evaluate the user experience of the Bibit application using the User Experience Questionnaire (UEQ) method. Data was collected through questionnaires distributed using purposive sampling, targeting individuals who actively use the application. The evaluation focuses on six UEQ aspects: attractiveness, clarity, efficiency, dependability, stimulation, and novelty, analyzed using the Data Analysis Tools developed by the UEQ team. The findings reveal variations in user experience, providing insights into both user satisfaction and challenges encountered. Overall, this study offers valuable insights into the user experience of the Bibit application and highlights areas for improvement, which can be leveraged to enhance the quality of the app’s services in the future.
Comparison of AHP and SAW Methods for Predicting Career Interests of SMAN 1 Karanganyar Demak Students Prabowo, Ardian Adi; Supriyanto, Aji
Sistemasi: Jurnal Sistem Informasi Vol 14, No 2 (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.v14i2.5025

Abstract

This study compares the efficacy of the Analytic Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods in predicting career interests of students at SMAN 1 Karanganyar Demak. The research assesses seven key factors: familial influence, educational engagement, individual capabilities, academic performance, institutional resources, resilience of a career, and academic interests. Results show that AHP prioritizes familial influence (28.94%), individual capabilities (17.10%), and educational engagement (16.23%), while SAW highlights career (15.75%), educational engagement (15.61%), and individual capabilities (14.92%). Both methods achieved an accuracy of 83.02%. Career recommendations were categorized into guidance-intensive cases (AHP: 42.68%; SAW: 46.00%), employment-oriented individuals (AHP: 33.96%; SAW: 32.97%), higher education aspirants (AHP: 12.94%; SAW: 10.06%), and entrepreneurial prospects (AHP: 10.42%; SAW: 10.96%).

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