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Kab. indragiri hilir,
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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
Examining the Readiness of the Organization's Security Success in Improving Security Performance Zuhroh, Nur Fatimatuz; Baihaqy, Ahmad
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.v14i2.4857

Abstract

Information security has become an important issue in the digital era due to increased cyber threats and data leaks. This study analyzes the influence of Organizational Culture, Risk Propensity, and Security Readiness on Organizational Security Performance, with Top Management Support as the moderation variable. This study uses a quantitative method with a survey approach and is analyzed using SPSS software for regression, mediation, and moderation tests. The results show that Organizational Culture, Risk Propensity, and Security Readiness have a significant influence on Organizational Security Performance. Security Readiness is proven to be a mediating variable that strengthens the relationship between Organizational Culture and Risk Propensity to organizational security performance. In addition, Top Management Support acts as a moderator that strengthens the relationship between independent variables and Organizational Security Performance. This research contributes by integrating Security Readiness as a mediator and Top Management Support as a moderator in the information security framework. These findings highlight the importance of a holistic approach that includes organizational culture, risk behavior, security readiness, and top management support to improve information security resilience amid the challenges of the digital age and the result can be a recommendation for the government and private sectors.
Implementation of the Random Forest Algorithm with Optuna Optimization in Lung Cancer Classification Yaqin, Ahmad Ainul; Barata, Mula Agung; Mahmudah, Nur
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.v14i2.4877

Abstract

Lung cancer remains one of the leading causes of death worldwide, with many sufferers unaware of their condition until it is too late for treatment. Therefore, high-accuracy prediction methods are urgently needed for early detection of lung cancer. This research uses the Random Forest algorithm, known for its excellent performance in medical data classification. In this study, modeling was optimized by implementing hyperparameter optimization using Optuna. The results of the generated model show an accuracy rate of 98.6%, which is highly significant in the context of early lung cancer detection. Additionally, this algorithm demonstrated 100% recall for the positive class and 97% for the negative class, indicating that the model is highly effective in identifying patients who truly have lung cancer. Another advantage of this model is seen in the AUC (Area Under the Curve) value reaching 1, indicating 100% accurate predictions. With these results, this research affirms the importance of using the Random Forest algorithm in developing early detection systems for lung cancer. This not only can improve treatment success rates but also significantly reduce mortality rates from lung cancer.
The Impact of User Satisfaction on the Intention to Continuously use the Threads Application: An ECM Approach Asyraf, Fajri Muhammad; Anofrizen, Anofrizen; Syaifullah, Syaifullah; Saputra, Eki
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.v14i2.5027

Abstract

Retaining user loyalty amidst the intensifying competition in social media platforms is a significant challenge for app developers. Threads, Meta’s new microblogging platform, experienced a sharp decline in daily active users following its initial launch, despite rapid early user growth. This study aims to analyze the factors influencing user satisfaction and the intention to continue using Threads through the lens of the Expectation Confirmation Model (ECM). This research employs a quantitative approach, collecting data via an online questionnaire distributed to 120 respondents. The data was analyzed using Structural Equation Modeling-Partial Least Squares (SEM-PLS). The findings indicate that Satisfaction is a key variable with a significant impact on Continuance to Use, whereas Perceived Usefulness does not significantly influence Continuance to Use. Additionally, Enjoyment plays a crucial role in enhancing both Satisfaction and Continuance to Use, emphasizing the importance of emotional factors in user experience. This study suggests that app developers should prioritize user satisfaction by improving service quality and relevant features while enhancing the app’s overall value to sustain user loyalty.
Implementation of the Long Short-Term Memory Algorithm in a Chatbot for Dengue Fever Information and Education Services Budianto, Heru; Yusuf, Fahmi; Irawan, Dede; Sidik, Muhamad Akhirul; Nurhasanah, Aiena; Mauldya, Sabrina; Afifah, Silmi Nur
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.v14i2.5060

Abstract

Dengue fever is one of the most common infectious diseases in Indonesia. However, information regarding its prevention and treatment remains fragmented, with limited accessibility and availability. This study developed a chatbot integrating the Long Short-Term Memory (LSTM) algorithm to answer various questions about dengue fever, including its symptoms, prevention, and treatment. The dataset used consists of questions and answers related to dengue fever, sourced from both primary and secondary data. The data undergoes a series of preprocessing steps before being used for model development, training, and evaluation. The test results indicate that the developed model achieved an accuracy of 100% during validation with a loss function value of 0.0221. These findings demonstrate that the LSTM-based chatbot can provide accurate and relevant responses, making it an effective tool for educating the public in an interactive and efficient manner. This implementation is expected to offer an innovative solution for increasing public awareness of dengue fever prevention and management.
Risk Factor Analysis of Dengue Fever in Makassar City using the Simple Additive Weighting Method Paseleng, Fatricius; Susetyo, Yeremia Alfa
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.v14i2.5079

Abstract

Dengue Fever is caused by the Flavivirus, which is transmitted through the bites of Aedes aegypti mosquitoes and several other Aedes species. Dengue Fever has a significant impact on public health, especially in large cities like Makassar. This study employs the Simple Additive Weighting (SAW) method to evaluate the main risk factors for dengue fever in Makassar City. The research will be conducted through several stages, including literature review, data collection, determining criteria and their weights, normalizing the decision matrix, calculating final scores, and making decisions. The results indicate that the Totaka sub-district has the highest dengue risk with a score of (0.395307), followed by Gusung (0.329353), while Barang Caddi has the lowest dengue risk (0.000618). This study aims to provide a ranking of dengue risks that can assist decision-makers in formulating prevention and control strategies for dengue fever in Makassar City.
Regression Analysis to Predict the Length of Time to Complete a Thesis based on the Title Aminuddin, Al; Hidayat, Rahmat; Sastria, Gita; Astried, Astried
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.v14i2.4994

Abstract

The selection of thesis titles by students is an important thing to do as part of the graduation requirements in completing undergraduate studies. In general, the difficulty or complexity of the thesis can be reflected through the title of the thesis that is appointed. This can indicate that the more difficult a thesis title, the longer it will take to complete the thesis research. This study utilizes the data mining method using machine learning, namely linear regression, in predicting how long it will take to complete a thesis title. The data used is obtained from the words or text in the thesis title as a feature or independent variable and the completion time in days as the dependent variable to predict the time required for students starting from a thesis proposal seminar to a comprehensive seminar or thesis final session. The regression model produces an evaluation value of the coefficient of determination of 0.999, which is close to the maximum value equal to 1.
Evaluation of an Information System using the PIECES Framework: A Case Study of the Inventory Administration Information System (SIAP) of the North Sulawesi Provincial Government Aruperes, Viveca Grivenda; Hartomo, Kristoko Dwi
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.v14i2.5041

Abstract

This study evaluates user satisfaction with the Inventory Administration Information System (SIAP) in North Sulawesi Province using the PIECES Framework and provides recommendations for improvement. The PIECES Framework was chosen due to its proven effectiveness in assessing satisfaction, identifying issues, and guiding system development. This framework consists of six variables: Performance, Information & Data, Economic, Control & Security, Efficiency, and Service. The sample size was determined using Slovin's formula, involving 36 administrators from government offices. Data was collected through questionnaires measured on a Likert scale. The results indicate overall user satisfaction across all six variables. However, some weaknesses were identified, particularly in the Performance and Control & Security variables.
Implementation of the Prototype Method in Developing a Questionnaire Information System for Integrated Survey Services Setiawan, Rhoedy; Romadhon, Zainur; Hakim, Alvin Rainaldy
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.v14i2.5069

Abstract

The advancement of information technology has driven educational institutions to enhance the efficiency and quality of both academic and non-academic services through more integrated survey systems. Universitas Muria Kudus (UMK) still relies on manual survey methods, leading to data duplication, input errors, and delays in analysis. This study aims to design and develop a centralized questionnaire information system to improve survey management efficiency. Using the prototype method, the system was developed in two cycles: the first cycle included core features such as a dashboard, questionnaire management, reporting, and a login system, while the second cycle refined functionalities, including input validation, answer variations, search filters, and report export capabilities. BlackBox Testing was conducted to ensure optimal system functionality. The results indicate that the proposed system enhances efficiency, minimizes data errors, and accelerates survey result analysis, ultimately contributing to improved academic and non-academic services at UMK.
Implementation of the Advanced Encryption Standard (AES) Algorithm and Bit Plane Complexity Segmentation (BPCS) Steganography Technique for Enhancing Text File Security Kautsar, Afthar; Ikhsan, Muhammad
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.v14i2.5097

Abstract

In today's digital era, data security has become a crucial aspect due to the vast amount of information being transmitted and stored electronically. The Advanced Encryption Standard (AES) is one of the most widely used encryption algorithms because of its high level of security. However, data that is merely encrypted still risks detection; therefore, the Bit-Plane Complexity Segmentation (BPCS) steganography technique is employed to hide data within digital images, making it more difficult to identify. This study aims to enhance data security by combining AES encryption and BPCS steganography. The process begins by encrypting text data using AES-128, ensuring that the information cannot be accessed without a valid key. Next, the resulting ciphertext is embedded into a digital image using the BPCS technique, which selects bit-planes with high complexity for insertion without significantly altering the visual appearance of the image. Testing is conducted by measuring the accuracy of data extraction and the impact on image quality. The results indicate that this method effectively maintains data security and confidentiality. The data embedded in the image can be extracted with a success rate of 100%, while the image quality remains intact without noticeable changes. Thus, the combination of AES and BPCS provides a dual layer of protection: encryption ensures that the data cannot be read, while steganography conceals the existence of the data from unauthorized parties. This method can be applied in various data security scenarios, both for personal and organizational purposes.
Application of Naïve Bayes Method for Student Performance Classification Prayoga, Riza Akhsani Setyo; Basatha, Rizky; Akbar, Muhammad Sonhaji; Elfaiz, Ersha Aisyah; Putra, Cendra Devayana
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.v14i2.4852

Abstract

In every school, students exhibit varying levels of performance, influenced by several factors such as parental support and involvement, participation in extracurricular activities, motivation levels, internet access for learning, teacher quality, peer influence, and learning difficulties. This study aims to classify student performance to identify those who may need additional support for improvement. The classification method employed in this research is the Naïve Bayes algorithm. The results indicate that the trained model successfully classified 25 out of 30 tested data points. The evaluation metrics achieved include a precision of 100%, recall of 80%, specificity of 100%, accuracy of 83%, and an F1-score of 89%.

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