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TIN: TERAPAN INFORMATIKA NUSANTARA
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 27227987     DOI : -
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Jurnal TIN: TERAPAN INFORMATIKA NUSANTARA memuat tentang Kajian Bunga Rampai dari berbagai ide dan hasil penelitian para peneliti, mahasiswa, dan dosen yang berkompeten di bidangnya dari berbagai disiplin ilmu seperti: Komputer, Informatika, Industri, Elektro, Telekomunikasi, Kesehatan, Agama, Pertanian, Pembelajaran, Pendidikan, Teknologi Pendidikan, Ekonomi dan Bisnis, Manajemen, Akuntansi, dan Hukum
Arjuna Subject : Umum - Umum
Articles 582 Documents
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Pemahaman dan Pengalaman Pengguna terhadap Penerapan PACS (Picture Archiving and Communication System) pada Layanan Radiologi Samsi, Farah Aulia Rahma; Nugroho, Anshor; Mayani, Anita Nur
TIN: Terapan Informatika Nusantara Vol 6 No 4 (2025): September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i4.8311

Abstract

Picture Archiving and Communication System (PACS) is a computer-based technology designed to manage the acquisition, transmission, storage, distribution, display, and interpretation of medical images across institutions. This system is tightly integrated with imaging processes in the Radiology Department and clinical practices that depend on radiological examinations. At the Radiology Installation of RSUD Panembahan Senopati Bantul, the delivery of radiology results has become more efficient with PACS. For internal hospital patients, results are distributed electronically to radiologists and clinical specialists without printing. However, for referred patients from external hospitals or those being referred out, printed film remains necessary. This study applied a descriptive quantitative design, conducted in the Radiology Installation of RSUD Panembahan Senopati Bantul from May 5th to May 10th, 2025. Respondents consisted of 20 radiographers, and data collection was carried out using a Guttman scale questionnaire. The data were analyzed descriptively, with validity and reliability testing. Findings indicate that most respondents possess a strong understanding and acceptance of PACS, demonstrated by the predominance of “Yes” answers, some reaching 100%. This highlights the system’s optimal utilization and its positive contribution to service speed, patient data security, and workflow efficiency. The majority of respondents confirmed that PACS significantly improves radiology services, though some indicators showed varied responses, suggesting areas for further development.
Perbandingan Algoritma Naïve Bayes, Support Vector Machine, dan Random Forest Untuk Analisis Sentimen Komentar Politik Youtube Santoso, Bayu Aji; Nugroho, Bangkit Indarmawan; Asyfiya, Dzurrotu Umi
TIN: Terapan Informatika Nusantara Vol 6 No 4 (2025): September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i4.8326

Abstract

Sentiment analysis is an important field in natural language processing that is widely used to understand public opinion on social media. This study compares the performance of three machine learning algorithms, namely Naïve Bayes, Support Vector Machine (SVM), and Random Forest, in analyzing YouTube comment sentiment. The dataset consists of 15,257 comments obtained from the Indonesia Lawyers Club (ILC) and Rakyat Bersuara channels. The research process includes preprocessing stages (cleaning, case folding, tokenizing, normalization with a slang dictionary, stopword removal, and stemming), data labeling with a Lexicon-based approach using InSet Lexicon, data division with a ratio of 80% training data and 20% test data, and evaluation using accuracy, precision, recall, and F1-score metrics, complemented by K-fold cross validation tests. The results of the sentiment distribution show a dominance of negative sentiment at 43.2%, followed by neutral at 34.9%, and positive at 21.9%. Model evaluation showed that SVM excelled with 83.52% accuracy, 83.55% precision, 83.52% recall, and 83.52% F1-score, followed by Random Forest with 77.20% accuracy, while Naïve Bayes achieved the lowest result at 64.71%. The K-Fold test further strengthened these results, with the best accuracy of 84.14% for SVM. Thus, SVM can be concluded as the most effective algorithm for analyzing political comment sentiment on YouTube.
TikTok dan Kesehatan Mental: Studi Pengaruh Media Sosial pada Remaja Carolan, Farrin; Lawwin, Jay; Jovin, Jovin; Ronald, Ronald; Novisari, Winny
TIN: Terapan Informatika Nusantara Vol 6 No 4 (2025): September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i4.8157

Abstract

This study aims to analyze how the use of TikTok affects the mental health of adolescents in Batam. The method used in this study is a quantitative method using a survey, involving 405 participants aged between 10 and 24 years who actively use TikTok. Based on data from 405 respondents, 86.9% (352 respondents) actively use TikTok, covering all levels of adolescent education. The data collection tool was a questionnaire with a Likert scale designed to measure independent variables (TikTok use) and dependent variables (mental health, including depression, anxiety, stress, and bipolar disorder). Data analysis was performed using the Structural Equation Modeling (SEM) method with AMOS software. The results of this study indicate that TikTok usage significantly contributes to an increase in symptoms of depression, anxiety, stress, and bipolar disorder among adolescents. The reliability test results show that the Cronbach's Alpha values for the variables TikTok Usage (TU) are 0.768, Depression (D) are 0.801, Stress (S) are 0.872, Anxiety (A) are 0.868, and Bipolar Disorder (BD) are 0.874. Based on standard interpretation, a Cronbach's Alpha value greater than 0.70 is considered to have adequate reliability. Therefore, all variables indicate that the items in the questionnaire have a good level of internal consistency. These findings highlight the importance of improving digital literacy and time management in social media use to maintain adolescent mental health. This study provides valuable insights into understanding the complex relationship between social media and mental health, as well as providing a foundation for more effective interventions in the future.
Implementasi Model Extreme Programming dalam Pengembangan Sistem Simulasi Tes TOEFL Rahman, Reyvi; Khaira, Ulfa; Abidin, Zainil
TIN: Terapan Informatika Nusantara Vol 6 No 4 (2025): September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i4.8272

Abstract

English proficiency is a key requirement in both academic and professional settings, with TOEFL serving as a standardized measure of competency. However, many candidates are unprepared for this exam due to a lack of understanding and practice that simulates actual test conditions. Yanto Tanjung English Academy, a course provider offering online TOEFL instruction, currently lacks a comprehensive test simulation facility. Therefore, this research aims to develop a web-based TOEFL test simulation system to provide a realistic exam experience, enabling participants to be better prepared and more confident. The system was developed using the Extreme Programming (XP) method, which consists of planning, design, coding, and testing phases. Testing was conducted using a Test-Driven Development (TDD) approach to ensure the system's functionality and alignment with user requirements. The results show that all main features are accessible, as evidenced by an efficient average execution time of 2.126 seconds across all tested features. This performance data confirms that the TDD approach successfully yielded a system that is not only functional but also responsive for its users. Furthermore, the system received a high acceptance rate from both stakeholders and course participants. This system is expected to enhance the effectiveness of independent and flexible TOEFL learning and to serve as a beneficial digital solution for course participants and the general public wishing to practice TOEFL online
Kripto Aset dalam Keuangan Syariah: Tinjauan Sistematis tentang Tantangan dan Peluang Kesesuaian Syariah Ikmaliyah, Mirzah; Roza, Elvira Mey; Amanda, Asty; Rahayu, Sri
TIN: Terapan Informatika Nusantara Vol 6 No 5 (2025): October 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i5.7911

Abstract

This article presents a systematic literature review (SLR) on the challenges and opportunities of Shariah compliance in the use of crypto assets within the Islamic financial system. Drawing on 52 peer-reviewed articles published between 2020 and 2025, this study employed bibliometric analysis using VOSviewer to map key themes, terminologies, and scholarly trends. The review focuses on three core dimensions: (1) fiqh muamalah perspectives, (2) regulatory and legal frameworks, and (3) emerging business models in Shariah-compliant crypto finance. The results reveal that dominant keywords such as “cryptocurrency,” “Islamic finance,” and “Shariah compliance” indicate growing scholarly attention to ethical and jurisprudential dimensions beyond technological innovation. Five major thematic clusters were identified, including Islamic ethical foundations, digital regulation, halal financial instruments, global fatwa comparisons, and implementation barriers. The review also highlights a fragmented understanding of crypto legitimacy across fatwa institutions and a lack of empirical studies addressing Shariah-compliant adoption frameworks. Therefore, multi-stakeholder collaboration between regulators, scholars, and fintech practitioners is crucial to develop a comprehensive Shariah-based evaluative framework. These findings aim to guide future policies and contribute to building a trustworthy, inclusive halal crypto ecosystem aligned with the objectives of Islamic law (maqashid al-shariah).
Analisis Komparatif Kinerja Next.js, Nuxt.js, dan Remix.js dalam Implementasi Server Side Rendering Website Berita Hermanto, Richie Reuben; Engel, Mychael Maoeretz
TIN: Terapan Informatika Nusantara Vol 6 No 5 (2025): October 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i5.8315

Abstract

The rapid development of online news media requires websites to have high performance in order to deliver information quickly, stably, and optimally on search engines. The objective of this study is to analyze and compare the performance of the Next.js, Nuxt.js, and Remix.js frameworks in implementing Server Side Rendering (SSR) on news websites. The method used is a comparative experiment by building three identical news website prototypes using the three frameworks, then testing them with Google Lighthouse to measure rendering peformance and Apache JMeter to assess resilience to user load. The load testing was conducted in three scenarios using 250, 500, and 1000 virtual users/threads with a 5 second ramp-up period, a 300 second test duration, and an infinite loop count so that each virtual user continuously repeated requests until the test ended. Google Lighthouse test results show that Remix.js excels in the First Contentful Paint metric at 2.14 seconds, Largest Contentful Paint at 2.9 seconds, and Speed Index at 2.14 seconds, allowing news headlines and images to be displayed faster and improving user perception of speed and convenience. In JMeter testing, Nuxt.js showed the best performance with the lowest response time, highest throughput, and more stable error rate compared to other frameworks, demonstrating better resilience in the face of large traffic spikes. The conclusion of this study is that Remix.js is more optimal for improving user experience through content access speed, while Nuxt.js is superior in terms of scalability and reliability when traffic spikes occur. The implication of these findings is that the selection of an SSR framework for news websites should be tailored to the main priority, whether it is emphasizing access speed or system resilience under high load conditions.
The Impact of Green Bond and Green Budget Tagging on Sustainable Development Moderated by Regulatory Quality: Evidence from Indonesia Siska, Elmira; Irawan, Rini Larasati; Lestari, Tri; Rahayu, Sri; Alfita, Alya Kanaya
TIN: Terapan Informatika Nusantara Vol 6 No 5 (2025): October 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i5.8383

Abstract

The challenges of climate change, environmental decline, and growing pressure on natural resources are pushing both public and private financing systems to shift toward more sustainable and eco-friendly activities. The objective of this study is to examine whether Green Bond issuance, Green Budget Tagging, and Regulatory Quality significantly influence Sustainable Development and whether Regulatory Quality strengthens the relationship between Green Bond, Green Budget Tagging, and Sustainable Development. The research was conducted in Indonesia by using time series data covering period 2018-2023. Data were analyzed using multiple linear regression with moderation testing through SPSS 25. To ensure that the data used in the regression model meet the BLUE (Best Linear Unbiased Estimator) criteria, a series of classical assumption tests were conducted, including the normality test, multicollinearity test, heteroscedasticity test, and autocorrelation test. The results show that Green Bond has a significant positive effect on Sustainable Development (sig. 0.000<0.05), while Green Budget Tagging has not shown strong positive impact on Sustainable Development (sig.0.344>0.05). Regulatory Quality has a significant positive effect on Sustainable Development (sig. 0.000<0.05). Simultaneous testing reveals that both variables (Green Bond and Green Budget Tagging) together contribute significantly to Sustainable Development (sig. 0.000<0.05). Regulatory Quality significantly moderates the relationship between Green bond and Sustainable Development (sig. 0.000<0.05). It also significantly moderates the relationship Green Budget Tagging and Sustainable Development (sig. 0.023<0.05). Moreover, the inclusion of Regulatory Quality as a moderating variable increases the adjusted R² value from 0.847 to 0.865, indicating that regulatory quality strengthens the explanatory power of the model. These findings emphasize that the combination of green financing instruments and strong regulatory frameworks plays a crucial role in accelerating Indonesia’s sustainable development agenda.
Pengaruh Struktur Modal, Company Size, dan Kinerja Keuangan Terhadap Agresivitas Pajak Afghoni, Lazuardi Hasan; Ismanto, Juli
TIN: Terapan Informatika Nusantara Vol 6 No 5 (2025): October 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i5.8413

Abstract

This study was conducted to examine and provide empirical evidence regarding the influence of capital structure, company size and financial performance on tax aggressiveness in non-cyclical consumer sector companies recorded on the IDX for the 2020-2024 period. This study takes a quantitative approach by utilizing secondary data as a source of information. The sample was 37 companies selected through purposive sampling during five years of observation. Data analysis uses panel data regression with the help of the EViews version 13 program. The variables studied include capital structure (X1), company size (X2), financial performance (X3), and tax aggressiveness (Y). The study results indicate that the best model is the Fixed Effect Model (FEM). From the results of the analysis, simultaneously capital structure, company size and financial performance are proven to influence tax aggressiveness as indicated by the F-statistic probability value of 0.000000 < 0.05. Partially, capital structure is proven to influence tax aggressiveness as indicated by a probability value of 0.0280 < 0.05, and financial performance is also proven to influence tax aggressiveness as indicated by a probability value of 0.0015 < 0.05, while company size has no influence on tax aggressiveness as indicated by a probability value of 0.3855 > 0.05. The coefficient of determination value is 56.10%, which means the remaining 43.90% is influenced by other variables outside this study.
Sistem Rekomendasi Pemilihan Saham Blue-Chip di Bursa Efek Indonesia Menggunakan Fuzzy Mamdani Dandi, Muhammad Khairil; Kurniawan, Rakhmat
TIN: Terapan Informatika Nusantara Vol 6 No 5 (2025): October 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i5.8465

Abstract

The Indonesian capital market plays an important role in supporting national economic growth, particularly through stock investments. Blue-chip stocks are considered stable and have the potential to provide long-term returns, yet selecting the right ones remains a challenge for investors. This study aims to develop a recommendation system for selecting blue-chip stocks on the Indonesia Stock Exchange (BEI) using the Fuzzy Mamdani method. The research data were collected from a set of actively traded blue-chip stocks within a specific period and analyzed using four main variables: stock price, trading volume, market capitalization, and financial ratios. The recommendation process involves fuzzification, the formulation of 15 rule bases established through expert consultation with market analysts, Mamdani inference, and defuzzification to produce recommendation scores. The implementation results show that the system achieved an accuracy level of 84.65%, indicating stable consistency with actual market conditions. These findings confirm that the Fuzzy Mamdani method is effective in generating objective and systematic recommendations for blue-chip stock selection. The developed system successfully meets the research objective by assisting investors in identifying suitable stocks based on data-driven analysis.
Aplikasi Pendeteksi dan Pengklasifikasi Sampah Berbasis Android Menggunakan Algoritma SSD MobileNetV2 Rumayar, Eroldy; Kainde, Quido Conferti; Santa, Kristofel
TIN: Terapan Informatika Nusantara Vol 6 No 5 (2025): October 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i5.8453

Abstract

This study aims to develop a waste detection and classification application using the SSD MobileNetV2 algorithm based on an Android application. The problem of waste, especially waste generation, is a crucial issue that needs to be addressed, one of the factors being the lack of public awareness regarding waste sorting. Various efforts to increase public awareness of waste sorting that have been carried out, such as socialization, counseling, the use of brochure media, and poster media, require a lot of time, effort, and resources. This research was conducted to propose a more efficient and practical approach to education as well as handling waste sorting, namely by using an Android application integrated with the SSD MobileNetV2 object detection algorithm. The method used in this study consists of the process of collecting datasets of waste objects with types of organic, inorganic, and hazardous and toxic materials (B3), then training the SSD MobileNetV2 algorithm using the MediaPipe framework with the mediapipe-model-maker library, and developing an Android application integrated with the trained SSD MobileNetV2 algorithm using the MediaPipe framework with the Mediapipe Tasks Vision library. This study produced a synthetic dataset in Pascal VOC format with a total of 4302 images of waste objects divided into 80% for the training set and 20% for the validation set. The created dataset was then trained on the SSD MobileNetV2 algorithm with performance results of AP IoU=0.50:0.95 with a value of 0.847, AP IoU=0.50 with a value of 0.986, and AP IoU=0.75 with a value of 0.969. The trained SSD MobileNetV2 algorithm was then integrated into the developed Android application. The testing results on mid to high-end Android devices obtained an average inference time ranging from 165–230 ms. In addition, this application successfully detected waste objects according to those trained in the model. This application features a real-time scanning function with a classification mechanism for detected waste object types using bounding box colors, where organic waste is marked in green, inorganic waste in yellow, and B3 waste in red. With this mechanism, it provides an interactive experience for users in sorting their waste, thereby expected to increase awareness of waste sorting.

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