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TIN: TERAPAN INFORMATIKA NUSANTARA
Published by Forum Kerjasama Pendidikan TInggi
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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 12 Documents
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Search results for , issue "Vol 6 No 5 (2025): October 2025" : 12 Documents clear
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.
Aplikasi Pemantauan Akademik dan Non-Akademik Siswa Sekolah Dasar Berbasis Web dan Mobile Hidayat, Rizki; Mardhiyyah, Rodhiyah
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.v6i5.8455

Abstract

Student learning assessment is an essential component of education as it measures competency achievement and supports the continuous development of learning strategies. At SDN 2 Bungko Lor, Cirebon, the management of academic and non-academic data is still carried out manually using printed report cards and Excel spreadsheets. This condition limits parents’ ability to monitor their children's learning progress, as results are only accessible at the end of each semester. This study aims to design and develop a Web- and Android-based Academic and Non-Academic Monitoring Application using the Waterfall method to simplify data management, improve information accessibility, and strengthen communication among schools, teachers, and parents. The system was developed using Vue.js for the web application, Flutter for the Android application, PHP as the back-end, and MySQL as the integrated database. The system design applied UML (Use Case, Activity, and Class Diagrams) to model workflows and data structures. The main features include multi-user login, management of grades and attendance as academic data, recording of student behavior as non-academic data, class schedules, and a two-way chat feature to support coordination between schools and parents. Testing using the Black Box method confirmed that all core functionalities operated properly. The implementation of this system provides a more structured presentation of information and enhances collaboration between schools and parents in monitoring students’ academic and non-academic development.
Pengelompokkan Tingkat Stres Akademik Pada Mahasiswa Menggunakan Algoritma Fuzzy C-Means Alfaiza, Raihan Zia; Budianita, Elvia; Gusti, Siska Kurnia; Afrianty, Iis
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.v6i5.8460

Abstract

Academic stress is a common problem experienced by students due to the burden of assignments, exams, and social pressures. If not managed properly, it can impact achievement and psychological well-being. This study aims to classify the academic stress levels of students at the Faculty of Science and Technology, Sultan Syarif Kasim State Islamic University, Riau, using the Fuzzy C-Means (FCM) algorithm, which allows flexibility in the degree of data membership in more than one cluster. Data were obtained from a modified Perception of Academic Stress Scale (PASS) questionnaire, with 587 respondents from the 2021–2024 intake. The research stages included data selection, cleaning, and transformation, application of the FCM algorithm, and evaluation using three validation metrics: the Partition Coefficient Index (PCI), the Fuzzy Silhouette Index (FSI) and the Silhouette Coefficient. The test results showed the optimal number of clusters at C = 2, with the highest PCI value of 0.5663, FSI and ilhouette Coefficient score of 0.3056, resulting in two groups of students: 313 with high stress levels and 274 with low stress levels. The decrease in PCI, FSI and Silhouette scores across a larger number of clusters indicates that dividing two clusters provides the clearest grouping structure. These findings demonstrate that the FCM algorithm is effective in mapping students' academic stress patterns and can be used as a basis for designing more targeted academic mentoring strategies, counseling services, and psychological intervention programs services.
Hyperparameter Optimization of Naive Bayes for Supervisor Recommendation in Computer Science Sinaga, Muhammad Nabil; Kurniawan R, 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.v6i5.8478

Abstract

The increasing number of students in the Department of Computer Science at UIN Sumatera Utara has made the process of selecting thesis supervisors more complex and time-consuming. This study aims to develop a system that automatically recommends the most suitable supervisor based on the similarity between thesis titles and lecturers’ areas of expertise. The proposed model applies text preprocessing techniques such as case folding, tokenization, stopword removal, and keyword extraction to transform thesis titles into meaningful features. These features are then classified using the Naive Bayes algorithm to predict the probability of each lecturer being the most relevant supervisor. The dataset consists of 794 thesis titles and 25 lecturers collected from 2019–2024. The model was evaluated using an 80:20 data split, achieving an accuracy of 87.3% with stable precision and recall scores, demonstrating reliable performance in supervisor recommendations. This enhanced Naive Bayes model can assist academic departments in ensuring a fairer and more efficient supervisor assignment process.
Pengembangan Aplikasi Mobile Berbasis Location-Based Service dalam Mendukung Efisiensi Distribusi Pertanian Padi Yakti, Ikhwan Kuncoro; Mardhiyyah, Rodhiyah
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.v6i5.8545

Abstract

Rice harvest distribution is a critical aspect of maintaining price stability and national food security. However, the traditional distribution system still faces numerous challenges, such as long supply chains, lengthy delivery times, and limited information regarding prices and rice mill locations. These conditions lead to distribution inefficiencies, price fluctuations detrimental to farmers, and a decrease in their welfare. This research focuses on developing a Location-Based Service (LBS) mobile application integrated with a monitoring website to support the efficiency of rice distribution. The developed system is designed to connect farmers, rice mills, and distributors on a single digital platform, enabling a more monitored and integrated distribution process. The mobile application provides features for harvest recording, searching for nearby rice mill locations, real-time market price information, product sales and ordering, transaction logging, agricultural news, and digital payment integration. The monitoring website is intended for relevant agencies to display production and distribution data, progress graphs, and distribution maps of farmers and rice mills. The system was implemented using Flutter for the mobile application, Vue.js for the website, and Firebase Realtime Database as the integrated database, using data from the Cilamaya Wetan Agricultural Technical Service Unit (UPTD). Black Box Testing results indicate that all main system functions such as authentication, product management, ordering, location services, and payment integration are functionally sound and operate according to user requirements. Nevertheless, this testing was limited to technical functionality and did not include usability evaluation or user acceptance in the field. While the traditional distribution process involves 3-4 intermediaries (e.g., farmers, brokers, collectors, mills, large distributors, retailers, end distributors), the developed system offers a design that can shorten this process to only 1-2 intermediaries via a direct channel from farmer to mill, and then to the distributor. Potential analysis indicates that the system could enhance distribution efficiency by reducing intermediaries, improving price transparency, and facilitating easier monitoring by relevant agencies. The mobile application can display rice mill location information on a digital map, accessible to farmers in real-time. This research, therefore, yields a system developed to digitally support rice distribution efficiency. It can serve as a foundation for future research to test the system's implementation in the field and assess its real-world impact on farmer welfare and distribution effectiveness.

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