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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 40 Documents
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Search results for , issue "Vol 6 No 7 (2025): December 2025" : 40 Documents clear
Implementation of the Preference Selection Index Method in a Decision Support System for Determining Customer Loan Eligibility Ilham, Safarul
TIN: Terapan Informatika Nusantara Vol 6 No 7 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i7.8357

Abstract

This study aims to apply the Preferential Selection Index (PSI) method in evaluating the eligibility of loan applicants for the PNM Mekaar program. The research investigates the effectiveness of PSI in selecting the most eligible borrowers based on multiple criteria, such as Age, Owns a Business, Loan Capital, Income, Business Permit, Business Permit Level and Customer History. The analysis is conducted using a decision support system (DSS), where each alternative is evaluated against these criteria and weighted accordingly. The study finds that the alternative with the highest value, C8 (0.222403657), is followed closely by alternative A7 (0.207720657). The results of this study demonstrate that PSI offers a more structured, objective, and efficient approach to loan eligibility assessment compared to traditional methods. The integration of PSI within the DSS allows for faster decision-making, improved consistency, and a reduction in the risk of loan defaults. These findings contribute to enhancing the decision-making process in microfinance institutions, particularly in improving financial inclusion and supporting the growth of micro, small, and medium enterprises (MSMEs). The research concludes that PSI is a valuable tool for financial institutions seeking to adopt data-driven, transparent, and reliable loan approval procedures.
A Mobile Based Accounting Application Design for MSMEs using the RAD Method Mashud, Mashud; Aisa, Sitti; Awaliah, Neneng; Rahman, Fery Fadul
TIN: Terapan Informatika Nusantara Vol 6 No 7 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i7.8559

Abstract

Digital transformation in the Micro, Small, and Medium Enterprises (MSMEs) sector has become a strategic necessity to improve the efficiency and transparency of financial management. This study aims to design and test a mobile-based accounting system that can support the digital recording, reporting, and financial management processes of MSMEs. The method used is Research and Development (R&D) with the Waterfall model, which includes the stages of needs analysis, system design using the Unified Modeling Language (UML) and functional testing using the Black Box Testing method. The results of the study indicate that all main features, including user registration, transaction recording, automatic reports, and multi-user management, function validly and according to functional specifications. Thus, the system can meet the basic accounting needs of MSMEs with a simple interface and real-time access via mobile devices. Practically, the results of this study produce a prototype of a mobile accounting application that can be implemented directly by MSMEs. Theoretically, this study enriches the literature on digital transformation in MSME accounting systems, while also serving as a basis for further development that includes data security features and artificial intelligence-based analytics.
Sistem Prediksi Kualitas Udara Menggunakan Algoritma Long Short-Term Memory (LSTM) Wicaksono, Muhammad Zaki; Astrianty, Ledy Elsera
TIN: Terapan Informatika Nusantara Vol 6 No 7 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i7.8619

Abstract

Conventional and static air quality monitoring in Yogyakarta City which only presents historical (past) data reports hinders proactive mitigation efforts against air pollution. This research aims to develop an air quality prediction system using the Long Short-Term Memory (LSTM) algorithm, a deep learning method superior for time-series data analysis. The system utilizes historical data from the Yogyakarta City Environmental Agency (DLH) from 2022 to 2024, covering pollutant parameters such as PM10, PM2.5, SO₂, CO, O₃, and NO₂. The primary prediction focus is the AQI (Air Quality Index) value, calculated based on the concentration of these pollutant parameters. The research method includes data preprocessing, such as handling missing data with interpolation, designing a two-layer LSTM model architecture, model training, and performance evaluation using Mean Absolute Error (MAE) and Mean Absolute Deviation (MAD) metrics. The results show that the developed LSTM model successfully provides predictions with good performance, where the combined average MAE value (4.85) is significantly lower than the average MAD of the actual data (10.19), indicating that the model's prediction error is smaller than the natural variability of the data. The output of this research is a prototype application with a graphical user interface (GUI) capable of displaying air quality predictions for the next day, identifying critical pollutant components, and presenting air quality condition classifications informatively.
Implementasi Sistem Rujukan Pasien Digital Terpadu Menggunakan Metode Deskriptif Kualitatif Untuk Optimalisasi Layanan Kesehatan Shidiq, Farihan; Romli, Moh. Ali
TIN: Terapan Informatika Nusantara Vol 6 No 7 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i7.8626

Abstract

The patient referral process at Bidan Mawar Clinic is still carried out manually using paper forms and telephone communication, which often causes delays and recording errors. This condition hampers coordination between midwives and community health centers (Puskesmas) and potentially reduces the quality of healthcare services. To address these issues, this study develops a web- and mobile-based patient referral system aimed at improving efficiency, accuracy, and the speed of the referral process. The research approach employs a descriptive qualitative method, including stages of needs analysis, system design using Unified Modeling Language (UML), and system implementation using Flutter for the mobile application, PHP and Express.js for the backend, and MySQL as the database. The implementation results show that the system can perform login, registration, referral data submission, and real-time status monitoring functions with a 100% success rate under normal testing scenarios. The developed system accelerates the referral process by up to twice as fast compared to the manual method, reduces administrative errors, and enhances coordination between midwives and Puskesmas. Therefore, this system contributes to improving the efficiency and quality of healthcare services at the primary healthcare level.
Aplikasi Inventory dengan Visualisasi Penjualan Berbasis Outflow Stok pada Toko Ritel Dzulfikar, Muhamad Althaf Atsaqif; Asriningtias, Yuli
TIN: Terapan Informatika Nusantara Vol 6 No 7 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i7.8659

Abstract

Inventory management in retail stores often faces constraints regarding recording accuracy, restocking delays, and difficulties in preparing reports when processes are still carried out manually. This research designs and implements a mobile-based inventory application in a Retail Store case study to handle login–register authentication, mapping of item storage locations, management of categories and item data, recording of in-out transactions (not POS/cashier), sales visualization based on item outflow in bar diagrams, and periodic reports of incoming and outgoing goods. The development methodology applied is Black-box Functional Testing on core scenarios. Black-box functional testing on 9 core scenarios achieved a 100% success rate, covering login–registration, master data management, incoming–outgoing transactions, stock-outflow visualization, and report export. The system architecture adopts Flutter on the client side, Node.js–Express on the service side, and MySQL on the database side. The development methodology is iterative, covering requirements elicitation, data model design with ERD and process flow with DFD, module implementation, and black-box functional testing on core scenarios. The implementation results demonstrate that all modules operate according to specifications: transactions automatically update stock, visualization highlights best-selling products through stock outflow indicators, and period reports support restocking decisions. These findings affirm that the application successfully enhances operational efficiency and employee productivity due to faster and easier recording, mitigates the risk of item data loss, and provides accurate analysis regarding stock outflow that aids in predicting and optimizing restocking policies.
Deteksi Serangan DDoS (Distributed Denial of Service) Menggunakan Wavelet Decomposition dan Optimasi Hyperparameter Berbasis Optuna Ghibran, Andi Khalil; Mustikasari, Mustikasari; Darmatasia, Darmatasia; Antamil, Antamil
TIN: Terapan Informatika Nusantara Vol 6 No 7 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i7.8706

Abstract

This study aims to design and develop a Distributed Denial of Service (DDoS) attack detection system based on Wavelet Decomposition capable of identifying network traffic anomalies in real-time. The main problem addressed is the high false positive rate in conventional detection methods, which often fail to distinguish between legitimate traffic bursts and actual attacks. Two primary data sources were used: the CICIDS2017 dataset and self-generated data representing controlled DDoS attack patterns. The proposed method applies Discrete Wavelet Transform (DWT) to decompose network traffic signals into amplitude and energy components. Detection is then performed using the Median Absolute Deviation (MAD) approach, optimized with three parameter search methods: Grid Search, Random Search, and Optuna. Experimental results indicate that the energy-based method with Optuna optimization achieves the best performance, with an accuracy of 98.6% on the CICIDS2017 dataset and 99.4% on the self-generated data, and error rates of 1.4% and 0.6%, respectively. This research contributes to enhancing the accuracy of DDoS detection systems with low computational overhead, making it suitable for large-scale network environments.
Analisis Performa Metode KNN, Yolov8, Dan Yolov11 Pada Klasifikasi Konjungtiva Mata Untuk Deteksi Anemia Sumihar, Yoel Pieter; Maedjaja, Febe; Sas, Valentino Henry
TIN: Terapan Informatika Nusantara Vol 6 No 7 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i7.8707

Abstract

Rapid and non-invasive anemia detection is crucial, especially in regions with limited laboratory facilities. The conjunctiva of the eye serves as a promising visual indicator for anemia through the analysis of color and texture. This study aims to analyze and compare the performance of three image classification methods K-Nearest Neighbors (KNN), YOLOv8, and YOLOv11 in detecting anemia using conjunctival images. The CP-AnemiC dataset was employed, consisting of 710 original images, later expanded to 3,550 images through augmentation. KNN utilized color features extracted from the CIE LAB color space, while YOLOv8 and YOLOv11 leveraged automatic feature extraction using convolutional neural networks. Evaluation metrics included accuracy, precision, recall, and F1-score. The results indicate that YOLOv8 achieved the best performance with 93.4% accuracy and a 94.5% F1-score, followed by YOLOv11 with 93.0% accuracy and a 94.2% F1-score. In contrast, KNN obtained an accuracy of only 85.7%. YOLOv8 demonstrated fast and accurate detection, while YOLOv11 exhibited more stable training behavior. These findings highlight that deep learning models particularly YOLOv8 and YOLOv11 are highly promising for implementing efficient, accurate, and practical conjunctival image–based anemia detection systems. This research contributes by presenting an explicit comparative analysis between the classical method (KNN) and the latest deep learning models (YOLOv8 and YOLOv11) in the specific context of conjunctival image classification.
Pengaruh Coretax dan Sanksi Perpajakan terhadap Kepatuhan Pajak pada Credit Union dimoderasi Sistem Pengendalian Manajemen Roziana, Roziana; Risal, Risal; Afif, Ali
TIN: Terapan Informatika Nusantara Vol 6 No 7 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i7.8721

Abstract

The main source of state revenue is taxes, but corporate taxpayers' compliance with Credit Unions (CU) of Puskopcuina members is still low. This study analyzes the influence of Coretax implementation and tax sanctions on compliance, with the Management Control System (SPM) as moderation. The study used a quantitative approach involving 47 respondents, where data was collected through questionnaires and analyzed using SPSS 26 through data quality tests, classical assumption tests, descriptive analysis, and hypothesis tests. The results showed that the implementation of Coretax had no significant effect on compliance (coefficient of 0.034; significance of 0.839), while tax sanctions had a significant positive effect (coefficient of 0.284; significance of 0.047). SPM weakened the influence of Coretax (coefficient of -0.149; significance 0.020) and strengthened the influence of tax sanctions (coefficient of 0.149; significance 0.009). Thus, tax sanctions play an important role in encouraging increased compliance of corporate taxpayers, while the effectiveness of Coretax is highly dependent on MCS support.
Penerapan Laundry Management System Web-Mobile Menggunakan Metode Waterfall dengan Evaluasi TAM dan Blackbox Testing Pangesty, Shandika Sayyid Ammar; Wibowo, Adityo Permana
TIN: Terapan Informatika Nusantara Vol 6 No 7 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i7.8731

Abstract

The main problems faced by Mulia Laundry stem from business processes that are still carried out manually, including service recording, inventory management, and customer transactions. This situation reduces operational efficiency, increases the possibility of recording errors, and hinders service speed. Therefore, the purpose of this study is to develop and implement a web- mobile based Laundry Management System that can automate the entire laundry business process to be more efficient, accurate, and integrated. The system is designed using a client-server architecture through REST API, with a structured software engineering approach through Unified Modeling Language (UML) modeling and using the Waterfall model Software Development Life Cycle (SDLC) development method. The main features of this system include customer management, services, inventory, transactions, and real-time order status tracking. The system was evaluated using Blackbox Testing, which showed that all features operated according to specifications without any errors in the main application processes. In addition, user acceptance testing using the Technology Acceptance Model (TAM) obtained an average perceived usefulness (PU) score of 4.67 and a perceived ease of use (PEOU) score of 4.47, both of which are in the excellent category. The results of this study indicate that the system is well accepted by users and can prove its effectiveness in improving operational efficiency and supporting the digitization of business processes in laundry MSMEs.
Otomatisasi Pencatatan dan Kepatuhan Regulasi Terhadap Keberlanjutan UMKM Pengendalian Internal Sebagai Moderasi Imanuel, Rizky; Risal, Risal; Afif, Ali
TIN: Terapan Informatika Nusantara Vol 6 No 7 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i7.8734

Abstract

Given their large number and contribution to the country's GDP, micro, small, and medium enterprises (MSMEs) play a significant role in the Indonesian economy. However, corporate sustainability presents challenges for business actors, particularly related to the implementation of internal controls, automation of recording, and regulatory compliance. This study uses a quantitative approach by utilizing primary data as a data source. This study uses a purposive sampling method to select MSME respondents. The data analysis process uses SPSS version 26. Data analysis is carried out through descriptive statistics, data quality tests for validity and reliability, classical assumption tests, multiple linear regression, and moderated regression analysis (MRA) with the help of SPSS version 26. Data were collected through questionnaires, and 89 returned questionnaires were declared eligible and represent all research respondents. From the analysis results, simultaneously recording automation, regulatory compliance is proven to have an effect on the sustainability of MSMEs, internal control is not proven to moderate the relationship between the two variables, partially recording automation is proven to affect the sustainability of MSMEs shown by a value of 0.016 <0.05, and regulatory compliance is proven to affect the sustainability of MSMEs shown by a value of 0.02 <0.05, while internal control does not moderate the relationship between recording automation with a value of 0.721>0.05, regulatory compliance 0.731>0.05. The implications of these findings indicate the importance of awareness of business actors in implementing effective internal control in running their businesses.

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