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TIN: TERAPAN INFORMATIKA NUSANTARA
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 27227987     DOI : -
Core Subject : Economy, Health, Science, Education, Art, Social, Engineering,
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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 21 Documents
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Search results for , issue "Vol 6 No 2 (2025): July 2025" : 21 Documents clear
Penerapan Faster RCNN + ResNet 50 untuk Mengidentifikasi Spesies dan Stadium Parasit Plasmodium Malaria Prananda, Alifia Revan; Novichasari, Suamanda Ika; Fatkhurrozi, Bagus; Abdillah, Muhammad Nurkholis; Frannita, Eka Legya; Majidah, Zharifa Nur; Wibowo, Fadhila Syahida
TIN: Terapan Informatika Nusantara Vol 6 No 2 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i2.7187

Abstract

Malaria is one of the epidemic health diseases and is well-known as a serious infectious disease. The malaria examination process had occurred by analyzing the digital microscopic images using a microscope. Those examination procedures were conducted manually, which lead to some hurdles such as misinterpretation, misdiagnosis and may produce subjective results. This research aims to develop a method for detecting the Plasmodium parasite and identifying the species and stage of Plasmodium parasite. The proposed method was performed into 488 raw data comprising of 538 parasites. The proposed method was started by conducting a data augmentation process for balancing the number of data, training model, testing model, evaluation. In this study, both the training and testing processes were performed by applying Faster RCNN + ResNet-50. The result of the testing process shows that Faster RCNN + ResNet-50 successfully achieved mAP of 0,603. It also achieved accuracy of 93.91%, sensitivity of 66.20%, specificity of 96.10%, PPV of 60.14% and NPV of 97.30%. This result indicates that the proposed method is powerful for detecting Plasmodium parasites and identifying all species and stadiums.
Analisis Komparatif Metode MOORA dan MAUT untuk Rekomendasi Pengangkatan Tenaga Pendidik Oktavia, Petricia; Frindo, Muhamad Meky
TIN: Terapan Informatika Nusantara Vol 6 No 2 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i2.7337

Abstract

The objective and data-driven recruitment of educators is a strategic step toward improving the quality of education. This study aims to develop a recommendation system for selecting prospective educators by comparing two multi-criteria decision-making methods: MOORA (Multi-Objective Optimization on the Basis of Ratio Analysis) and MAUT (Multi-Attribute Utility Theory). Five key criteria were used in the evaluation: Grade Point Average (GPA), mastery of didactic and methodological knowledge, teaching experience, age, and distance from home to school. Primary data were collected directly from educational institutions and prospective educators, involving six alternatives that were analyzed through normalization, weighting, and final score calculation. The analysis showed that the MOORA method identified candidate A2 as the best with a score of 0.3143, while the MAUT method ranked candidate A6 highest with a score of 0.644. The difference in rankings stems from the distinct evaluation principles of the two methods: MOORA relies on normalized ratios relative to the maximum value, while MAUT applies an aggregated utility approach. Despite this variation, both methods consistently identified the top three candidates. The developed recommendation system not only enhances transparency and accountability but also outperforms conventional intuition-based approaches by providing a structured, measurable, and replicable framework. This system has the potential to be adopted by educational institutions to ensure a fairer and more objective educator recruitment process.
Seleksi Wiraniaga Terbaik dengan Pendekatan Multi-Kriteria Metode ARAS dan SMART Cahyono, Yono; Ikasari, Ines Heidiani; Khoirudin, Khoirudin
TIN: Terapan Informatika Nusantara Vol 6 No 2 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i2.7404

Abstract

The selection of the best salesperson is a critical component in enhancing sales performance and maintaining a company’s competitiveness. However, this process is often hindered by subjective assessments and difficulties in objectively comparing candidates. This study aims to apply two Multi-Criteria Decision Making (MCDM) methods, ARAS (Additive Ratio Assessment System) and SMART (Simple Multi-Attribute Rating Technique) to evaluate and rank 15 sales candidates based on six criteria: Work Quality, Creativity, Initiative, Teamwork, Expertise, and Cost Efficiency. Qualitative assessment data were converted into quantitative values and analyzed using both methods to obtain final scores and rankings. The results indicate that the top-ranked candidates using the ARAS method are Lia Husna (A7), Eriza (A13), and Dodi (A3), while the SMART method identifies Septian (A5), Zainal (A2), and Lia Husna (A7) as the top performers. The difference in rankings is attributed to the weight distribution and the methods’ sensitivity to attribute values—SMART emphasizes high values in heavily weighted criteria, whereas ARAS evaluates the relative ratio against the ideal solution. Correlation analysis between both methods reveals partial alignment, suggesting that integrating multiple approaches strengthens result validation. Overall, the dual-method approach enhances selection objectivity and provides a more robust foundation for strategic decision-making in salesperson performance management.
Pengembangan Intelligent Leather Inspection Method Berbasis Interpretable Artificial Intelligence Frannita, Eka Legya; Wulandari, Dwi; Putri, Naimah; Rahmawati, Atiqa; Prananda, Alifia Revan
TIN: Terapan Informatika Nusantara Vol 6 No 2 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i2.7425

Abstract

The Industry 4.0 revolution, characterized by the widespread adoption of artificial intelligence and automation, has fundamentally transformed quality inspection processes in manufacturing sectors. Nevertheless, the leather tanning industry continues to rely on conventional visual inspection methods conducted by human operators, which are inherently susceptible to subjectivity, inter-operator variability, and inconsistent outcomes. This study proposes an integrated deep learning framework utilizing the NasNet-Large architecture combined with Local Interpretable Model-Agnostic Explanations (LIME) to automate objective defect detection and quality classification of pickled leather. The research employs a digital image dataset comprising four distinct leather grade categories, each annotated with expert-validated ground truth labels and professional interpretations. Experimental results demonstrate consistent model performance with 75% accuracy in both training and validation phases while achieving improved testing accuracy of 79%. LIME-based interpretability analysis reveals significant spatial convergence between model-identified defect regions and expert-annotated ground truth references. These findings indicate that the developed model exhibits remarkable competence in replicating professional leather quality inspection capabilities. The proposed approach not only enhances inspection efficiency by reducing human-dependent errors but also provides transparent decision-making interpretability - a critical requirement for reliable AI implementation in industrial applications. This research contributes to the advancement of explainable AI systems in material quality assessment, offering methodological innovation and practical implementation value for the leather manufacturing sector.
Digitalisasi Manajemen Kegiatan Kelompok Kerja Guru Menggunakan Teknologi Web Ramlah, Ramlah; Utami, Listia; Sulehu, Marwa; Ratnawati, Ratnawati; Idris, Nur Idil Fitri; Mashud, Mashud
TIN: Terapan Informatika Nusantara Vol 6 No 2 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i2.7659

Abstract

Teacher Working Group (KKG) is a professional forum for teachers to improve their competence and collaboration through routine activities such as training, preparation of teaching materials, and discussions on education policies. However, these activities are often hampered by manual management resulting in information delays, data duplication, and unstructured documentation. This study aims to design and implement an integrated and efficient web-based KKG activity management information system. The study was conducted in Cluster 3, Mamajang District, Makassar City. The method used is the Waterfall software development model, with data collection techniques through observation, interviews, and literature studies. System testing was carried out using the black box method to ensure that the system's functionality runs according to plan. The implementation results show that the system can manage membership data, activity schedules, documentation reports, and internal notifications effectively. The test results show that all system functions run well. This digitalization has been proven to support the efficiency of KKG activity management and has the potential to be adopted more widely in the context of improving the quality of basic education.
Peran Industri Microstock Animasi dalam Mendorong Pertumbuhan Ekonomi Kreatif di Era Digital Afriansyah, M.; Saputra, Joni
TIN: Terapan Informatika Nusantara Vol 6 No 2 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i2.7811

Abstract

The development of digital technology in recent years has driven global economic transformation and contributed to the emergence of the creative economy, which relies on human creativity and innovation. The animation industry, as part of the creative economy, has experienced significant growth through digital microstock platforms such as Adobe Stock, Envato Elements, and Shutterstock. This study aims to examine the role of the animation microstock industry in supporting the growth of the creative economy in Mataram City, West Nusa Tenggara. A descriptive qualitative approach was used, with data collected through observation, in-depth interviews, literature review, and documentation. Findings show that although many students and graduates in Mataram possess digital animation skills, there remain limitations in terms of access to global markets and information about microstock opportunities. However, there is strong potential in terms of technical ability, access to equipment, and a growing spirit of digital entrepreneurship. Animation microstock provides opportunities for passive income and supports independent digital creative work. With the right strategies—such as production capacity improvement, market expansion, and social media utilization—local creative actors can take advantage of these opportunities. The development of the animation microstock industry in West Nusa Tenggara holds great potential for job creation, strengthening local competitiveness, and supporting inclusive and sustainable digital economic growth.
Penerapan Strategi SEO (Search Engine Optimization) dalam Meningkatkan Penjualan Produk Digital Saputra, Joni; Afriansyah, M.
TIN: Terapan Informatika Nusantara Vol 6 No 2 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i2.7816

Abstract

The development of the digital creative industry has encouraged more and more creators to utilize microstock platforms such as Adobe Stock to sell digital animation works. However, high competition and the increasing number of assets often make digital animation products difficult to find by potential buyers. This is a major challenge for creators in increasing the visibility and sales of their work. To overcome this problem, digital marketing strategies such as Search Engine Optimization (SEO) have begun to be implemented as an effort to increase search rankings and product reach. This study aims to analyze the effect of implementing SEO techniques on increasing sales of animation-based digital products on the Adobe Stock platform. In the digital economy era, the microstock marketplace has become a strategic channel for creators in marketing visual assets, but the high level of competition demands the right optimization strategy so that products can be found and purchased. The research method used is a quantitative approach with a one group pretest-posttest design, which is applied to 60 animation assets. The SEO strategy is carried out through metadata optimization, including adjusting the title, selecting relevant and high-value keywords, and contextual descriptions based on search intent. The results showed an increase in sales from 38 to 126 products within three months after SEO was implemented, with an increase of 231.58%. The results of the paired sample t-test showed a p value <0.05, which means the increase is statistically significant. In conclusion, metadata-based SEO has proven effective in increasing the visibility and sales of digital animation products on Adobe Stock. This study recommends that digital asset creators utilize SEO strategies as an integral part of content marketing on microstock platforms.
Potensi Penggunaan Blockchain untuk Meningkatkan Keamanan Jaringan: Telaah Literatur dan Implikasi Masa Depan Ikhsan, Syaif Nurul; Febriawan, Dimas
TIN: Terapan Informatika Nusantara Vol 6 No 2 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i2.7838

Abstract

The digital era has given rise to a high dependency on network infrastructure and data, which simultaneously triggers increasingly complex information security challenges. Cyber attacks such as DDoS, data hacking and information manipulation are real threats. Meanwhile, conventional security solutions are considered not yet fully capable of handling increasingly sophisticated attacks. This research is here to fill the literature gap by exploring the potential of blockchain technology in strengthening network security systems through a systematic literature study approach to 10 recent scientific articles. This research aims to analyze the contribution of blockchain to the main dimensions of security: authentication, integrity, availability and privacy. The methodology used is a qualitative approach based on literature study, with article selection using the criteria of year of publication, theme relevance and academic validity. The results show that blockchain offers significant solutions in terms of immutable transaction recording, decentralized authentication systems, and smart contract-based privacy protection models. These findings reinforce the urgency of integrating blockchain into today's network security architecture, while paving the way for the development of hybrid systems that combine blockchain with AI and IDS.
Rancang Bangun Sistem Informasi Pemetaan UMKM Menggunakan Metode Extreme Programming Yoga, I Putu Agus Tirta; Wijaya, I Nyoman Yudi Anggara; Mega Putra, Anak Agung Gede Adi
TIN: Terapan Informatika Nusantara Vol 6 No 2 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i2.7839

Abstract

Micro, Small, and Medium Enterprises (MSMEs) have a strategic role in the economy of developing countries, including Indonesia, especially in creating jobs, reducing poverty, and driving economic growth. In Indonesia, MSMEs contribute more than 95% of total businesses and have proven to be resilient in the face of the 1997–1998 monetary crisis. However, in Susut Village, MSMEs still face various challenges, especially in terms of digitalization and limited infrastructure, which hinder their growth potential. To overcome these problems, this study designs and builds a website-based MSME Mapping Information System equipped with a Geographic Information System (GIS) to present accurate location and type of business information. This system was developed using the Extreme Programming (XP) method which focuses on an iterative and collaborative approach between the development team and users. The purpose of this system is to empower village communities, increase access to MSME information, expand market reach, and introduce superior village products to a wider audience. Thus, it is hoped that this system can encourage local economic growth and improve community welfare.
Penerapan Metode Regresi dalam Memprediksi Laba Bersih Penjualan Sari, Nur Avia Adenta; Nurmalitasari, Nurmalitasari; Nurchim, Nurchim
TIN: Terapan Informatika Nusantara Vol 6 No 2 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i2.7986

Abstract

Unexpected changes in net profit can make it difficult for XYZ to control costs and make strategic decisions. This study proposes the use of linear regression as a forecasting method for net sales profit as a way to reduce uncertainty in financial planning and assist in business decision-making. This approach was chosen because of its ability to measure and explain the correlation between dependent factors, such as net profit, and independent variables, such as sales volume and operating costs. The analysis procedure includes data exploration, regression modeling, model performance evaluation, and visualization of prediction results, which can be conducted systematically. Considering the findings of this study's evaluation, the model demonstrated excellent performance in predicting net sales profit, with an evaluation result of Root Mean Squared Error (RMSE) of 27778.50, Mean Absolute Error (MAE) of 20084.71, Mean Absolute Percentage Error (MAPE) of 9.88 %. The main advantage of this forecasting is its ability to help businesses improve the accuracy of financial planning, manage operational costs, and develop focused business plans. Additionally, management can avoid overstocking or understocking, set reasonable sales targets, and adjust production levels to market demand through the use of accurate forecasts.

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