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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 758 Documents
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Pengembangan Sistem Informasi Manajemen Membership Gym Terintegrasi Kartu Digital Menggunakan Metode Research and Development Brian Fajar Adiyatma; Rauhulloh Ayatulloh Khomeini Noor Bintang
TIN: Terapan Informatika Nusantara Vol 7 No 1 (2026): June 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i1.10106

Abstract

Data management at Hercules Fitness Karanganyar, which still relies on manual methods using ledgers, serves as the primary background for this research. The problems encountered include the complexity of tracking active membership status, a high potential for duplicated payment records, and the time-consuming preparation of monthly reports, all of which decrease operational productivity. Therefore, this study aims to design and develop a web-based membership information system featuring a novel automated digital card integration and unified notification system utilizing the Laravel framework.This system is expected to facilitate member data administration, transaction recording, attendance tracking, training scheduling, notification delivery, and the provision of digital membership cards. The Research and Development (RnD) approach utilizing the ADDIE (Analysis, Design, Development, Implementation, Evaluation) model was applied in this study, encompassing the phases of needs analysis, system architecture design, development, and evaluation. System testing was conducted at Hercules Fitness Karanganyar, involving 27 participants consisting of gym management and members. Data were collected through direct observation, interviews, and questionnaires. The results indicate that the developed application successfully streamlines the registration process, membership management, transaction tracking, and information delivery to members in a more systematic manner. Based on the Black Box testing, all crucial features on both the administrator and user interfaces operated validly according to the planned scenarios. Furthermore, the User Acceptance Testing (UAT) yielded a feasibility percentage of 88.49%, which based on Likert scale interpretation criteria classifying the system as highly feasible. In conclusion, this Laravel-based membership management software significantly enhances operational efficiency by automating daily administrative workflows and reducing data recapitulation time at Hercules Fitness Karanganyar. This research delivers a valuable practical contribution by providing a digital governance ecosystem blueprint that can be readily adopted by local sports service MSMEs to improve their service efficacy.
Analisis Banker’s Algorithm untuk Penghindaran Deadlock Berbasis Simulasi Kuantitatif Multiskenario Christian Bastanta Sembiring Meliala; Teti Desyani; Moch Ibba Ali Yassin; Aldiansyah Sastrawinata; Mikael Surya Saputra; Brian Aidil Rizkita; Rizki Arohman Maulana
TIN: Terapan Informatika Nusantara Vol 7 No 1 (2026): June 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i1.10112

Abstract

Deadlock represents a critical threat in operating system resource management, as it has the potential to bring all computational processes to a complete halt. This study examines the effectiveness, efficiency, and constraints of the Banker's Algorithm as a deadlock avoidance mechanism through a multi-scenario quantitative simulation. The data were derived from simulations involving three core components: the resource allocation matrix (Allocation), the maximum process requirement declaration (Max), and the resource availability vector (Available), within a system configuration consisting of five processes and three resource types. The findings demonstrate that the Banker’s Algorithm accurately distinguishes between safe and unsafe states through its two primary mechanisms: the Safety Algorithm and the Resource-Request Algorithm. With Available set to [3, 3, 2], the algorithm successfully identified the safe execution sequence ⟨P1, P3, P4, P0, P2⟩, ensuring all processes could complete without deadlock risk. When Available was reduced to [2, 1, 0], the system entered an unsafe state in which no process could initiate execution. Through multi-scenario simulations, the critical transition threshold from a safe to an unsafe state was identified at approximately 83% resource utilization. In terms of efficiency, the O(n²×m) time complexity makes the algorithm well-suited for small to medium-scale systems, though it may become a performance bottleneck in large-scale cloud computing environments. This study produces a quantitative evaluation framework that can serve as a reference for implementing the Banker’s Algorithm in modern operating systems.
Perbandingan Long Short-Term Memory dan Bidirectional Long Short-Term Memory pada Analisis Sentimen Ulasan Wisata Adam Malik; Nur Ariesanto Ramdhan; Otong Saeful Bachri
TIN: Terapan Informatika Nusantara Vol 7 No 1 (2026): June 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i1.10120

Abstract

Tourism reviews on Google Maps can be used to understand visitors’ perceptions of destination quality, including aspects that often become sources of satisfaction or complaints. This study analyzes reviews of Pantai Alam Indah because the destination has a large number of reviews, diverse text forms, and an imbalanced sentiment distribution. The purpose of this study is to compare the performance of Long Short-Term Memory and Bidirectional Long Short-Term Memory in tourism review sentiment analysis. The data were collected through Google Maps scraping and processed through case folding, cleaning, tokenizing, stopword removal, and stemming. The final dataset consisted of 2,702 reviews, including 2,024 positive reviews and 678 negative reviews. To reduce the effect of class imbalance, the training process applied class weighting by assigning a higher weight to the negative class. Both models used a 128-dimensional embedding layer, a 64-neuron dense layer, a sigmoid activation function in the output layer, Adam optimizer, batch size of 32, 10 epochs, and a validation split of 0.2. In addition to sentiment classification, the reviews were grouped into cleanliness, facilities, price, and general aspects using a keyword-based rule-based approach. The evaluation results show that Bidirectional Long Short-Term Memory achieved an accuracy of 75.79%, precision of 76.33%, recall of 75.79%, and F1-score of 76.04%, while Long Short-Term Memory achieved an accuracy of 75.05%, precision of 75.48%, recall of 75.05%, and F1-score of 75.25%. The performance difference between the two models was relatively small, so the results should be interpreted carefully. The aspect analysis shows that the general aspect dominated positive sentiment, while cleanliness had the highest number of negative sentiments.
Visualisasi Interaktif Emosi pada Teks Uji Terkontrol Menggunakan RoBERTa GoEmotions dan Roda Emosi Plutchik M. Faiq Rafii Wahyudi; Zainal Abidin
TIN: Terapan Informatika Nusantara Vol 7 No 1 (2026): June 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i1.10131

Abstract

Text-based emotion classification results are commonly presented as labels, tables, or probability scores, making relationships among emotions difficult for users to interpret intuitively. This problem indicates the need for a visualization approach that not only presents the dominant emotion but also shows the intensity and relationship of supporting emotions in a single visual representation. This study aims to develop an interactive emotion visualization system for controlled test texts by integrating the RoBERTa GoEmotions model and the Plutchik Emotion Wheel. The system processes input text through light preprocessing, Transformer model inference, rule based emotion mapping into the eight basic Plutchik emotions, max normalization, visual threshold filtering, and radial visualization using D3.js. The contribution of this study lies in integrating the more detailed GoEmotions output into the basic emotion structure of Plutchik, applying normalization and visual threshold filtering to improve readability, and developing an interactive visualization that supports the interpretation of text emotion analysis results. Functional testing was conducted to examine the consistency of the inference process, emotion mapping, score normalization, and visualization generation. The test example shows that a sentence expressing success produces joy as the dominant emotion, with an aggregate score of 1.220 and a normalized value of 1.000. This result is consistent with the context of the input text and is visualized as the most dominant petal in the Plutchik Emotion Wheel. The findings indicate that integrating modern NLP models with interactive visualization can improve the interpretability of text-based emotion analysis compared with numerical or tabular presentation.
Analisis Komparatif OWASP ZAP dan Nuclei pada Vulnerability Scanning Non-Intrusive Aplikasi Web E-Commerce Publik Bambang Harie Wiyono; Rintan Madi Sari; Lukman Rosyidi
TIN: Terapan Informatika Nusantara Vol 7 No 1 (2026): June 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i1.10143

Abstract

This study discusses a comparative analysis of non-intrusive vulnerability scanning results on public e-commerce web applications using OWASP ZAP and Nuclei. This study is not intended to directly prove vulnerability exploitation, but rather to evaluate the characteristics of scanning outputs based on the number of aggregate findings, unique findings after deduplication, CVSS v3.1 severity distribution, OWASP Top 10 mapping, overlap, and priority findings that require manual validation. Testing was conducted using a black-box and non-intrusive approach on five targets coded E1 to E5. The coding was applied to maintain testing ethics on public targets, while target selection was based on open web application access, relevance to the e-commerce context, and variations in service characteristics that could be observed externally. The results showed 83 aggregate findings, consisting of 68 OWASP ZAP findings and 15 Nuclei findings. After the normalization and deduplication process, 81 unique findings were obtained with 2 overlapping findings. OWASP ZAP produced more consistent outputs across several targets and was dominant in the Security Misconfiguration category, particularly security headers, Content Security Policy, cache-control, and cookie attributes. Meanwhile, Nuclei produced fewer findings but made an important contribution by detecting 5 Critical findings and 3 High findings, especially on target E4. The limitation of this study lies in output constraints on several targets; therefore, the scanning results cannot be interpreted as the final security condition of the targets, but rather as initial technical indications that require further validation. This study does not measure precision, recall, false positive rate, or scanning time efficiency because the testing was conducted on public targets under non-intrusive limitations and without Proof of Concept. The results indicate that the combination of OWASP ZAP and Nuclei provides more complete analysis coverage than the use of a single scanner because both have different and complementary detection characteristics.
Pengembangan Gamifikasi Scratch Berbasis MDLC untuk Meningkatkan Computational Thinking pada Pembelajaran Algoritma dan Pemrograman SMK Sri Mulyani Nst; Resmi Darni; Mahesi Agni Zaus; Rizkayeni Marta
TIN: Terapan Informatika Nusantara Vol 7 No 1 (2026): June 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i1.10161

Abstract

Students' Computational Thinking skills in Algorithms and Programming materials are still relatively low because the use of technology-based interactive learning media is not optimal. This study aims to develop gamification-based learning media using Scratch and test its feasibility and practicality in learning. The research method used is Research and Development (R&D) with the Multimedia Development Life Cycle (MDLC) model which includes the stages of concept, design, material collecting, assembly, testing, and distribution. The study was conducted at SMK Muhammadiyah 1 Padang with 35 class X students in Informatics as subjects. Data collection was carried out through expert validation, practicality questionnaires, and pretest and posttest tests. The initial practicality test was conducted on 15 students as a small group which is part of the total research subjects before implementation on all subjects. The validation results by three media experts showed a percentage of 93.7% with a very feasible category. The results of the practicality test obtained a percentage of 96% with a very practical category. The results of the Computational Thinking ability measurement showed an average pretest score of 7.71 (48.2%) and a posttest score of 12.6 (78.75%) with an N-Gain value of 0.59 which is in the moderate category. These findings indicate an increase in students' Computational Thinking abilities after using the developed media. This study produced a gamification-based learning media using Scratch that has been declared valid with a very feasible and practical category for use in learning. In addition, the results of the media implementation showed an increase in students' Computational Thinking abilities with a moderate increase category. The results of this study contribute as an alternative interactive learning media that can be used by teachers in Informatics learning, especially in Algorithm and Programming materials at the vocational high school level.
Pengaruh Intensitas Konsumsi Short-Form Video Terhadap Beban Kognitif Siswa Sekolah Menengah Atas Muhammad Ihsan; Mastur Mastur; Hamsi Mansur
TIN: Terapan Informatika Nusantara Vol 7 No 1 (2026): June 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i1.10168

Abstract

The paradigm shift in social media consumption toward short-form video formats has triggered maladaptive behavior that threatens high school students' working memory capacity due to continuous exposure to instant audiovisual information without adequate restoration intervals. This study aims to empirically examine the effect of short-form video consumption duration intensity on students' cognitive load based on the Cognitive Load Theory framework. A causal-associative quantitative approach using an explanatory survey method was implemented. Primary data collection was conducted online utilizing structured questionnaires via Google Forms administered to a single-shot sample of 167 student respondents determined through convenience sampling technique across two schools in Binuang District, Tapin Regency, namely MAN 2 Tapin and SMAN 1 Binuang. Data analysis techniques included descriptive statistical analysis and inferential testing using simple linear regression executed separately per dimension. The results demonstrate a significant asymmetrical pattern. In Model 1, daily usage duration has a significant positive effect on Intrinsic Load (p = 0,04 < 0,05) with a contribution of 5.0%. Conversely, Model 2 testing indicates that consumption duration has no significant effect on Germane Load (p = 0,090 > 0,05) with a contribution of only 1.7%. In conclusion, high duration of accessing short videos linearly increases brain workload in processing material density but fails to contribute to substantive academic schema construction. This research is expected to contribute to the development of educational technology studies regarding the phenomenon of cognitive load on students in the digital era.
Analisis Pengaruh Sistem Pentanahan Tower dan Sambaran Petir Terhadap Gangguan serta Evaluasi Efektivitas Metode Perbaikan Pertanahan pada SUTT 150 kV Wyananda Fiqi Fadlan Adhima; Rummi Sirait
TIN: Terapan Informatika Nusantara Vol 7 No 1 (2026): June 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i1.10177

Abstract

The high frequency of lightning activity in Indonesia poses a significant threat to the reliability of power transmission systems. Based on operational data, the 150 kV Tanjung Jati–Sayung transmission line recorded the highest number of lightning-induced disturbances within the Semarang Transmission Maintenance Unit (UPT Semarang) during the 2021–2025 period, making it a relevant subject for further investigation. This study aims to analyze the relationship between lightning strike frequency, tower grounding resistance, and transmission system disturbances, as well as to evaluate the effectiveness of grounding system improvement methods that have been implemented. A quantitative approach was employed using descriptive analysis, Pearson correlation, and simple linear regression based on lightning strike data, tower grounding resistance measurements, and disturbance records. The results indicate that lightning strike frequency has a positive relationship with transmission system disturbances, with a correlation coefficient of 0.137 and a p-value of 0.0452. Similarly, tower grounding resistance exhibits a positive relationship with system disturbances, with a correlation coefficient of 0.2133 and a p-value of 0.0017. Although these relationships are statistically significant, the relatively low coefficient of determination (R² < 5%) suggests that both variables explain only a small portion of the variation in lightning-related disturbances, indicating the presence of other contributing factors that were not included in this study. Nevertheless, grounding system improvement remains one of the technical measures that can be optimized to reduce the risk of transmission line disturbances. The evaluation results show that towers employing the Multi Rod Grounding (MRG) method exhibited the lowest disturbance probability among the grounding improvement methods observed in this study. Overall, the findings provide empirical insights into the relationship between lightning strike frequency, tower grounding resistance, and transmission system disturbances, and may serve as a useful reference for developing maintenance strategies aimed at improving transmission system reliability.
Pengembangan Aplikasi Keuangan Menggunakan Metode Regresi Linier untuk Efisiensi Pengelolaan Transaksi dan Laporan Keuangan Bengkel Hendri Setiawan; Wakhid Kurniawan
TIN: Terapan Informatika Nusantara Vol 7 No 1 (2026): June 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i1.10184

Abstract

The rapid advancement of information technology has encouraged various business sectors to enhance efficiency in data management, particularly in the financial domain. Has Jaya Automotive Workshop still relies on manual record-keeping for transaction management and financial reporting, which poses risks such as recording errors, delays in report generation, and difficulties in decision-making. This study aims to develop a web-based financial information system to improve transaction management efficiency and provide accurate, structured, and informative financial data. The research employs a software engineering approach using the Waterfall development model, encompassing requirements analysis, system design, implementation, and testing. The system is developed using containerization technology with Docker to ensure ease of deployment and environmental consistency. Additionally, Machine Learning is integrated using a linear regression algorithm to predict profit and loss based on historical data. The results indicate that the developed system simplifies transaction recording, accelerates financial reporting, and presents data visualization in graphical form to enhance user understanding of financial conditions. The prediction feature provides an estimate of future financial performance, although the model’s accuracy remains relatively limited due to fluctuating data characteristics. Overall, the system improves the efficiency and effectiveness of financial management and adds value in supporting data-driven decision-making at Has Jaya Automotive Workshop.
Model Rekomendasi Latihan Muscle Building Pemula Menggunakan Forward Chaining Berbasis Karakteristik Pengguna Pasadena Saka; Vivi Aida Fitria
TIN: Terapan Informatika Nusantara Vol 7 No 1 (2026): June 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i1.10214

Abstract

Beginners in muscle building training often have difficulty determining an exercise program that suits their body condition, training goals, available time, training location, equipment availability, and injury history. This study aims to design and develop a muscle building exercise recommendation system for beginners using the forward chaining method. The input data include injury history, height and weight, resistance training experience, basic technique mastery, previous training frequency, training goal, training focus, training location, equipment availability, number of training days, and training duration per session. Height and weight are used to calculate Body Mass Index (BMI), while training experience, basic technique mastery, and previous training frequency are used to determine the beginner level. The knowledge base is arranged into six rule groups: injury rules, body condition rules, beginner level rules, initial intensity rules, program adjustment rules, and exercise recommendation rules. The inference process matches user facts with the rule set step by step until an exercise recommendation is produced. The system output includes an exercise program, schedule, duration, intensity, exercise examples, body condition notes, injury notes, and matched rule information. Initial functional testing and knowledge base validation were conducted using 30 user input combination scenarios. The results showed that 26 scenarios were suitable and 4 scenarios were not yet suitable, resulting in a suitability percentage of 86.67%. These findings indicate that the system can run most of the inference flow in the tested scenarios, but additional rules are still needed for uncovered fact combinations.

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