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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,
Aerospace Engineering Arts Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Social Sciences Veterinary Other
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 656 Documents
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Perbandingan Sensitivitas Serta Stabilitas MQ-4 dan MQ-5 Berbasis Arduino Untuk Deteksi Kebocoran Gas LPG Yaaman Nazara; Gogor Christmass Setyawan; Agustinus Rudatyo Himamunanto
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.v7i1.9992

Abstract

LPG gas leakage is a serious household safety threat in Indonesia, where 88.59% of households use LPG as their primary cooking fuel. Although colorless and faintly odorous at low concentrations, its flammable nature can cause explosions or fires if undetected. This research aims to compare MQ-4 and MQ-5 sensor performance in a single Arduino Uno-based gas leakage detection system. A quantitative experiment with direct comparison was conducted under identical conditions inside a sealed acrylic chamber measuring 16 × 12 × 10 cm, using LPG gas from a refillable lighter to simulate household leakage. Parameters measured include sensitivity, defined as the slope of the log(Rs/R₀) versus log(relative ppm) curve, and reading stability from the standard deviation of repeated measurements, where Rs is sensor resistance when exposed to gas and R₀ is resistance in clean air. All ppm values are relative estimates based on official sensor datasheets. Results show MQ-5 has higher sensitivity with a slope of 0.7914 compared to MQ-4 (0.6505), while MQ-4 is more stable with a log₁₀(Rs/R₀) standard deviation of 0.656 compared to MQ-5 (0.669). The system successfully detected all 30 leakage scenarios (100%) without false alarms, with a classification success rate of 99.0% per session. This research recommends MQ-5 for rapid early detection and MQ-4 for long-term monitoring requiring data consistency, thus both contribute as empirical evidence for a simple, accurate, and economical gas leakage detection solution.
Sistem Penjadwalan Ruangan Berbasis Website dengan Validasi Benturan Jadwal Salma Nurul Ikhsani; Nova Tri Romadloni
TIN: Terapan Informatika Nusantara Vol 6 No 12 (2026): May 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i12.9995

Abstract

The utilization of information technology holds a vital position in elevating the excellence of data management and services in government agencies. This research was conducted at the Samber Nyawa Information Center of the Karanganyar Regency Communication and Information Service, which continues to face challenges in managing room utilization. The problem is that the current room scheduling procedure is carried out conventionally, often leading to overlapping schedules, information distribution constraints, and low efficiency in monitoring room utilization for both domestic and public events. This investigation objectifies to model and build a website-based room scheduling information system to facilitate the room scheduling mechanism in a more proficient and consolidated layout. The platform development deploys the Waterfall model, which comprises the phases of prerequisite analysis, system design, execution, verification, and maintenance. The application is structured leveraging the Laravel framework alongside a MySQL database and executes the Model View Controller (MVC) pattern. Strategies for gathering information are executed via observation, questions and answers, and literature review. The system validation utilized a User Acceptance Testing (UAT) scheme involving 20 participants consisting of Karanganyar Regency Communications and Information Technology (Diskominfo) employees, students, interns, and general users who had tried the website-based room scheduling information system. The examination findings showed that the system achieved a user approval rating of 89%, categorized as very good. The finalized software is capable of facilitating the progression of managing room usage schedules and provides real-time and structured room availability information for users.
Perbandingan Performa CNN MobileNetV2 dan K-Nearest Neighbors untuk Klasifikasi Kondisi Tanaman Cabai Tegar Wahyu Adi Saputra; Rodhiyah Mardhiyyah
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.v7i1.10004

Abstract

Diseases and pests affecting chili plants can reduce crop quality and productivity if not detected at an early stage. The identification of plant conditions is still commonly performed through manual visual observation, making the process prone to diagnostic errors and time-consuming. This study aims to compare the performance of a MobileNetV2-based Convolutional Neural Network (CNN) and K-Nearest Neighbors (KNN) for chili plant condition classification using digital images. The dataset consisted of 7,991 training images, 515 validation images, and 355 testing images generated through a cropping process based on bounding-box annotations, covering seven categories of chili plant conditions: Anthracnose, Aphid, Armyworm, Healthy, Leaf Spot, Whitefly, and Yellowisha. Preprocessing included image resizing to 128 × 128 pixels and normalization. The CNN model employed a MobileNetV2 architecture with transfer learning, while the KNN model utilized manually extracted features consisting of Histogram of Oriented Gradients (HOG), Local Binary Pattern (LBP), and Color Histogram. Model performance was evaluated using a confusion matrix, accuracy, precision, recall, and F1-score with a weighted-average approach. The results show that CNN outperformed KNN, achieving an accuracy of 81.69%, precision of 86.28%, recall of 81.69%, and F1-score of 81.34%, whereas KNN achieved an accuracy of 45.63%, precision of 66.80%, recall of 45.63%, and F1-score of 42.24%. The contribution of this study lies in providing a comparative analysis between deep learning and traditional machine learning approaches on a dataset encompassing diseases, pests, and healthy conditions within the same classification scenario. The findings indicate that CNN's automatic feature extraction capability produces more effective visual representations than the manually engineered features used by KNN.
Implementasi Model MaxViT untuk Deteksi Penyakit Daun Cabai Berbasis Mobile Nur Puspita Amalia; Salamun Rohman Nudin
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.v7i1.10025

Abstract

Chili is an important horticultural commodity in Indonesia, but its productivity often decreases due to leaf diseases such as Cercospora leaf spot, Powdery Mildew, Mites and Thrips, and Nutritional deficiency. Manual disease identification requires more time and may produce less accurate diagnoses. This study aims to develop a mobile-based chili leaf disease detection system using the Multi-Axis Vision Transformer (MaxViT) model. The dataset consisted of 10,987 chili leaf images divided into five classes and split into training, validation, and testing data with a ratio of 70:15:15. Model training was carried out using four optimizer scenarios, namely a standard baseline model, SGD, Adam, and AdamW. The result showed that the Adam optimizer archieved the best performance with 99,45% accuracy, 99,44% precision, 99,45% recall, and 99,45% F1-Score. The best model was converted into TensorFlow Lite format with a file size of 32.0 MB and deployed in a mobile application. The application can detect diseases through camera capture or gallery images and provide prediction results along with disease descriptions and treatment recommendations. Testing results indicate that the system performs well under various usage conditions. This system is expected to help users indentify chili leaf diseases quickly, practically, and accurately.
Pengembangan Sistem Informasi Dokumentasi Budaya dan Pengelolaan Dokumen Legalitas Kesenian Reyog Ponorogo Berbasis Web Menggunakan Metode Rapid Application Development Fauzan Yuda Ayub Wijanarko; 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.v7i1.10035

Abstract

The management of art studio data and legal documents related to Reyog Ponorogo cultural heritage is still conducted manually, resulting in difficulties in archive retrieval, risks of document loss, and limited public access to cultural information. Furthermore, there is currently no integrated platform capable of combining cultural documentation and legal document management within a centralized digital system. This study aims to develop a web-based information system for cultural documentation and legal document management of Reyog Ponorogo to support cultural digitalization and improve document archiving processes. The research employed the Research and Development (R&D) method using the Rapid Application Development (RAD) model, which consists of requirements analysis, system design, implementation, and testing phases. The system was developed using the Laravel framework, Model View Controller (MVC) architecture, and a MySQL database. The main features include art studio data management, legal document uploads, document verification, cultural news management, and online cultural information services. System evaluation was conducted using Black Box Testing and User Acceptance Testing (UAT). The results of Black Box Testing indicated that all system functions operated according to the specified functional requirements. Furthermore, the UAT results involving 20 respondents achieved a total score of 654 out of a maximum score of 700, resulting in a user acceptance rate of 93.4% and an average score of 4.67 out of 5, categorized as Very Good. These findings demonstrate that the system is capable of supporting cultural documentation and legal document management in a more structured, accessible, and digitally archived manner. The contribution of this study lies in providing an integrated digital platform that combines cultural documentation and legal document management to support the sustainable preservation of Reyog Ponorogo cultural heritage.
Backend Berbasis Laravel dengan Pendekatan Gamifikasi pada Sistem Pelaporan Tugas Harian Mahasiswa Nasrin Akhsani; Novi Tristanti
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.v7i1.10042

Abstract

Management of digital reporting of students' daily assignments still faces various obstacles, such as data inconsistencies, weak activity validation, delays in collecting assignments, and not yet optimal mechanisms that can improve student discipline on an ongoing basis. These problems show the importance of implementing a backend that is structured and capable of effectively supporting the automation of academic processes. This research aims to implement a web-based daily task reporting system backend using the Laravel framework with a gamification approach in the Nugas system. The research uses a qualitative approach with an implementation case study type and an adaptive Waterfall system development method. The research subjects consisted of 10 active students of the Informatics Study Program at Muhammadiyah Karanganyar University who were selected using a purposive sampling technique. Data collection was carried out through semi-structured interviews, observations, questionnaires and system documentation, while data analysis used source triangulation techniques to maintain the credibility of the research results. Backend implementation produces a system with 17 database Tabels, 15 controllers, and 2 main services, namely GamificationService and NotificationService. The results of black box testing on 74 RESTful API endpoints show that 72 endpoints (97.3%) function according to system requirements. Performance testing using Laravel Debugbar on 10 main endpoints shows an average database query time of ~35 ms without any N+1 query problems found, and the cache implementation runs well. Trials on 10 students showed that all respondents successfully submitted assignments and obtained the Early Bird badge, while the average questionnaire score reached 4.16 on a scale of 5 in the good category. This research provides a contribution in the form of a gamification-based Laravel backend implementation model that is integrated with a RESTful API to support the management of academic tasks in a more structured, automatic and scalable manner. Overall, the research results show that the application of gamification elements in the form of points, badges, leaderboards and achievements can increase student motivation in completing academic assignments.

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