1 10 26 https://repository.horizon.ac.id/files/original/f49777059e48c6e45abdddfc2dd7839e.pdf 0f9f35b6f7c8e41d15712164dfb721b6 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 23, NO.2 2025 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Temperature response analysis between PD and PI controls applied to infant incubators Subject The topic of the resource Baby incubator DS18B20 sensor LM35 sensor Proportional and derivative Proportional and integral Description An account of the resource Premature infants, born with low birth weight, require specialized care and isolation due to their vulnerability to infections in public settings. Baby incubators, classified as life support equipment, play a crucial role in safeguarding these infants by maintaining a consistent temperature and humidity similar to the mother’s womb. This study compares the temperature control systems in baby incubators, specifically proportional and derivative (PD) control versus proportional and integral (PI) control. LM35 and DS18B20 sensors were employed in the study. Results from PD control using the LM35 sensor show a rise time of 5 min and 40 sec, a settling time of 25 min, and an overshoot of 2.2 °C. The DS18B20 digital sensor, under PD control, achieves a rise time in 6 min and 30 sec, a settling time of 23 min, with an overshoot of 1.2 °C. For PI control with the LM35 sensor, there’s a 3 °C overshoot, a 5-minute rise time, and a 30-minute settling time. The DS18B20 sensor under PI control exhibits a 2.7 °C overshoot, a 5-minute rise time, and a 29-minute settling time. PD control demonstrates lower overshoot and faster response but longer rise times than PI control. Future research explores fuzzy control systems and proportional integral derivative (PID)-fuzzy hybrid control. Creator An entity primarily responsible for making the resource Abd. Kholiq, Lamidi, Farid Amrinsani, Anisia Yunita Maulani Argumery, Hafizh Aushaf Mahdy Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource Dec 26, 2024 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT Baby incubator DS18B20 sensor LM35 sensor Proportional and derivative Proportional and integral https://repository.horizon.ac.id/files/original/784784735ae9aa463f155cd73969be6d.pdf e45ce44b10bbae68c491eb7cc28e889a Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 23, NO.2 2025 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A wideband microstrip antenna employing ring and hexadecagonal slots with parasitic elements for W-band applications Subject The topic of the resource Hexadecagonal slot Millimeter-wave Parasitic elements Point-to-point communications Ring slot Slotted patch W-band Description An account of the resource This article presents a monopole patch antenna, designed for operation in the W-band. The antenna is constructed on Rogers/RT 5880 dielectric material with dimensions of 3.4×4×0.16 mm³, a loss tangent of 0.0009, and a relative permittivity of 2.2. The initial design features a simple rectangular patch measuring 1.3542×1.0306 mm², powered by a microstrip line using an inset feed. To enhance the bandwidth and gain, two parasitic rectangular elements were added on both sides of the patch in addition to the incorporation of a circular ring slot with the ground plane. Further improvements in bandwidth and return loss were achieved by etching a hexadecagonal-shaped slot on the patch. Simulation results indicate that the optimized design achieves an impedance bandwidth of 28.54 GHz, ranging from 79.67 GHz to 108.21 GHz, centered at 88 GHz. The antenna also shows a maximum return loss of 59 dB and a voltage standing wave ratio (VSWR) of 1.0022. The radiation pattern is directional, with a peak gain of approximately 8.57 dBi, and a maximum directivity of about 8.6 dB, as predicted by the computer simulation technology (CST) frequency-domain solver. These advantageous characteristics make the proposed antenna a suitable choice for point-to-point transmission applications. Creator An entity primarily responsible for making the resource AbdulGuddoos S. A. Gaid1, Mohammed M. S. Qaid1, Mohammed A. E. Abdullah1, Mohammad Ahmed Alomari2 Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource Jan 23, 2025 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT https://repository.horizon.ac.id/files/original/c54e868a9c131c100efa39635f945cdb.pdf b9504e835c7c4dcb55a4c05a6dcb218a Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 23, NO.2 2025 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource K-Means clustering interpretation using recency, frequency, and monetary factor for retail customers segmentation Subject The topic of the resource Customer segmentation Industrial and innovation K-Means algorithm Machine learning Recency, frequency, and monetary analysis Small and medium enterprises Description An account of the resource Efforts to retain customers represent a crucial customer relationship management (CRM) strategy in every business, offering the potential to enhance profits, particularly for small and medium enterprises (SMEs). In the context of this study, which focuses on the transaction dataset of retailers in a developing market, Indonesia, the emphasis has predominantly been on customer attraction rather than the implementation of customer retention strategies. The primary objective of this research was to scrutinize customer transaction data within the dataset. The K-Means clustering (KMC) method, integrated with recency, frequency, and monetary (RFM) attributes, was employed to classify customers and formulate effective strategies for customer retention. Conducted through a descriptive research method with a quantitative approach, the study involved sequential stages of data preprocessing and RFM analysis for comprehensive data analysis. The outcomes revealed the identification of 5 distinct clusters with associated strategies based on the RFM scores obtained. These strategies, tailored to each cluster, serve as valuable insights in industrial and innovation for marketing and business strategic teams, offering practical approaches to customer retention that can lead to increased benefits for SMEs. Creator An entity primarily responsible for making the resource Agung Nugraha1, Yutika Amelia Effendi2, Nicholas1, Zejin Tao1, Mokh Afifuddin3, Nania Nuzulita4 Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource Jan 23, 2025 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT https://repository.horizon.ac.id/files/original/5b62e616d588d8da1f3e8a1ca27fd6dc.pdf 327d213643cebcc06ae7f06a3e7b6ade Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 23, NO.2 2025 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Prototype of alternate wetting and drying rice cultivation using internet of things for precision agriculture Subject The topic of the resource Alternate wetting and drying Encrypted secure protocol-network over wireless protocol Internet of things Irrigation Precision agriculture Sensor networks Description An account of the resource This study introduces a semi-automatic system for alternating wet and dry rice cultivation using internet of things (IoT) technology to enhance precision agriculture and address critical challenges in water resource management. The prototype consists of node and master devices powered by ESP32 microcontrollers integrated with sensors to monitor air temperature, humidity, and water levels. Communication between the devices is achieved through the low-latency, low-power encrypted secure protocol-network over wireless (ESP-NOW) protocol, enabling real-time monitoring and remote control of water pumps. Data collected by the system is displayed on ThinkSpeak servers and Nextion touch screens, aiding efficient irrigation and environmental management for farmers. Performance testing demonstrates that the system achieves reliable communication up to 115 meters with efficient energy consumption, operating for approximately two hours with a 3,000 mAh battery. By optimizing irrigation practices, the system reduces water waste while ensuring adequate crop hydration, promoting sustainable farming practices. This scalable IoT solution not only enhances productivity and resource efficiency but also contributes to broader efforts in agricultural sustainability by supporting precise environmental control and minimizing dependency on manual labor. Creator An entity primarily responsible for making the resource Akkachai Phuphanin, Metha Tasakorn Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource Dec 26, 2024 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT Alternate wetting and drying Encrypted secure protocol-network over wireless protocol Internet of things Irrigation Precision agriculture Sensor networks https://repository.horizon.ac.id/files/original/477586c8defb3f17d596d6e93a8aa228.pdf e81b95430bc9e9e6ffbc3d04e8461284 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 23, NO.2 2025 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Imposing neural networks and PSO optimization in the quest for optimal ankle-foot orthosis dynamic modelling Subject The topic of the resource Ankle-foot orthosis Modeling Neural network Particle swarm optimization System identification Description An account of the resource Individuals with abnormal walking patterns due to various conditions face significant challenges in daily activities, especially walking. Ankle-foot orthosis (AFO) devices are crucial in providing essential support to their lower limbs. Accurately modeling the dynamic behavior of AFO systems, particularly in predicting ground reaction forces, is a complex yet vital task to ensure their effectiveness. This research develops dynamic models for AFO systems using advanced modeling techniques, employing both parametric and non-parametric approaches. Parametric methods, such as particle swarm optimization (PSO), and non-parametric methods, like multi-layer perceptron (MLP) neural networks, are utilized through system identification methods. According to the findings, the MLP neural network continuously generates objective results and performs exceptionally well in correctly detecting the AFO system, attaining a noticeably lower mean squared prediction error of 0.000011. This research highlights the potential of advanced modeling techniques, particularly MLP neural networks, in enhancing AFO system modeling accuracy. Although parametric techniques like PSO are useful, the MLP approach performs better, offering insightful information about modelling AFO systems and indicating that non-parametric techniques like MLP neural networks have potential to further AFO creation and control. Creator An entity primarily responsible for making the resource Annisa Jamali1, Aida Suriana Abdul Razak1, Shahrol Mohamaddan2 Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource Dec 26, 2024 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT Ankle-foot orthosis Modeling Neural network Particle swarm optimization System identification https://repository.horizon.ac.id/files/original/efbd94446cbac57212f76186e6ee44be.pdf 665473207b52b1069c2c50304f5919fc Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 23, NO.2 2025 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Advanced crop yield prediction using machine learning and deep learning: a comprehensive review Subject The topic of the resource Crop yield prediction Deep learning Machine learning Remote sensing Systematic literature review Vegetation indices Description An account of the resource The advancement of machine learning (ML) and deep learning (DL) techniques has significantly improved crop yield prediction, making it more accurate and reliable. In this review, the implementation of ML and DL algorithms for crop yield prediction is thoroughly investigated, focusing on their crucial role in enhancing crop productivity. Along with ML and DL algorithms examine, the review analyses the use of remote sensing technologies, such as satellite and drone data, in providing high-resolution inputs essential for accurate yield predictions. The study identifies the state of art algorithms, most used features, data sources and evaluation metrics, providing a comparison of ML and DL. The findings indicate that DL models are more effective with large datasets, while ML models remain robust for smaller datasets. The future directions are proposed to develop the generalised models for different crops and regions. The review aims to assist researchers by summarising state of art techniques and identifying the present. Creator An entity primarily responsible for making the resource Ayush Anand, Kavita Jhajharia Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource Jan 22, 2025 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT Crop yield prediction Deep learning Machine learning Remote sensing Systematic literature review Vegetation indices https://repository.horizon.ac.id/files/original/6d44aab05c9b9b41b421c821abcf33ee.pdf 38b3dacc5c7ccf115ae00245882d1171 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 23, NO.2 2025 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Analyzing the impact of sports activity intensity on muscle capacity through integrated biosensor technology Subject The topic of the resource Biosensors Electromyography Integrated Muscle Sport activity Description An account of the resource In the past few years, biosensor technology has paved the way for new insights into the physiological effects of physical exercise. Quantitative analysis, especially in the case of muscle capacity measurement, is the focus of studies to assess the impact of sports activities. Therefore, this study examines the impact of sports activity intensity on muscle capacity using an integrated biosensor system developed at Bandung State Polytechnic. Surface electromyography (sEMG) measurements were conducted on 30 participants aged 20–25 during various sports activities. Results showed a strong positive correlation (r=0.814) between sports activity frequency and muscle contraction, suggesting higher activity correlates with increased muscle activity. Conversely, the correlation during muscle relaxation was low (r=0.261), indicating independence from sports activity. In the future, it is expected that integrated biosensors will have the ability to concurrently measure and monitor various parameters like heart rate (via electrocardiogram), blood oxygen levels (via photoplethysmography), and blood pressure. The integrated biosensor system allows for comprehensive assessment and optimization of sports performance and injury prevention strategies. Creator An entity primarily responsible for making the resource Ervin Masita Dewi1, Nurista Wahyu Kirana1, Sugondo Hadiyoso2 Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource Dec 26, 2024 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT Biosensors Electromyography Integrated Muscle Sport activity https://repository.horizon.ac.id/files/original/521c04989adceed40ae2f780d3058be2.pdf a1cc1459f9be1589ce3b8d745d8c9bfb Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 23, NO.2 2025 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Comparing global system for mobile and G-NetTrack signal strength in drive test study Subject The topic of the resource Global positioning system network track Global system for mobile module Kolmogorov-Smirnov Mann-Whitney Normality test Received signal strength indicator Description An account of the resource The quality of wireless signals is determined by the received signal strength indicator (RSSI), which can be measured using various tools, including Android apps and global system for mobile (GSM) modules. To enhance the measurement of signal quality and communication reliability, this study aimed to develop a complementary instrument consisting of a microcontroller, global positioning system (GPS) module, GSM module, and microSD card. The firmware was developed using C++ code and compiled using the Arduino integrated development environment (IDE). In addition, this study utilized the Kolmogorov-Smirnov test (K-S test) normality and the Mann-Whitney U test to investigate any differences in RSSI quality between the GSM module and global positioning system network track (G-NetTrack). The results showed that the GSM module consistently produced higher RSSI values than G-NetTrack in most locations along the route. Furthermore, the K-S test normality suggested that the RSSI values obtained from both tools were not normally distributed, and the Mann-Whitney U test revealed a significant difference between the two samples, with G-NetTrack having lower values than the GSM module (U=14730, p<0.05). This study demonstrated that the GSM module provides stronger signal strength measurements than G-NetTrack during the drive test, and highlighted the importance of using appropriate statistical tests to analyze RSSI data. Creator An entity primarily responsible for making the resource Hollanda Arief Kusuma1, Dwi Eny Djoko Setyono2 Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource Jan 22, 2025 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT https://repository.horizon.ac.id/files/original/b1f2565286f6e48ca4ac0f22b307de84.pdf db432a1c49d173c5a9f2e5d7808df88d Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 23, NO.2 2025 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Oversampling vs. undersampling in TF-IDF variations for imbalanced Indonesian short texts classification Subject The topic of the resource Bahasa Indonesia Imbalanced dataset Oversampling method Short-text classification Term frequency inversed document frequency Undersampling method Description An account of the resource Even though it is considered a more traditional method compared to more modern algorithms, term frequency inversed document frequency (TF-IDF) nevertheless produces good results in a range of text mining tasks. This study assesses the effectiveness of several TF-IDF modifications for short text classification. Imbalanced datasets are another issue that is addressed in this research. To rectify the imbalanced issue, we integrate standard, log-scaled, and boolean TF-IDF in short text classification with undersampling and oversampling methods. Precision, recall, and f-measure metrics are used to evaluate each experiment. The best result is obtained when applying boolean TF-IDF with the oversampling method. Oversampling methods outperform the undersampling methods in every experiment, although there are some cases where experiments with undersampling methods are considerable. Additionally, our conducted study reveals that employing modified TF-IDF, such as boolean or log-scaled versions, provides greater advantages to classification performance, particularly in handling imbalanced datasets, when compared to solely relying on the standard TF-IDF approach. Creator An entity primarily responsible for making the resource I Nyoman Prayana Trisna, Ni Wayan Emmy Rosiana Dewi, Muhammad Alam Pasirulloh Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource Dec 26, 2024 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT Bahasa Indonesia Imbalanced dataset Oversampling method Short-text classification Term frequency inversed document frequency Undersampling method https://repository.horizon.ac.id/files/original/bb67e21080ea25111ce8e75fe8e3409d.pdf 4e92f017110238652c46b0ac3edb12a4 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 23, NO.2 2025 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Detecting fake news through deep learning: a current systematic review Subject The topic of the resource Deep learning Machine learning Misinformation detection Natural language processing Systematic review Description An account of the resource This systematic review explores the domain of deep learning-based fake new detection employing advanced search practices on Scopus and Web of Science (WoS) databases with keywords “fake news,” “deep learning,” and “method.” The study encompasses 33 articles categorized into three main themes: i) dataset and benchmarking for fake news detection, ii) multimodal approaches for fake news detection, and iii) deep learning applications and techniques for fake news detection. The analysis reveals the significance of curated datasets and robust benchmarking in improving the efficacy of fake news detection models. Additionally, the review highlights the emergence of multimodal approaches that integrate textual and visual information for improved detection accuracy. The findings clarify the essential role of deep learning applications, emphasizing the development of sophisticated models for automated identification of fake news. This systematic study adds to a thorough grasp of current research trends and offers insightful information for future developments in the field of deep learning-based false news identification. Creator An entity primarily responsible for making the resource Idza Aisara Norabid, Masita Jalil, Rozniza Ali, Noor Hafhizah Abd Rahim Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource Dec 26, 2024 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT Deep learning Machine learning Misinformation detection Natural language processing Systematic review