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Jurnal INFOTEL
Published by Universitas Telkom
ISSN : 20853688     EISSN : 24600997     DOI : https://doi.org/10.20895/infotel.v15i2
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Jurnal INFOTEL is a scientific journal published by Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) of Institut Teknologi Telkom Purwokerto, Indonesia. Jurnal INFOTEL covers the field of informatics, telecommunication, and electronics. First published in 2009 for a printed version and published online in 2012. The aims of Jurnal INFOTEL are to disseminate research results and to improve the productivity of scientific publications. Jurnal INFOTEL is published quarterly in February, May, August, and November. Starting in 2018, Jurnal INFOTEL uses English as the primary language.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 11 Documents
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Search results for , issue "Vol 16 No 4 (2024): November 2024" : 11 Documents clear
The Comparative Analysis Of Multi-Criteria Decision-Making Methods (MCDM) In Priorities Of Industrial Location Development Agusta Praba Ristadi Pinem; Aria Hendrawan; Nur Wakhidah
JURNAL INFOTEL Vol 16 No 4 (2024): November 2024
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v16i4.1099

Abstract

The process of prioritizing the development of an industrial area's site is a matter that necessitates a mature approach. The establishment of an industrial region has significant social implications for the surrounding locality. However, it is also necessary to take into account the availability of variables that facilitate the functioning of such an industrial zone. The goal of the study "A Comparative Analysis of Multi-Criteria Decision Making Methods (MCDM) for Determining the Priority of Industrial Area Location Development" is to compare and contrast different MCDM methods in the context of deciding which industrial area locations should be developed first. A case study was undertaken, examining various possible industrial sites for future development. Multiple approaches, namely MOORA, WASPAS, ARAS, COPRAS, and AHP, are employed to ascertain the prioritization of industrial area development locations. This study presents a comparative analysis of each approach by using the Spearman Rank correlation and utilizing the factual data obtained from the Department of Capital Plantation and Integrated One Door Services (DPMPTSP). The external research is anticipated to involve a comprehensive review of the literature on the efficacy of Multiple Criteria Decision Making (MCDM) methods. This research has the potential to assist both governmental bodies and private entities in establishing priorities for the development of industrial areas, taking into account prevailing circumstances and conditions while also considering various significant factors and criteria.
Optimizing Autism Spectrum Disorder Identification with Dimensionality Reduction Technique and K-Medoid Galih Hendro Martono; Neny Sulistianingsih
JURNAL INFOTEL Vol 16 No 4 (2024): November 2024
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v16i4.1142

Abstract

This research addresses the challenges of diagnosing and treating Autism Spectrum Disorder (ASD) using dimensionality reduction techniques and machine learning approaches. Challenges in social interaction, communication, and repetitive behaviours characterize ASD. The dimension reduction used in this research aims to identify what features influence autism cases. Several dimension data reduction techniques used in this research include PCA, Isomap, t-SNE, LLE, and factor analysis, using metrics such as Purity, silhouette score, and the Fowlkes-Mallows index. The machine learning approach applied in this study is k-medoid. By employing this method, our goal is to pinpoint the unique characteristics of autism that may facilitate the detection and diagnosis process. The data used in this research is a dataset collected for autism screening in adults. This dataset contains 20 features: ten behavioural features (AQ-10-Adult) and ten individual characteristics. The results indicate that Factor Analysis outperforms other methods based on purity metrics. However, due to data structure issues, the t-SNE method cannot be evaluated using purity metrics. PCA and LLE consistently provide stable silhouette scores across different values. The Fowlkes-Mallows index results closely align, but t-SNE tends to yield lower values. The choice of algorithm requires careful consideration of preferred metrics and data characteristics. Factor analysis is adequate for Purity, while PCA and LLE consistently perform well. This research aims to improve the accuracy of ASD identification, thereby enhancing diagnostic and treatment precision.
Solusi Rantai Pasokan Berbasis Blockchain Menggunakan Teknologi IPFS dan QR untuk Tenun Tradisional di Nusa Tenggara Barat Heri Wijayanto; Melki Jonathan Andara; Diky Wiraguna; Nadiyasari Agitha; Mosiur Rahaman
JURNAL INFOTEL Vol 16 No 4 (2024): November 2024
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v16i4.1195

Abstract

Traditional weaving is a significant cultural heritage in West Nusa Tenggara, Indonesia, renowned for its unique and intricate woven fabrics. However, the industry faces challenges such as product counterfeiting and the need for more transparency in the supply chain, hindering its growth and economic potential. This paper proposes a solution by leveraging blockchain technology to enhance traceability, security, and efficiency throughout the supply chain of traditional woven products. Integrating the InterPlanetary File System (IPFS) and Quick Response (QR) codes further fortifies data integrity and provides consumers with comprehensive product information. A prototype web application is developed, demonstrating the practical implementation of this framework. Rigorous testing of the prototype validates the correct functionality of the proposed solution. This innovative framework aims to safeguard the authenticity and sustainability of the traditional woven products from West Nusa Tenggara, fostering a more competitive and secure industry while preserving cultural heritage.
A Systematic Literature Review of BERT-based Models for Natural Language Processing Tasks Agung Fatwanto; Fardan Zamakhsyari; Rebbecah Ndungi
JURNAL INFOTEL Vol 16 No 4 (2024): November 2024
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v16i4.1206

Abstract

Research area in natural language processing (NLP) domain has made major advances in recent years. The Bidirectional Encoder Representations from Transformers (BERT) and its derivative models have been at the vanguard, gaining notice for their exceptional performance across a variety of NLP applications. As a response to this context, hence, this study aims to conduct a systematic literature review on current research in BERT-based models in order to describe their characteristic variations on three frequently demanded natural language processing (NLP) tasks, i.e. text classification, question answering, and text summarization. This study employed a systematic literature review method as prescribed by Kitchenham. We collected 4,120 papers from publications indexed by Scopus and Google Scholar from which 42 complied to our defined review criteria and finally chosen for further analysis. Our review came up with three conclusions. First, in order to select appropriate models for particular NLP tasks, three primary concerns should be considered: i) the type of NLP problem to be resolved (i.e. NLP task to be served), ii) the specific domain to be handled (such as financial, medical, law/legal or others), and iii) the intended language to be applied (such as English or others). Second, learning rate, batch size, and the type of optimizer were the three most considered hyperparameters to be properly arranged in model training. Third, the most widely used metrics for text classification tasks were F1-score, accuracy, precision, and sensitivity (recall), while question answering, and text summarization tasks were mostly used the Exact Match and ROUGE respectively.
Two Omnidirectional Antenna Models for Ship Hull Corrosion Detection Radar System Hepi Ludiyati; Aqiila Putri Zharfani Ashlah; Erika Dwi Jayanti; Hanny Madiawati; Enceng Sulaeman
JURNAL INFOTEL Vol 16 No 4 (2024): November 2024
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v16i4.1213

Abstract

This paper discusses two modified monopole antenna models. These antenna models are designed to detect hull corrosion of ships, which is predicted to be the cause of hull leaks. The modification was carried out by adding a conical parasitic element aimed at widening the bandwidth and increasing the antenna gain. The conical parasitic on the first antenna is directed upwards, while the second is the opposite. The first model uses a cone with a larger diameter than the second model. The calculation of the cone diameter is based on half the wavelength of the frequencies generated by the antenna. With a smaller diameter, PTFE is added between the monopole and the parasitic cone to avoid short circuits. This configuration is intended to see the effective antenna model widen the bandwidth and increase the gain. Antenna performance testing was carried out using a vector network analyzer and software-defined radio. The test results show that both antenna models are omnidirectional in radiation. The first model operates at a frequency of 3904.7 - 7793.1 MHz with a bandwidth of 3888.4 MHz and a highest gain of 10 dBi. The second model operates at a frequency of 2282.4 - 3324.1 MHz with a bandwidth of 1041.7 MHz and a highest gain of 8dBi. Thus, the first antenna model has a higher bandwidth and gain than the first model, but both have met the requirements for ship hull corrosion detection antennas.
A Random Oversampling and BERT-based Model Approach for Handling Imbalanced Data in Essay Answer Correction Dian Ahkam Sani
JURNAL INFOTEL Vol 16 No 4 (2024): November 2024
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v16i4.1224

Abstract

The task of automated essay scoring has long been plagued by the challenge of imbalanced datasets, where the distribution of scores or labels is skewed towards certain categories. This imbalance can lead to poor performance of machine learning models, as they tend to be biased towards the majority class. One potential solution to this problem is the use of oversampling techniques, which aim to balance the dataset by increasing the representation of the minority class. In this paper, we propose a novel approach that combines random oversampling with a BERT-base uncased model for essay answer correction. This research explores various scenario of text pre-processing techniques to optimize model accuracy. Using a dataset of essay answers obtained from eighth-grade middle school students in Indonesian language, our approach demonstrates good performance in terms of precision, recall, F1-score and accuracy compared to traditional methods such as Backpropagation Neural Network, Naïve Bayes and Random Forest Classifier using FastText word embedding with Wikipedia 300 vector size pretrained model. The best performance was obtained using the BERT-base uncased model with 2e-5 learning rate and a simplified pre-processing approach. By retaining punctuation, numbers, and stop words, the model achieved a precision of 0.9463, recall of 0.9377, F1-score of 0.9346, and an accuracy of 94%.
Solar Radiation Prediction using Long Short-Term Memory with Handling of Missing Values and Outliers Alfin Syarifuddin Syahab; MS Hendriyawan Achamd
JURNAL INFOTEL Vol 16 No 4 (2024): November 2024
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v16i4.1225

Abstract

The pyranometer sensor is an instrument for measuring Global Horizontal Irradiance (GHI) which is used as parameter for analyzing and predicting weather. GHI data which is processed into prediction model for photovoltaics is useful for determining the performance of solar power generation systems in distributed energy operations. However, GHI sensor data has weaknesses in missing values and outliers due to measurement errors. The research designed a GHI sensor data prediction model using data preprocessing by the imputation of missing values using linear, polynomial, and Piecewise Cubic Hermite Interpolating Polynomials (PCHIP) interpolation and eliminating outliers using Random Sample Consensus (RANSAC) on the dataset. Previous researches show that Long Short-Time Memory (LSTM) can improve the performance of predictions compared to machine learning. This research designs an LSTM prediction model with data preprocessing and without data preprocessing. The results of the imputation of missing values obtained the best performance in PCHIP with Mean Absolute Error (MAE) 39.708 W/m2, Root Mean Absolute Error (RMSE) 76.224 W/m2, Normalized Root Mean Absolute Error (NRMSE) 0.433, and Coefficient Determination (R2) 0.903 then imputation from outlier elimination obtained MAE 44.377 W/m2, RMSE 86.738 W/m2, NRMSE 0.500, and R2 0.886. RANSAC testing succeeded in eliminating 100% outliers. The results of LSTM with data preprocessing obtained better performance with the best evaluations on MAE, RMSE, NRMSE, and R2 for test data of 42.863 W/m2, 82.396 W/m2, 0.396 and 0.918. This study contributes to GHI prediction model that can handle missing values ​​and outliers from sensors to support solar power plants.
Design of a 20 Mbps OQPSK Modulator Based on Multiplexers Prapto Nugroho
JURNAL INFOTEL Vol 16 No 4 (2024): November 2024
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v16i4.1237

Abstract

This paper aims to delve into the design and implementation aspects of an OQPSK (Offset Quadrature Phase Shift Keying) modulator within the context of modem technology, underscoring its pivotal role in contemporary information technology infrastructure. The research primarily focuses on elucidating the theoretical foundations of OQPSK modulation, which represents an enhancement of QPSK modulation techniques. Central to the design is the utilization of a multiplexer to select one carrier signal out of four, which is subsequently modulated by data bits. Furthermore, the modulator employs two square wave signals phased 90 degrees apart, which are transformed into differential sinusoidal signals to constitute the carrier signal. Operating frequencies encompass a 5 MHz streaming data bits frequency and a 10 MHz clock frequency. Simulation results validate the efficacy of the OQPSK modulator by demonstrating its capability to generate modulated signals at a robust data transfer rate of 20 Mbps. This underscores the modulator's effectiveness in transmitting digital data over analog communication channels. In conclusion, the designed OQPSK modulator exemplifies its proficiency in efficiently modulating and demodulating signals, thereby bolstering connectivity and communication across diverse societal sectors. This research contributes significantly to the advancement of modem technology, which is indispensable for the expansion and maintenance of modern communication networks, ensuring robust connectivity in the digital age.
Revolutionizing Classroom Attendance: A Wireless Smart System Using ESP-NOW Protocol Leonardo Onggo; Susilo Wibowo; Rafina Destiarti Ainul
JURNAL INFOTEL Vol 16 No 4 (2024): November 2024
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v16i4.1259

Abstract

In an era where technological advancements drive improvements across various sectors, enhancing efficiency in educational management systems is crucial. This paper presents a novel wireless attendance system that leverages the ESP-NOW protocol, which offers advantages over traditional Wi-Fi by enabling low-power, low-latency, and direct device-to-device communication without the need for an intermediary network. The system employs ESP32 modules configured as both slave and master devices. Slave devices, positioned on the lecturer’s desk, interact with students' smartphones when the lecturer initiates the class, while master devices, strategically placed at multiple locations within the classroom, compile and consolidate attendance data for each room. The system incorporates RSSI-based restrictions via the ESP-NOW protocol to prevent overlapping attendance between rooms and ensure that students can only record their presence if they are physically within the designated classroom. Attendance data is automatically logged and made accessible in real-time through a dedicated mobile application for lecturers. Empirical testing demonstrates 100% accuracy in attendance recording, with an average verification time of less than 1 second and a data transmission rate ranging from 700 to 800 Bytes/seconds.
Desain dan implementasi Arus Keluaran Zeta Penaik-Penurun Inverter Jembatan-H menggunakan STM32F407VET6 Jonathan Wijaya; Leonardus Heru Pratomo
JURNAL INFOTEL Vol 16 No 4 (2024): November 2024
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v16i4.1261

Abstract

The development of electrical power conversion equipment is increasing, along with the utilization of new and renewable energy sources. Power conversion equipment from DC to AC voltage, known as inverters, is extensively researched and implemented in this sector. These inverters commonly operate as step-down voltage in specific applications used as step-ups with limited operating ranges. A step-up-down inverter with a single power circuit is developed to overcome this issue. Still, the number of power switches used correlates with the complexity of its control strategy. This paper investigates a step-up-down inverter using the Zeta H-Bridge Inverter with the implementation of six power switches. Furthermore, this type of inverter is operated with a controlled output current utilizing the STM32VET407 microcontroller. The control method is derived based on possible operational modes. An HX10-P current sensor detects the output current. It maintains itself according to the current reference by installing a proportional-integral controller. The initial verification utilizes computational simulation with power simulator software, ensuring the system operates as intended. The final stage involves implementation in the laboratory and testing with standardized equipment. The test results meet the IEEE 519 standard, where the output current has a THD of 1.1%.

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