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Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) Institut Teknologi Telkom Purwokerto Jl. D. I. Panjaitan, No. 128, Purwokerto 53147, Indonesia
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INDONESIA
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 473 Documents
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Optimization of Electric Multiple Unit Headway Ruliyanta, Ruliyanta; Idris, Fahmi; Keraf, Adhyartha Usse
JURNAL INFOTEL Vol 17 No 1 (2025): February 2025
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v17i1.1230

Abstract

The needs of the people of JABODETABEK, Indonesia, for fast, safe, and comfortable means of transportation, such as electric rail trains, are increasing. In 2023, the narrowing of the headway on the East Bekasi-Cikarang station route will cause frequent tripping of the traction substation. This is due to the increasing frequency of multiple electric unit trips and the lack of power capacity at the traction substations to supply electrical power. In addition to that, there is a voltage drop in the overhead power network because the distance between the traction substations is too long. The fastest headway is 3 minutes from the original 13 minutes. This research aims to optimize the power capacity of the traction substation in the LAA 1.10 Cikarang area. The method is load flow analysis using ETAP 19.0.1 software. Results of the design for adding the Tambun Insertion substation and the Telaga Murni Insertion substation. On a 3-minute headway, the average voltage drop increased by 22.5% on the East Bekasi - Cibitung route from 1,222 VDC to 1,497 VDC. Meanwhile, the Cibitung-Cikarang route, originally 1,282 VDC, became 1,494 VDC, or an increase of 16.5%.
Enhancing IoT Security: Optimizing PUF Responses through Pre-Processing Techniques Sukarno, Parman; Medina, Fachrul Reiza
JURNAL INFOTEL Vol 17 No 2 (2025): May
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v17i2.1236

Abstract

In this paper, we propose and detail the implementation of pre-processing techniques—specifically truncation and uniformization—to enhance the performance of authentication processes utilizing Physical Unclonable Functions (PUFs) within the context of the Internet of Things (IoT). Traditional authentication methods are often critiqued for their reliance on static secret storage, presenting inherent security risks. Physical Unclonable Function (PUF) technology addresses this concern by dynamically generating keys, akin to a device's "biometric" signature, thereby offering a more secure alternative. However, despite the dynamic nature of PUF-generated secret keys, vulnerabilities to specific attacks persist. Prior research has not focused on optimizing the secret key generated by PUFs, resulting in a lack of additional security layers and maintaining the susceptibility to PUF-targeted attacks at a constant level. This study introduces a PUF-based IoT device framework that optimizes PUF responses, aiming to significantly improve the security performance of the system. This enhancement is evaluated through metrics such as decidability, the confusion matrix, and randomness value, presenting a comprehensive approach to reinforcing system security. The optimization of Physical Unclonable Function (PUF) responses, through methods such as truncation or bit uniforming, plays a critical role in enhancing the security of IoT devices. Our findings indicate that bit uniforming notably improves system security, evidenced by a significant increase in the decidability value from 0.73 (unoptimized) to 1.37. This improvement is further reflected in the confusion matrix values, with False Rejection Rate (FRR), False Acceptance Rate (FAR), True Rejection Rate (TRR), and True Acceptance Rate (TAR) showing marked improvements from 18.02%, 4.93%, 95.06%, and 81.97% in the unoptimized state to 3.04%, 0.98%, 99.02%, and 96.96%, respectively, post-optimization. The proposed pre-processing techniques show its effectiveness in the PUF authentication systems, as superior results are obtained.
Software Effort Coefficient Optimization Using Hybrid Bat Algorithm and Whale Optimization Algorithm Puspaningrum, Alifia; Mustamiin, Muhamad; Herdiyanti, Fauziah; Noviyanto, Kamaludin
JURNAL INFOTEL Vol 17 No 1 (2025): February 2025
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v17i1.1250

Abstract

Software effort estimation is a crucial aspect in software engineering, especially in project management. It defines an effort required by a person to develop an application in certain of time. One of models which widely used for this purpose is Constructive Cost Model (COCOMO) II. In COCOMO II, two coefficients have a significant role in determining the accuracy of the effort estimation. Various methods have been conducted to estimate these coefficients to closely match the actual effort with the predicted values, such as particle swarm optimization, cuckoo search algorithm, etc. However, several metaheuristics has limit in exploration and exploitation to find optimal value. To overcome this problem, a hybrid metaheuristic combining the Bat Algorithm and Whale Optimization Algorithm (BAWOA) is proposed. This approach aims to optimize the two COCOMO II coefficients for better estimation accuracy. Additionally, the proposed method is compared with several other metaheuristic algorithms using the NASA 93 datasets. There are two evaluation criteria used in this research namely Magnitude of Relative Error (MRE) and Mean Magnitude of Relative Error (MMRE). With the optimal score among comparing method. proposed method achieves superior effort estimation, with an MMRE of 51.657%. It also proves that hybrid BAWOA can estimates predicted effort close to actual effort value.
Interpretation of Multi Sensor Measurement Results using Fuzzy Membership Function for Landslide Early Warning System Alimudin, Erna; Sumardiono, Arif; Yusuf, Muhamad; Mukhlisin, Muhammad; Apriantoro, Roni; Rabinah, Aiun Hayatu; Astuti, Hany Windri
JURNAL INFOTEL Vol 17 No 1 (2025): February 2025
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v17i1.1252

Abstract

Central Java has several areas prone to landslides. One of them is in Tembalang District in Semarang City, Central Java Province, Indonesia .Landslides can be caused by very high rainfall and there are no trees to support the soil, resulting in land shifting. Landslaezdide disasters are very dangerous because they cause many casualties. Therefore, there is a need for an early warning system for landslides. The landslide early warning system uses several sensors, namely rainfall sensors. Therefore, there is a need for an early warning system for landslides. The landslide early warning system uses several sensors, namely rainfall sensors, soil moisture sensors and soil movement. The sensor data will be processed using fuzzy logic so that the results can be more accurate. Early warning of landslides has several conditions, namely low risk to very high risk. Based on the results of real-time data collection in the landslide disaster early warning system, the results obtained were that the sensors were working well and communication sending data to the website was running well. Data processing has been carried out and can be processed via a controller with a fuzzy logic logic algorithm. The results obtained were that based on sensor data taken early warning of landslides still had a low risk with a value of 0.5375 and a medium risk with a value of 0.5875. This is due to moderate rainfall and high soil moisture, as well as ground movement ≥ 0.1
Kendali LQR berbasis inverse kinematik pada robot lengan 3 derajat kebebasan Sofyan, Adri Firmansya; Susanto, Erwin; Irsyad, Rafsanjani Nurul; Prabaswara, Alfitho Satya; Rodiana, Irham Mulkan
JURNAL INFOTEL Vol 17 No 1 (2025): February 2025
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v17i1.1257

Abstract

Linear Quadratic Regulator (LQR) is one of the optimal control methods on state space-based systems. The LQR control method is an option to be applied to the 3 DOF robot arm because multi-link systems such as robot arms are basically non-linear with quite complex modeling. Using conventional control methods has many trade-offs to find optimal stability between the parameters on the robot arm. System modeling is formulated using the Lagrangian dynamics and Euler-Lagrange method to obtain a nonlinear model of the system and then linearized it using Taylor series expansion. The values of the Q and R matrices can be adjusted to obtain a good system response for a particular trajectory. Tunning the Q and R parameters can also improve the stability of the system by reducing overshoot but causing the rise time of the system to increase
Optimization of Naive Bayes and Decision Tree Algorithms through the Application of Bagging and Adaboost Techniques for Predicting Student Study Success Febriyanto, Endi; Wasilah, Wasilah
JURNAL INFOTEL Vol 17 No 1 (2025): February 2025
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v17i1.1258

Abstract

In the Education Assessment Center of the Ministry of Education and Culture, the average grade for each student's subject in the last few years has been below 70. This condition cannot be allowed to continue. A special analysis is needed regarding factors that can help improve student grades. Predictions of student study success are urgently needed. These predictions can anticipate negative impacts that occur, including increased risk of dropout, decreased student motivation to learn, and individual potential that does not develop. The Naive Bayes and Decision Tree algorithms have been used to predict student study success. However, among its advantages, these two algorithms still have several short comings. It can cause the algorithm's performance not to be as expected. Several methods in ensemble techniques can improve algorithm performance. Two methods that are often used and can help improve the performance of classification algorithms are Bagging and Adaboost. This Study will combine Bagging and Adaboost into the Decision Tree and Naïve Bayes algorithms to optimize the results in predicting student success. The stages carried out are initial Study, data collection, data pre-processing,data processing and evaluation model, and analysis of the results. The results show that Bagging and Adaboost techniques have been proven effective in improving accuracy, precision, recall, and F1-Score performance. Combining the naïve Bayes algorithm with Adaboost increases accuracy, precision and recall significantly by 1.95%, 28.98%, and 15.79%.
Brain Tumor Detection Through Image Enhancement Methods and Transfer Learning Techniques Thohari, Afandi Nur Aziz; Mountaines, Patricia Evericho; Mohd Isa, Mohd Rizal
JURNAL INFOTEL Vol 17 No 1 (2025): February 2025
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v17i1.1262

Abstract

A brain tumor is dangerous and must be treated immediately to prevent worsening. The identification of brain tumors can be performed by a more in-depth examination by specialists or by using artificial intelligence technology through MRI datasets. Several studies have examined how artificial intelligence could be used to find brain cancer in MRI images. The algorithm usually used is CNN with the addition of transfer learning. Previous studies have produced very high accuracy, but the accuracy value can still be improved. In this study, MRI image quality is improved as a new input for modeling. The test results show that the proposed CNN Model produces an accuracy of 98.50% on the test data. This result is higher than the baseline method of 98.45%. Analysis of other metrics, such as precision, recall, and F1-score, indicates consistent performance across classes. These findings suggest that using preprocessing to improve image quality can improve Model performance. Using CLAHE and median blur to improve image quality can improve accuracy by 14.5%. This study contributes to identifying an effective combination of Model optimization techniques for image classification tasks.
Analisis Kepuasan Pengguna Menggunakan Kombinasi End User Computing Satisfaction Dan Servqual Pada Website KEMENAG Provinsi Maluku Wattimena, Nalbraint; Hartomo, Kristoko Dwi; Hong, Hendry
JURNAL INFOTEL Vol 17 No 1 (2025): February 2025
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v17i1.1264

Abstract

In recent years, the need for online service information has been increasing. To meet this need, the Regional Office of the Ministry of Religious Affairs in Maluku Province, through religious institutions, provides service information on their website using information system technology. In the last three months, total visits to the Ministry's website have increased by 39.4%. However, there are still issues with the website, such as complicated and time-consuming navigation due to large and numerous menu displays. A user satisfaction survey for this website has also never been conducted. Due to these issues, the researchers are interested in studying user satisfaction with the Ministry of Religious Affairs website using a combination of the EUCS and Servqual methods. This study aims to obtain an in-depth understanding of user satisfaction with the website using these combined methods and to identify various factors influencing user satisfaction. The results indicate that 8 variables have very high satisfaction values. From the T-test conducted, 7 variables affect user satisfaction: accuracy, format, ease of use, timeliness, responsiveness, assurance, and empathy. Among these, the most influential variable is format. Meanwhile, one variable, content, does not affect user satisfaction. According to the F-test results, the variables content, accuracy, format, ease of use, timeliness, responsiveness, assurance, and empathy collectively influence user satisfaction.
Kinerja SVM yang Dioptimalkan dengan PSO Sebagai Metode Klasifikasi untuk Analisis Sentimen Media Sosial UNNES Janaah, Miftahul; Nugroho, Anan
JURNAL INFOTEL Vol 17 No 1 (2025): February 2025
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v17i1.1266

Abstract

The rapid growth of Big Data, particularly from social media platforms, presents organizations with vast opportunities for extracting valuable insights. For educational institutions like UNNES, sentiment analysis can be crucial for monitoring and enhancing public perception. This research explores the application of sentiment analysis using SVM optimized by PSO to improve classification accuracy. Although SVM is widely known for its effectiveness in linearly separable data, it struggles with nonlinear data. By employing kernel functions and optimizing hyperparameters through PSO, this study aims to improve SVM's performance. The results show that the optimized SVM model with the RBF kernel and PSO achieved an accuracy of 82.05%, compared to 80.96% using standard SVM, demonstrating a 1.09% improvement. These findings indicate that PSO significantly enhances the efficiency and accuracy of SVM models in sentiment analysis, making it a powerful tool for analyzing social media data in educational contexts.
Performance Comparison of HFC and FTTH Using Optisystem Software Putra, Dwi Permana; Siregar, Marsul; Pandjaitan, Lanny; Bachri, Karel O; Sereati, Catherine O
JURNAL INFOTEL Vol 17 No 2 (2025): May
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v17i2.1271

Abstract

This research present the Analysis of the application of Optisystem software technology for FTTH and HFC shows that both have the capability for the WDM systems, to support a maximum transmission distance of 20 kilometers and can serve up to 32 subscribers. Key factors such as signal strength, Q factor, and bit error rate (BER) were observed and analyzed discreetly. It was found that FTTH has an average Q factor of 13.49 and HFC has an average Q factor of 7.475. The difference is about 44.59%, which indicates that FTTH has an advantage in terms of signal quality. However, based on the simulation results as well as the field measurements, Since the BER value does not exceed the maximum limit of 10-9 and the Q-factor value exceeds the minimum limit of 6, it can be stated that both technologies are reliable for efficient and high-quality communication services.

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