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Eko Fajar Cahyadi
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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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Prediction of patient length of stay using random forest method based on the Indonesian national health insurance Aini Hanifa; Yogiek Indra Kurniawan; Jati Hiliamsyah Husen; Arief Kelik Nugroho; Ipung Permadi
JURNAL INFOTEL Vol 15 No 3 (2023): August 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i3.963

Abstract

Inpatient care is the largest component of healthcare service expenditure. Healthcare management plays a role in reducing expenditure costs and improving healthcare services. Identification of factors related to patient length of stay and accurate prediction of how long patients will be hospitalized becomes important to support stakeholder decision making. In this study, the length of stay for patients using BPJS insurance services was predicted using the random forest method. An experiment has been conducted to compare different numbers of trees and candidate split attributes in a prediction model. The experimental results showed that increasing the number of trees and candidate split attributes can improve prediction performance and reduce the resulting error rate. The optimal value was found when the number of trees was 100 with the MSE/Variance value of 0.3805. The main determinant variables for predicting patient length of stay were found to be the patient's disease diagnosis, participant segment, and healthcare facility type.
Klasifikasi Citra Medis Tumor Otak Menggunakan Algoritma Convolutional Neural Network Alwas Muis; Sunardi Sunardi; Anton Yudhana
JURNAL INFOTEL Vol 15 No 3 (2023): August 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i3.964

Abstract

Brain tumor is a disease that is very dangerous for humans where this disease really needs faster and more accurate treatment. This disease requires early detection because it requires fast and accurate medical treatment. Machine learning helps solve problems by leveraging deep learning technology in the branch of machine learning. Deep learning is a technology that can detect, classify, and segment various problems in machine learning. One of the methods used in deep learning is the Convolutional Neural Network. This method is most often used in performing image processing where this method has various types of feature extraction. The purpose of this study was to test the accuracy of using the Convolutional Neural Network method in classifying brain images. The brain image used in this study is an image scanned by Magnetic Resonance Imaging. The dataset in this study was downloaded from the Kaggle website as many as 7023 data consisting of four classes of brain image data, namely glioma, notumor, meningioma, and pituitary classes. The results of this study obtained an accuracy value of 84% so that this research can be used by medical personnel to diagnose brain tumors easily, quickly, precisely, and accurately.
Design of a microcontroller-based quadcopter prototype module Fly Sky XL163RX take off and landing Saragih, Yuliarman; Ibrahim, Ibrahim; Satrio Hadikusuma, Ridwan; Handayana, Kayat; Elisabet, Agatha
JURNAL INFOTEL Vol 15 No 3 (2023): August 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i3.966

Abstract

This research paper presents the design and development of a microcontroller-based quadcopter prototype module, named Fly Sky XL163RX, with the capability of take off and landing. The objective of this study is to design a reliable and efficient quadcopter module that can be utilized for various applications, such as aerial photography, surveillance, and delivery services. The proposed quadcopter module is equipped with the Fly Sky XL163RX microcontroller, which serves as the control unit for managing the flight operations. The design process involves several key steps, including the selection of appropriate components, integration of sensors and actuators, and the development of control algorithms. The quadcopter module utilizes a combination of sensors, including gyroscopes, accelerometers, and altimeters, to gather real-time data and stabilize the flight. The control algorithm employs a proportional-integral-derivative (PID) controller to adjust the motor speeds and maintain stability during take off and landing. The Fly Sky XL163RX microcontroller offers a user-friendly interface and supports various communication protocols, allowing for easy customization and control of the quadcopter module. Additionally, the module incorporates safety features, such as emergency landing capabilities and collision avoidance systems, to enhance flight security and prevent potential accidents. The performance of the Fly Sky XL163RX quadcopter module was evaluated through extensive flight testing. The results demonstrate the module's capability to achieve stable take off and landing operations, as well as its responsiveness to user commands. The module's compact size and lightweight design make it suitable for indoor and outdoor applications. In conclusion, this research presents the design and development of the Fly Sky XL163RX microcontroller-based quadcopter module, which exhibits reliable and efficient take off and landing operations. The module's integration of sensors, control algorithms, and safety features contribute to its overall performance and usability. Future work may focus on enhancing the module's capabilities, such as implementing autonomous flight modes and improving battery efficiency.Quadcopter, Microcontroller, FlySky XL163RX, Take Off, Landing, Control Algorithm, Sensors, Actuators, PID Controller, Flight Testing, Aerial Applications.
Design of machine learning-based water quality prediction system with recursive feature elimination cross-validation James Julian; Annastya Bagas Dewantara; Fitri Wahyuni
JURNAL INFOTEL Vol 15 No 3 (2023): August 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i3.977

Abstract

Lack of clean water has become a problem in the world, and it is estimated that by 2025 there will be 2.8 billion people who will experience a shortage of clean water. The high demand for clean water and the limited water sources with proper potency is one of the main reasons for the need for a device capable of measuring the potability level of water that is flexible to carry and does not require high costs in the manufacturing process. In this paper, the design of machine learning-based potability devices with recursive feature elimination with cross-validation (RFECV) is carried out as a guide in making the design of a water potability detection system, and the results obtained from RFECV with the Random Forest (RF) algorithm have a higher accuracy value. 15.71% better than the RF model, 6.85% better than the Support Vector Machine (SVM) model, and 8.57% better than the Artificial Neural Network (ANN) model trained without RFECV. The water potability prediction system's design selection is based on feature elimination results in the RFECV process. It is based on a literature review on device selection. The proposed water potability detection system consists of ESP32 as the primary computing device, electrochemical spectroscopy-based Al/PET sensor to detect sulfate values with a sensitivity of 0.874 Ω/ppm, PH4502C as a pH measuring instrument with an accuracy of up to 98.10%, WD-35802-49 electrode. as a device for measuring hardness in water with a measurement range of 0.4 – 40,000 ppm, a total dissolved solids sensor to determine the solids content in water with an accuracy of up to 97.80%, as well as a carbon-based sensor for measuring chloramines with a reading capacity of 186 nA/ppm.
Penyempurnaan Sistem Inkubator Bayi Berbasis FLC Menggunakan Algoritma Genetika Setiyo Budiyanto; Lukman Medriavin Silalahi; Dadang Gunawan; Erry Yulian Triblas Adesta
JURNAL INFOTEL Vol 15 No 3 (2023): August 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i3.991

Abstract

This research problem focuses on treating premature babies due to hypothermia so that the baby must be put in an incubator for several days. Conventional intensive care method in premature babies, namely skin-to-skin care method between mother and child. Meanwhile, the latest technological developments, the method is already based on electrical-Internet of Things (IoT) engineering. This research proposes the design of an IoT-based prototype known as a smart incubator. This prototype has been equipped with a real-time monitoring system and system settings using the mamdani fuzzy inference system control method and combined using the Genetic Algorithm (GA) method. The results showed that the ideal temperature range in the smart incubator was 33° C with an accuracy of 99.97% and was in accordance with the fuzzy membership degree in the range of 29° C ≤x≤ 37° C. Furthermore, the ideal relative humidity range in the smart incubator was 60% with an accuracy of 98.60% and was in accordance with the fuzzy membership degree in the range of 59 ≤x≤ 65. Then, the noise range in the smart incubator is 37.9dB to 56.8dB with an accuracy of 96.44% and has been appropriate at the fuzzy membership degree. At a maximum distance of 50cm, it takes 8 seconds for the prototype to detect movement as a safety measure.
Analytic hierarchy process for evaluating the quality of courier services in e-commerce services from the perspective of Pos Indonesia Purwokerto Jihad Sindhu Gossa; Khairun Nisa Meiah Ngafidin; Sisilia Thya Safitri
JURNAL INFOTEL Vol 15 No 3 (2023): August 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i3.1016

Abstract

E-commerce became one of the technological developments in Indonesia in the fourth industrial revolution. Since then, the daily needs transaction process has become accessible through the e-commerce platform. The rapid development of e-commerce is predicted to increase and thus encourage the development of courier services over the past period, making courier services an essential element that affects customer satisfaction in e-commerce services. An analysis of customer satisfaction in several e-commerce service providers towards customer reviews on Google Play conducted by Sasmita and a statement by the Ministry of Trade through a consumer complaint report in 2021 stated that complaints about problems in the e-commerce sector have increased, which includes courier services incorporated with e-commerce service providers. Gulc argued that at least seven factors determine the quality of courier service based on the customer's perspective. The AHP method assists courier services affiliated with e-commerce services in recognizing which of these seven factors of courier service quality dimensions require attention to create a sustainable competitive advantage. This research aims to measure the priority level of criteria in determining the quality of courier services on e-commerce platforms, thus providing recommendations for the appropriate service priorities for courier service companies. The calculation results using AHP on the seven factors determining the quality of courier service according to the Manager Assistant of the Service Department at the Central Purwokerto Branch of the Kantor POS Indonesia show that the responsiveness criterion is more important than the other six criteria.
Forecasting a museum visit post pandemic using exponential smoothing model Shinta Puspasari; Rendra Gustriansyah; Ahmad Sanmorino
JURNAL INFOTEL Vol 15 No 4 (2023): November 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i4.949

Abstract

This paper aims to evaluate the performance of a machine learning model for predicting the number of visitors to a museum after the COVID-19 pandemic. The easing of policies that began to be implemented by the Palembang city government after the end of the pandemic at the end of 2022 became a momentum in predicting the number of visits to the SMBII museum. During the pandemic the museum experienced a very drastic decline due to closures and restrictions on activities at the museum and had an impact on achieving the museum's targets in the fields of tourism and education. Museum managers need to establish a strategy as an effort to achieve the targets set during the post-pandemic period. This study predicts the number of visits to the SMBII museum in post-pandemic years by applying the double exponential smoothing (ESM) model. The dataset used is SMBII museum visit data which is divided into three categories of visitors, namely students, local and foreign. The evaluation results show that the double ESM model has the best performance with MSE = 3.8 and a = 0.9. The phenomena that occurred in the student visitor category affected ESM's performance in predicting visits where MSE in the post-pandemic period had a 200% higher value than before the pandemic which was influenced by the implementation of post-pandemic policies in museums. With the forecasting results in this study, it is hoped that it can become information in developing strategies and improving the performance of post-pandemic museums
Development of a wearable resonator mask for breathing rate monitoring Yusnita Rahayu; Tasya Kirana; Jack Ping Soh
JURNAL INFOTEL Vol 15 No 4 (2023): November 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i4.979

Abstract

As one of the processes of patient care, diagnosis, and monitoring are the most important steps in the medical field. Sleep apnea is a problem that affects about 25 million Americans, and 80% of them go untreated because it is not identified. Monitoring has a big role in making patient treatment decisions. So this research aims to produce a wearable resonator mask that can work as a breathing rate monitor. The proposed resonator will use the relative humidity generated during the respiration process. The resonator uses a textile jeans material that is flexible, comfortable, and fits on a mask. Testing is carried out in 3 different positions; lying down, sitting, and standing. There is a difference in the percentage of RH produced from each position based on the difference in the frequency range produced. The proposed resonator operates well at 3.9 GHz.
Implementation of association rule using apriori algorithm and frequent pattern growth for inventory control Imam Riadi; Herman Herman; Fitriah Fitriah; Suprihatin Suprihatin; Alwas Muis; Muhajir Yunus
JURNAL INFOTEL Vol 15 No 4 (2023): November 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i4.980

Abstract

Business success is a business that is able to compete and grow keep abreast of developments in the business world. Especially in the retail sector, where competition is getting tighter. Business owners need to pay attention to the layout of goods and stock management to improve service and meet consumer needs because consumers often have difficulty in finding goods. On the other hand, shortages and excess stock often occur due to lack of goods management. Based on these problems, appropriate techniques are needed for the management of goods supply, one of which is to apply techniques found in the branch of science. Data mining is a technique of association rules. This study aims to find patterns of placement and purchase of goods in generating Association Rule using FP-Growth algorithm. The dataset in this study used data on sales of goods in clothing stores. The results of the study of 140 transactions there are 24 association rules consisting of 7 association rules with 2-itemsets and 17 association rules with 3-itemsets that most often appear in transactions. Based on the order of the highest support value, namely CKJ→STX^LK with a support value of 67%, while the highest confidence value, there are 3 association rules that get the same value, namely STX^CKJ→LK, STX^CAK→LK, STX^RI→LK with a value of 100%. Thus, the rules of association produced by the frequent itemset algorithm, FP-growth, can serve as decision support for the sales of goods in small and medium-sized retail businesses
Metode Pembelajaran Mesin untuk Memprediksi Status Gizi Balita Gustriansyah, Rendra; Suhandi, Nazori; Puspasari, Shinta; Sanmorino, Ahmad
JURNAL INFOTEL Vol 16 No 1 (2024): February 2024
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i4.988

Abstract

Malnutrition is one of the leading health problems experienced by toddlers in various countries. Based on the 2022 Indonesian Nutritional Status Survey results, malnutrition in children under five in Indonesia is higher than the average malnutrition in Africa and globally. Therefore, a way is needed to predict the nutritional status of children under five early and quickly so that the Government (through District Health Office) can immediately provide the necessary treatment. This study aims to predict or classify the toddlers' nutritional status based on age, body mass index (BMI), weight, and body length using various machine learning (ML) methods, namely naïve Bayes, linear discriminant analysis, decision tree, k-nearest neighbor, random forest, and support vector machine. The predictive performance of each ML method was evaluated based on accuracy, sensitivity, specificity, the area under curve, and Cohen's Kappa coefficient. The test results show that the RF method is the most recommended for predicting toddlers' nutritional status. The study's contribution is to obtain information about toddlers' nutritional status easier.

Page 37 of 48 | Total Record : 473

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