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Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer
Published by Politeknik Negeri Banjarmasin
ISSN : 25983245     EISSN : 25983288     DOI : -
Core Subject : Science, Engineering,
Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering
We are the Editor of Jurnal ELTIKOM, invites Mr. / Ms Lecturer, researcher and practitioner to be able to publish your paper on topics covering Electrical Engineering, Electronics Engineering, Telecommunications Engineering, Computer Engineering, Information Technology.
Arjuna Subject : -
Articles 7 Documents
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Search results for , issue "Vol. 5 No. 1 (2021)" : 7 Documents clear
Retracted: Prakiraan Kebutuhan Energi Listrik Kota Parapat Tahun 2018 - 2022 Sebagai Kawasan Strategis Nasional Danau Toba Pakpahan, Victor Maruli; Pinem, Sanjaya
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 5 No. 1 (2021)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v5i1.177

Abstract

This article has been Retracted due to violations by the authors.
Prediksi Inflasi Indonesia Berdasarkan Fuzzy Ann Menggunakan Algoritma Genetika Rifa'i, Anwar
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 5 No. 1 (2021)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v5i1.215

Abstract

Monetary policy makers have a fear of inflation because it can trigger an increase in poverty and soar-ing budget uses. A high level of inflation will result in a country's economic collapse. Monetary policy making needs to be studied to prevent this. One effort that can be done is to predict the inflation that will occur. Inflation rate time series data can be used to predict future inflation rates. Pemangku kebijakan moneter memiliki ketakutan terhadap inflasi karena dapat memicu naiknya angka kemiskinan dan mel-onjaknya penggunaan anggaran. Tingkat Inflasi yang tinggi akan mengakibatkan jatuhnya perekonomian suatu negara. Pengambilan kebijakan moneter perlu dikaji secara mendalam untuk mencegah hal terse-but. Salah satu upaya yang dapat dilakukan adalah dengan melakukan prediksi inflasi yang akan terjadi. Data tingkat inflasi dari waktu ke waktu merupakan modal untuk melakukan prediksi tingkat inflasi pada waktu mendatang. Suatu prediksi yang baik memiliki nilai error yang kecil. Pada prediksi menggunakan fuzzy artificial neural network (Fuzzy ANN) metode backpropagation, nilai error dapat diperkecil dengan melakukan optimasi pada bobot yang dihasilkan. Pada penelitian ini, optimasi bobot Fuzzy AAN dil-akukan menggunakan algoritma genetika. Model prediksi yang diperoleh selanjutnya dievaluasi menggunakan MAPE untuk menentukan keakuratan prediksi. Hasil penelitian menunjukkan bahwa pred-iksi menggunakan backpropagation neural network dioptimasi menggunakan algoritma genetika (10,33%) lebih baik dibandingkan dengan prediksi menggunakan backpropagation neural network saja (11,67%). Setelah mengetahui bahwa kedua model memiliki hasil prediksi yang cukup baik, keakuratan kedua model dibandingkan menggunakan independent sampe t-test berdasarakan error yang dihasilkan. Hasilnya menjukkan bahwa pada tingkat kepercayaan 95% prediksi menggunakan Fuzzy ANN yang telah dioptimasi menggunakan algoritma genetika (M= 0,69, SD= 0,0421) lebih baik secara signifikan dibandingkan degan fuzzy ANN saja (M= 0.97, SD= 0,04634 ), t(22 )= 1.71714, p=0.013.
Finding The Most Desirable Car Using K-Nearest Neighbor From E-Commerce Websites Naufal, Mohammad Farid; Wibisono, Yudistira Rahadian
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 5 No. 1 (2021)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v5i1.221

Abstract

The increasing number of cars that have been released to the market makes it more difficult for buyer to choose the choice of car that fits with their desired criteria such as transmission, number of kilometers, fuel type, and the year the car was made. The method that is suitable in determining the criteria desired by the community is the K-Nearest Neighbors (KNN). This method is used to find the lowest distance from each data in a car with the criteria desired by the buyer. Euclidean, Manhattan, and Minkowski distance are used for measuring the distance. For supporting the selection of cars, we need an automatic data col-lection method by using web crawling in which the system can retrieve car data from several ecommerce websites. With the construction of the car search system, the system can help the buyer in choosing a car and Euclidean distance has the best accuracy of 94.40%.
Internet of Thing Menggunakan Firebase dan Nodemcu untuk Helm Pintar Prasetyawan, Purwono; Samsugi, Selamet; Prabowo, Rizky
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 5 No. 1 (2021)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v5i1.239

Abstract

The Indonesian government has made laws with the aim of safety in riding, but some people still violate it, especially in wearing standard helmets and riding tired or drowsy. This needs to be campaigned for public awareness. One of the technology trends in the industrial era 4.0 is the Internet of Things (IoT). This article discuss the utilize of IoT innovation to support riders' safety in preventive efforts by designing a smart helmet prototype. This helmet has the intelligence to force the rider to wear the helmet correctly (helmet detection) and alert the rider when drowsiness (drowsiness detection). This study uses an experimental method, applying the Firebase and NodeMCU platforms to present the IoT concept in implementing the smart helmet functionality. The MPU6050 accelerometer is used for drowsiness detection and for helmet detection using a flex sensor with a switch to ensure that the helmet belt is worn properly. The actuator of the helmet detection is a relay (contact to the engine motor), while the drowsiness detection actuator is the buzzer (beep sound). The two smart helmet functionalities run well. The accuracy value for drowsiness detection is 78% and for helmet detection 100%.
Pengukuran Nilai Grounding Terbaik Pada Kondisi Tanah Berbeda Arifin, Jaenal
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 5 No. 1 (2021)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v5i1.251

Abstract

A good grounding or grounding system is a mechanism to protect electronic devices. This protection can be direct or indirect during lightning strikes in rainy seasons. The characteristic and condition of the soil is one of the factors that can affect the grounding value. In this research, the measurement of grounding value is conducted in different soil conditions. The conditions are the watery, clay, dry, rocky, sand and swamp soils. This research purpose is to determine the value of grounding or grounding resistance in different type of soils. The measurement methods use three point method and four electrode method by sticking the electrodes into the ground. The value of the grounding resistance displayed on the measuring instrument (Earth Resistance Tester) would be smaller if the electrodes are planted deeper with the addition of electrode rods, and the distance between the electrodes is set between 5 to 10 meters.
Implementasi Node MCU Sebagai Serial Komunikasi dengan Arduino Uno pada Smart Shopping Trolley Yuliani, Livia Ayudia; Nurpulaela, Lela; Latifa, Ulinnuha
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 5 No. 1 (2021)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v5i1.282

Abstract

Currently, there are many buyers who use the offline selling concept, so we often see long queues at su-permarkets. The queue is due to the length of time a chasier scans the price of each producs in the shop-ping cart. However, people always complain when doing the buying process at supermarkets. The public regretted the long queue process when making payment transaction at the cashier. This results in the length of the waiting time increasing according to the length of the queue. So, to be able to overcome this problem is to use internet of things which aims to facilitate the client in the process of purchasing a prod-uct. The internet of things device or component as an internet module is NodeMCU V2 AMINCA. The measurement method used is Quality of Service by using the assistance of the Wireshark application. Val-ue of throughput, packet loss, latency, and jitter obtained is 2229 bit/s, 0% packets, 25,284 seconds, 0,050 ms with category of zero throughput index (bad) and index four for packet loss, latency, and jitter.
VOL 5 NO 1 2021 COVER Fauzan, Reza
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 5 No. 1 (2021)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

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