cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Alfian Maarif
Contact Email
alfianmaarif@ee.uad.ac.id
Phone
-
Journal Mail Official
biste@ee.uad.ac.id
Editorial Address
-
Location
Kota yogyakarta,
Daerah istimewa yogyakarta
INDONESIA
Buletin Ilmiah Sarjana Teknik Elektro
Published by Universitas Ahmad Dahlan
ISSN : 26857936     EISSN : 26859572     DOI : 10.12928
Core Subject : Engineering,
Electrical & Electronics Engineering
Buletin Ilmiah Sarjana Teknik Elektro (BISTE) adalah jurnal terbuka dan merupakan jurnal nasional yang dikelola oleh Program Studi Teknik Elektro, Fakultas Teknologi Industri, Universitas Ahmad Dahlan. BISTE merupakan Jurnal yang diperuntukkan untuk mahasiswa sarjana Teknik Elektro. Ruang lingkup yang diterima adalah bidang teknik elektro dengan konsentrasi Otomasi Industri meliputi Internet of Things (IoT), PLC, Scada, DCS, Sistem Kendali, Robotika, Kecerdasan Buatan, Pengolahan Sinyal, Pengolahan Citra, Mikrokontroller, Sistem Embedded, Sistem Tenaga Listrik, dan Power Elektronik. Jurnal ini bertujuan untuk menerbitkan penelitian mahasiswa dan berkontribusi dalam pengembangan ilmu pengetahuan dan teknologi.
Arjuna Subject : -
Articles 13 Documents
 1   2 
Search results for , issue "Vol. 5 No. 2 (2023): June" : 13 Documents clear
Industrial Relations Dispute Simulation System Prototype with Artificial Intelligence Approach Naik Henokh Parmenas; Ridha Sefina Samosir
Buletin Ilmiah Sarjana Teknik Elektro Vol. 5 No. 2 (2023): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v5i2.7607

Abstract

There are many cases of industrial relations disputes/IRD every year. IRD cases can be resolved by kinship or mediation to reduce the material burden of all parties, such as case costs other than time and energy. With this background, the researcher proposed developing a system for simulating the IRD judicial process with an AI approach. AI encourages faster and high-accuracy prediction results because AI works through the learning process against a set of training data to produce learning models. The research method used is an experimental laboratory to select AI algorithms with the highest accuracy. Meanwhile, for system development methods, research proposes prototyping methods with designing systems using UML. Prototyping is an option because it takes the intensity of communication between the developer and the end user to determine the prototype of the system being built. System development with platform website. UML provides a variety of diagrams that facilitate communication with developers to illustrate the system being built. System testing uses the black box methodology approach because at this stage, testing is carried out to ensure that the functional system has met the needs. From the experimental results, the decision tree algorithm provides the highest accuracy of 80% in training and testing a set of datasets in the form of cases and IRD court rulings from 2022. The accuracy score means that the learning model by the decision tree algorithm can correctly predict (TP / True positive) 75 % of all cases (test data). The accuracy score is obtained through a confusion matrix that shows the performance of the decision tree algorithm for classification. The results of this research help the process of simulating IRD cases before being taken to judicial line to minimize costs and other efforts that could potentially be incurred during judicial process.
PCB (Printed Circuit Board) Etching Machine Using ESP32-Camera Based Internet of Things Adi Prasetyo; Jamaaluddin Jamaaluddin; Izza Anshory
Buletin Ilmiah Sarjana Teknik Elektro Vol. 5 No. 2 (2023): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v5i2.8132

Abstract

The most important factor in the PCB etching process is timeliness and minimizing work on users. Because in general, the PCB etching process itself is still done manually and there is no timeliness and good results. So, the PCB etching machine tool using Internet of Things based Esp32-Cam is made for users in the PCB etching process. Users can monitor the etching process of the internet of things system using telegram. In the telegram there is a choice of time to carry out the etching process. The components used in this tool power supply as a power source in this tool uses a voltage of 5vdc, Esp32-Cam as a microcontroller, camera features on Esp32-Cam as a photo sender after the etching process time has been completed, RTC (Real Time Clock) as a timer for the PCB etching process, servo motor as a box drive containing water and PCB when the etching process time is selected. The conclusion of the results of this tool is that the device or tool works well and can help users on the PCB etching process efficiently, it's just that there are few challenges for the signal network due to delays in bad internet signals.
Quadrotor Altitude Control using Recurrent Neural Network PID Faisal Fajri Rahani; Phisca Aditya Rosyady
Buletin Ilmiah Sarjana Teknik Elektro Vol. 5 No. 2 (2023): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v5i2.8455

Abstract

The quadrotor is one type of Unmanned Aerial Vehicle (UAV) or unmanned flying vehicle. Quadrotor can be operated by a remote controller or autonomously. Quadrotor control is a challenging problem because it takes into account complex things such as parametric uncertainty, external disturbances, and so on. At the spatial level, three linear degrees of freedom along three axes and three degrees of freedom rotating along three axes are used for the control of a quadrotor. Conventional controls for quadrotors are widely used such as PID, state feedback, and so on. However, because the control is linear, non-linear control has begun to be developed. Some of these controls, for example, use a sliding mode control system, fuzzy methods, and controls by combining linear control with artificial intelligence. This paper will use PID control and an artificial neural network for the quadrotor direction control system. The results of this control test indicate that the combination of PID and RNN on the directional control shows a better response than conventional PID.

Page 2 of 2 | Total Record : 13

 1   2 

Filter by Year

2023 2023


Reset
Filter By Issues
All Issue Vol. 8 No. 1 (2026): February Vol. 7 No. 4 (2025): December Vol. 7 No. 3 (2025): September Vol. 7 No. 2 (2025): June Vol. 7 No. 1 (2025): March Vol. 6 No. 4 (2024): December Vol. 6 No. 3 (2024): September Vol. 6 No. 2 (2024): June Vol. 6 No. 1 (2024): March Vol. 5 No. 4 (2023): December Vol. 5 No. 3 (2023): September Vol. 5 No. 2 (2023): June Vol. 5 No. 1 (2023): March Vol. 4 No. 3 (2022): December Vol. 4 No. 2 (2022): Agustus Vol. 4 No. 1 (2022): April Vol. 3 No. 3 (2021): Desember Vol 3, No 2 (2021): Agustus Vol. 3 No. 2 (2021): Agustus Vol. 3 No. 1 (2021): April Vol 3, No 1 (2021): April Vol. 2 No. 3 (2020): Desember Vol 2, No 3 (2020): Desember Vol 2, No 2 (2020): Agustus Vol. 2 No. 2 (2020): Agustus Vol 2, No 1 (2020): April Vol. 2 No. 1 (2020): April Vol 1, No 3 (2019): Desember Vol. 1 No. 3 (2019): Desember Vol 1, No 2 (2019): Agustus Vol. 1 No. 2 (2019): Agustus Vol 1, No 1 (2019): April Vol. 1 No. 1 (2019): April More Issue