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All Journal Buletin Ilmiah Sarjana Teknik Elektro INAJEEE (Indonesian Journal of Electrical and Electronics Engineering) Jurnal Pemberdayaan Masyarakat
Nurdiansyah, Aristyawan Putra
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Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Social Sciences

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SERIAL PERIPHERAL INTERFACE (SPI) COMMUNICATION APPLICATION AS OUTPUT PIN EXPANSION IN ARDUINO UNO Baskoro, Farid; Rohman, Miftahur; Nurdiansyah, Aristyawan Putra
INAJEEE (Indonesian Journal of Electrical and Electronics Engineering) Vol 3, No 2 (2020)
Publisher : Jurusan Teknik Elektro Fakultas Teknik UNESA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/inajeee.v3n2.p63-69

Abstract

Serial Peripheral Interface (SPI) is a synchronous serial communication whose data or signal transmission involves Chip Select (CS) or Slave Select (SS) pins, Serial Clock (SCK), Master Out Slave In (MOSI), and Master In Slave Out (MISO). In the Arduino Uno, there are four pins that allow Arduino Uno to perform SPI communication. In this research, SPI communication is implemented to expand the output of the Arduino Uno by using the features of the MCP23S17 IC so that the Arduino Uno, which initially has 20 output pins, can expand to 36 output pins.The results of the research show that the Arduino Uno manages to control 36 output pins. 16 output pins from the MCP23S17, 16 output pins from the Arduino Uno, and 4 pins are used for the SPI communication line. The results of this study also show the form of the SPI communication signal from Arduino Uno in declaring 21 registers on MCP23S17, declaring the MCP23S17 pin register as output, and implementing the output using LEDs.
Mediator of Technology Competence and Solar Panel Module on Satisfaction, Motivation, and Self-Regulated Learning Baskoro, Farid; Agung, Achmad Imam; Achmad, Fendi; Firmansyah, Rifqi; Nurdiansyah, Aristyawan Putra; Putro, Wahyu Sasongko
Jurnal Pemberdayaan Masyarakat Vol 4, No 4 (2025)
Publisher : Yayasan Keluarga Guru Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46843/jpm.v4i4.579

Abstract

The development of digital technology requires higher vocational education, particularly in engineering, to emphasize practical competency and independent learning. This study aims to analyze active engagement as a mediator in the relationship between technological competency and practical modules on learning satisfaction, motivation, and self-regulated learning. The study used a quantitative-correlation approach with the Structural Equation Modeling–Partial Least Squares (SEM-PLS) analysis technique on 80 electrical engineering students, Surabaya State University (Unesa) who were selected using purposive sampling. The results showed that technological competence had a significant effect on active involvement (? = 0.291; p 0.01) and motivation (? = 0.276; p 0.05). The practical module has a significant effect on learning satisfaction, active engagement is the most potent factor influencing learning satisfaction, motivation, and self-regulated learning. Active engagement as a crucial mediating mechanism within the technology-enhanced learning framework is related to engagement-driven learning through collaborative projects, problem-based learning, and digital simulations. These findings are relevant to contributing to the digital transformation of vocational education and the needs of the renewable energy industry.
K-Nearest Neighbors for Smart Solution Transportation: Prediction Distance Travel and Optimization of Fuel Usage and Charging Recommendations for ICE Vehicles Based in Surabaya Baskoro, Farid; Aribowo, Widi; Shehadeh, Hisham; Zangana, Hewa Majeed; Putro, Wahyu Sasongko; Dwiyanti, Sri; Nurdiansyah, Aristyawan Putra
Buletin Ilmiah Sarjana Teknik Elektro Vol. 8 No. 2 (2026): April
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v8i2.15068

Abstract

Surabaya ranks 9th in Southeast Asia and 44th globally in the TomTom Traffic Index, with an average travel time of ±22 minutes for a 10 km distance, longer than Jakarta’s ±20 minutes. Given these traffic conditions, this study examines the application of the K-Nearest Neighbors (KNN) algorithm to predict vehicle travel distance based on remaining fuel consumption and provides recommendations for the nearest Gas Station (SPBU) based on the predicted distance. The study seeks to provide accurate distance predictions and recommend the nearest Gas Station (SPBU) for users based on fuel consumption and the predicted route, helping to navigate Surabaya’s congested traffic efficiently. The data used includes various levels of fuel consumption: 0.02, 0.06, 0.10, 0.14, 0.16, 0.20, and 0.24 liters for engines of 110, 125, and 150 cc. The model evaluation results, using three metrics: MAE, MAPE, and RMSE show that KNN performs excellently at low fuel consumption levels. At a consumption rate of 0.02 liters, the model produces a low MAE of 0.347, MAPE of 31.21%, and RMSE of 0.40, indicating minimal prediction error. The model's performance remains consistent at a consumption of 0.06 liters with MAE of 0.330, MAPE of 9.90%, and RMSE of 0.41, demonstrating a high level of accuracy. Technically, the implementation of this model can help reduce traffic congestion by directing vehicles to the nearest gas stations, thereby minimizing sudden stops on the road, improving traffic flow, and reduce wasted time spent searching for distant gas stations.
Co-Authors Achmad Imam Agung Achmad, Fendi Farid Baskoro Putro, Wahyu Sasongko Raden Mohamad Herdian Bhakti Rifqi Firmansyah Shehadeh, Hisham Sri Dwiyanti Widi Aribowo Zangana, Hewa Majeed