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Journal of Educational Engineering and Environment
Published by Universitas PGRI Banyuwangi
ISSN : -     EISSN : 30257956     DOI : https://doi.org/10.36526/jeee.v1i1
Core Subject : Engineering,
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mechanical Engineering
Journal of Educational Engineering and Environment is a periodical journal published twice a year in the month May and December which contains various articles in the form of research, systematic reviews, and case reports with a focus on industrial engineering, mechanical engineering, electrical engineering, environmental engineering, civil engineering, and engineering education as well as related topics.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 44 Documents
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Prototype Phase Failure Detection Berbasis Internet Of Things (IoT) Arif Dwi Wahyudi; Charis Fathul Hadi; Ratna Mustika Yasi
Journal of Educational Engineering and Environment Vol. 4 No. 2 (2025): Journal of Educational Engineering and Environment
Publisher : Fakultas Teknik Universitas PGRI Banyuwangi

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

Abstract

The three-phase system is applied to the electricity network supplied by PLN, starting from the generator to the low voltage network (JTR) in front of people's homes. The PLN network uses three-phase lines (R, S, T) and neutral (N), or often called ground. According to the term three-phase power, it consists of three live cables and one neutral cable. Usually three-phase power supplies have a voltage of 380 volts and are widely used in industry and factories. Previous research to detect Phase failure still used conventional methods so it was difficult to control. This once happened at a hospital where the researcher worked, which experienced damage to a 3 Phase electric motor and a 3 Phase submersible water pump due to the failure of one of the Phases of the electrical network without being recognized and controlled by the Phase failure system. Currently, much of the technology used in equipment is operated manually, so the efficiency in terms of time, energy and accuracy is not optimal. This research carried out the design and development of a prototype Phase Failure Detection system which, when applied, can function as a safety measure, can monitor or monitor in real time, and can also remotely control the function of a 3 Phase electrical network using an Android system based on the Internet of Things. . The Phase Failure Detection working system is that if there is a phase imbalance (R, S, T) that exceeds the value set by the software, it will provide information via LCD, LED indicator and buzzer (alarm). NodeMCU ESP8266 in real-time. The voltage measurement value on the LCD (Contactor input voltage) is close to the voltage value measured using the AVOmeter. From the results of the research, 8 measurements were carried out in each phase, including a voltage of 220V - 196V in each phase R, S, T, and showed a maximum voltage error value for each phase of 0.50%, namely at a phase voltage of 199 volts. The voltage value shown by the AVOmeter is relatively the same as the voltage value shown by the LCD, so it can be concluded that the research results in the form of a prototype of this tool have a high level of accuracy because the percentage value of the allowable deviation coefficient between phases (10% of the nominal voltage of 220 volts) not exceeded [1], and when there is a deviationin the voltage value between Phases that exceeds 10%, the device automatically cuts off the flow of each Phase
Sistem Pengeringan Buah Kopi Robusta Gombengsari Dengan Metode Hot Air Drying Berbasis IoT Aryo Pamungkas; Charis Fathul Hadi; Widhi Winata Sakti
Journal of Educational Engineering and Environment Vol. 5 No. 1 (2026): Journal of Educational Engineering and Environment
Publisher : Fakultas Teknik Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/jeee.v5i1.8733

Abstract

This study discusses a hot air drying system for Robusta coffee cherries from Gombengsari, addressing issues that disrupt traditional sun-drying processes, such as unpredictable rainfall, vulnerability to pests, and overnight storage that causes reabsorption of moisture in the dried coffee.An experimental method was employed to determine the optimal drying temperature for coffee cherries that preserves their characteristics and flavor profile. Comparative results from the hot air drying system for Robusta coffee cherries showed moisture content reductions of 25.2%, 30.27%, 37.37%, 25.10%, 30%, and 37%. The application of hot air drying influenced the final weight, moisture content levels, and average error rate of 1%. Drying was conducted over 5 hours with initial coffee weights of 300g and 500g, at temperatures starting from 45°C. For 300g batches: 45°C yielded 25.2% moisture content, 55°C yielded 30.27%, and 65°C yielded 37.37%. For 500g batches: 45°C yielded 25.10% moisture content, 55°C yielded 30%, and 65°C yielded 37%. The optimal drying condition was achieved with a 300g batch at 65°C, resulting in 37.37% moisture content reduction and a final weight of 187.9 grams.
Electricity Consumption Forecasting Analysis using Linear Regression Method, DKL 3.2 Method and BaU Scenario Muhammad Zainal Roisul Amin; Ratna Mustika Yasi; Wahyu Setyo Aji; Bambang Sri Kaloko
Journal of Educational Engineering and Environment Vol. 5 No. 1 (2026): Journal of Educational Engineering and Environment
Publisher : Fakultas Teknik Universitas PGRI Banyuwangi

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Abstract

Accurate long-term electricity demand forecasting is essential for ensuring reliable power system planning and sustainable energy development. Previous studies have generally focused on the application of a single forecasting approach, such as linear regression, or a limited comparison between two methods, resulting in insufficient evaluation of forecasting performance across multiple sectors and forecasting models. This research addresses this gap by conducting a comparative analysis of three forecasting approaches Multiple Linear Regression, Electricity Demand List Method 3.2 (DKL 3.2), and Business as Usual (BaU) for projecting electricity consumption in the ULP Kencong service area during the 2025–2029 period. The novelty of this study lies in the integration and comparison of these three forecasting methods within a single framework, combined with the utilization of customer growth, connected power capacity, and Land and Building Tax (PBB) indicators as forecasting variables. Forecasting simulations were performed using LEAP software and Microsoft Excel, while forecasting accuracy was evaluated using the Mean Absolute Percentage Error (MAPE). The results indicate that all sectors are expected to experience continuous growth in electricity consumption, with the industrial sector showing the highest increase. Among the evaluated methods, Multiple Linear Regression demonstrated the best forecasting performance, achieving the lowest MAPE values in three of the four analyzed sectors, namely residential (3.49%), business (6.68%), and social (4.77%) sectors. In contrast, DKL 3.2 produced the highest forecasting errors, particularly in the industrial sector (45.98%), while BaU showed moderate and relatively stable performance. These findings support the claim that Multiple Linear Regression is the most suitable and accurate method for long-term electricity consumption forecasting in the ULP Kencong region, providing a reliable basis for future electricity supply planning and infrastructure development.
The Effect Of Epoxy Resin Ratio And Sugar Cane Bagasse Particle Dimensions On The Effectiveness Of Noise-Reducing Materials Adhi Purna Yulian Putra; Anas Mukhtar; Gatut Rubiono; Muhamad Khoirul Anam; Adi Pratama Putra
Journal of Educational Engineering and Environment Vol. 5 No. 1 (2026): Journal of Educational Engineering and Environment
Publisher : Fakultas Teknik Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/jeee.v5i1.8975

Abstract

: Noise is a sound pollution that has a significant impact on human health and the environment. The use of bagasse waste as a noise dampener is an interesting alternative material source to be developed. This study aims to determine the effect of the ratio of epoxy resin and particle dimensions of bagasse waste on the effectiveness of noise dampening materials. The study was conducted experimentally, where the composite was made using variations in the ratio of epoxy resin to bagasse, namely: 10:40, 10:50, and 10:60 grams. Bagasse particle powder used three different mesh sizes, namely 16, 20, and 30. Testing the sound absorption capacity of the dampening specimen was carried out using a PVC impedance tube with a length of 100 cm and a diameter of 15 cm, the sound source used a frequency of 50 Hz–1000 Hz with the specimen placed at a distance of 50 cm and 75 cm from the sound source. The results showed that the ratio of epoxy resin and particle dimensions of bagasse affected the reduction of noise levels. The increase in the ratio of epoxy resin and bagasse powder is directly proportional to the composite density value, where the highest density value of 0.78 g/cm³ is obtained at a composition of 10:60 grams at a mesh size of 20, while the lowest density is 0.54 g/cm³ at a composition of 10:40 grams mesh 16. The most optimal sound absorption coefficient is achieved at a mixture ratio of 10:60 grams mesh 30 with an effectiveness of 10% at a distance of 50 cm from the noise source.

Page 5 of 5 | Total Record : 44

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