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I Gede Dyana Arjana, I Gede
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Computer Science & IT Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering

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EVALUASI UNJUK KERJA IOT, SISTEM KONTROL DAN MONITORING SUHU DAN KELEMBAPAN PADA RUANG FREEZER MENGGUNAKAN APLIKASI BLYNK (STUDI KASUS PADA PT. AEROFOOD ACS DENPASAR) Krisna Mahendra, Made; Dyana Arjana, I Gede; Suartika, I Made
Jurnal SPEKTRUM Vol 10 No 4 (2023): Jurnal SPEKTRUM
Publisher : Program Studi Teknik Elektro UNUD

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/SPEKTRUM.2023.v10.i04.p14

Abstract

The implementation of temperature control and monitoring system in the freezer room at PT Aero Food ACS company plays a crucial role in maintaining the quality of stored food raw materials. Therefore, an appropriate and efficient control system is required to preserve the quality of stored meat. To address this, a system was developed using IoT-based Blynk application for control and monitoring, utilizing WEMOS as the microcontroller and DHT22 as the sensor. Before the system is deployed in the company, a performance test and evaluation are necessary to ensure that the system functions correctly and complies with the company's SOP. During the testing phase, the control system operated well and was in accordance with the company's SOP.
EARLY WARNING SYSTEM PELEPASAN BEBAN PADA PENYIMPANAN ENERGI GEDUNG DH TEKNIK ELEKTRO Padwita Darma, I Made Angga; Dyana Arjana, I Gede; Setiawan, Widyadi
Jurnal SPEKTRUM Vol 11 No 2 (2024): Jurnal SPEKTRUM
Publisher : Program Studi Teknik Elektro UNUD

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Abstract

The aim of this research is to produce a prototype of an Early Warning System (EWS) for load shedding in energy storage based on ESP32. The load shedding system functions as a load manager to ensure that VIP load classes can be supplied for a longer duration. This load shedding system uses a control system from ATmega 328. The load shedding system utilizes the voltage level read on the battery, allowing it to classify loads according to their importance levels. The load classes are divided into four levels: VIP load class, first-class load, second-class load, and third-class load. The Early Warning System (EWS) is used to provide notifications stored on the battery. ATmega 328 will send battery voltage data to ESP32, which will then be sent through the Telegram application. The performance of the EWS in the load shedding system is reviewed in terms of its effectiveness. The object of this research is the automatic sending of load shedding warnings. Data on battery percentage was taken 20 times. When the battery voltage is 5% above the load class cutoff percentage, ATmega328 will send battery voltage data to ESP32. In the experimental results, it was found that when the percentages show 80%, 75%, 55%, 50%, 30%, 25%, and 5%, the EWS works by sending messages to users about which load class will soon be cut off.
AKURASI PERAMALAN BEBAN LISTRIK SEKTOR RUMAH TANGGA MENGGUNAKAN ARTIFICIAL NEURAL NETWORK DI KOTA PALANGKA RAYA Mahendra Penyarikan, I Gede; Dyana Arjana, I Gede; Arta wijaya, I Wayan
Jurnal SPEKTRUM Vol 11 No 1 (2024): Jurnal SPEKTRUM
Publisher : Program Studi Teknik Elektro UNUD

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/SPEKTRUM.2024.v11.i01.p2

Abstract

Electrical energy is one of the most important energies in the daily life of the people of Palangkaraya, both in business, social, government and household sects. Planning electrical energy in its needs is needed to avoid an energy crisis, because economic growth in the Palangkaraya City area requires electrical energy in its operations. The planning carried out in the study by predicting electricity demand used the ANN (Artificial Neural Network) method. ANN is used at the prediction stage within the scope of the household sector. JST results have good forecasting accuracy with MAPE (Mean Absolute Percentage Error) of 7.1975%. With an absolute error value occurred at Rates of R.2/3,500VA to 5,500VA in July amounting to 32.2728%.
ANALISA KENAIKAN BEBAN LISTRIK SEKTOR RUMAH TANGGA TERHADAP BEBAN PUNCAK DI KOTA PALANGKA RAYA Septiana, Gebi; Dyana Arjana, I Gede; Arta Wijaya, I Wayan
Jurnal SPEKTRUM Vol 11 No 1 (2024): Jurnal SPEKTRUM
Publisher : Program Studi Teknik Elektro UNUD

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/SPEKTRUM.2024.v11.i01.p25

Abstract

Electricity is an essential need in the life of Palangka Raya City, and it can be utilized across various sectors such as business, social, industrial, governmental, and household. The increase in population growth in Palangka Raya City has led to a rise in the demand for electricity, necessitating its regulation and efficient distribution to customers. Specifically in the electricity sector, particularly in households, the demand tends to fluctuate due to resistive, inductive, and capacitive loads. This study aims to analyze the load factor, which is the ratio of average load to peak load measured over certain periods such as daily, monthly, or yearly. The first step involves data collection in the household sector of Palangka Raya City, including tariff data and monthly consumption data. The second step involves classifying electrical loads followed by an analysis of load factor accumulation. The third step involves summarizing the results of the accumulation data. From the analysis, it is concluded that the highest load factor values are found in the R.1/450 VA category, with an average of 49.30%, and the highest power factor value is 83.16% compared to other load factor categories. However, tariffs for R.3/6,600 VA and above show a gradual decrease in load factor from February to December.
Co-Authors I Made Suartika I Wayan Arta Wijaya Krisna Mahendra, Made Mahendra Penyarikan, I Gede Padwita Darma, I Made Angga Septiana, Gebi Widyadi Setiawan