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All Journal Jurnal Penelitian Fisika dan Aplikasinya (JPFA) JURNAL ILMIAH PENDIDIKAN FISIKA AL BIRUNI Jurnal Fisika FLUX Jurnal Pengembangan Rekayasa dan Teknologi Elektrika Jurnal Ilmu Fisika Indonesian Physical Review Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming CITIZEN: Jurnal Ilmiah Mulitidisiplin Indonesia Prisma Sains: Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram International Journal on Advanced Technology, Engineering, and Information System (IJATEIS) Electrician : Jurnal Rekayasa dan Teknologi Elektro AMPLITUDO: Journal of Science & Technology Innovation
Supari Supari, Supari
Magister Teknik Elektro, Fakultas Teknologi Industri Universitas Islam Sultan Agung Jl. Raya Kaligawe Km. 4 Semarang 50012
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MORLET’S WAVELET ANALYSIS ON EL NIÑO SOUTHERN OSCILLATION (ENSO) AND THE INDIAN OCEAN DIPOLE (IOD) FOR 84 YEARS: 1940-2023 Suhadi, Suhadi; Putri, Jamiatul Khairunnisa; Iskandar, Iskhaq; Supari, Supari; Irfan, Muhammad; Ariska, Melly; Akhsan, Hamdi
Indonesian Physical Review Vol. 7 No. 3 (2024)
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/ipr.v7i3.363

Abstract

As is known, the impact caused by El Niño Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) can reach extreme levels, especially rainfall in Indonesia. So, updating information on events and cycles of these phenomena is essential. Using Sea Surface Temperature (SST) data spanning the previous 84 years (1940–2023) from ERA5, we examined Sea Surface Temperature Anomalies (SSTA), which serve as a predictive tool for ENSO and IOD events. Apart from that, in this research, SSTA variance analysis was also carried out using Wavelet. The analysis results show several Positive IOD-Like events (1943, 1944, 1977, 1996) and Negative IOD-Like (1985, 1992, 2016). Apart from that, the results of this research also show that El Niño in 2002/03 coincided with Negative IOD in 2002. The results of Wavelet analysis show that the SSTA DMI variance experienced increased activity in the periods 1940-1968, 1969-1991, and 1992-2023. The Wavelet analysis also shows that ENSO activity increased in 1970-2000 and decreased again in 2000-2023.
Analisa Mesin Pengering Makanan Food Dehidrator Menggunakan Sensor Thermostat Berbasis Hybrid Pinandita, Satria; Supari, Supari; Saputra, Dian Nova; Al Amin, Anggara Fuad
Electrician : Jurnal Rekayasa dan Teknologi Elektro Vol. 18 No. 1 (2024)
Publisher : Department of Electrical Engineering, Faculty of Engineering, Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/elc.v18n1.2582

Abstract

The process of drying food is done in the traditional way, by drying it in the hot sun, but the traditional drying method makes the food unhygienic. Several factors can influence the drying results of food ingredients, including temperature and drying time. Using optimal drying temperatures and times can reduce the level of damage caused by the drying process. This research aims to obtain an analysis of a food dehydrator drying machine using a hybrid-based thermostat sensor that can optimally condition the temperature and time factors in the drying process, the hyfood dehydrator machine system uses a dehumidification method, there is a heat recovery mechanism that recycles heat to open new air, thus saving 60-70% of fresh air preheating energy consumption. Hot air moving in the room dries the material. It is known that the test result data was analyzed by calculating the accuracy values, down to the relative distance values. The results of the comparison process are used as validation of the output values ??produced by the temperature measuring instrument. The measurement results of the Digital Thermostat Sensor are in accordance with the datasheet and have a high level of accuracy. So the Digital Thermostat Sensor measuring instrument can be used as a measurement tool. With an internal fan, thermostat, and time settings on this device, you only need to set the right heat according to the type of food you want to dry. The shelves in the cupboard consist of drying trays that can maximize the drying process
SIMULASI PENGATURAN KECEPATAN MOTOR INDUKSI 3 PHASA DENGAN DIRECT TORQUE CONTROL MENGGUNAKAN MATLAB Khasanah, Ulfatun; Supari, Supari; Heranurweni, Sri
Elektrika Vol. 9 No. 1 (2017): April 2017
Publisher : Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (864.46 KB) | DOI: 10.26623/elektrika.v9i1.1109

Abstract

Induction motors are widely used in the industrial world because they have many advantages, including construction that is very simple and strong, cheap, has high efficiency, quite good power factor, and maintenance is easier. Besides the advantages of induction motors also have weaknesses, one of the disadvantages of an induction motor is not being able to maintain its speed constantly if there is a change in load. If there is a change in load, the speed of the induction motor will decrease. One method of regulating the speed of an induction motor developed in addition to vector control is the Direct Torque Control (DTC) method. The DTC control technique allows direct and separate flux and torque settings and can be done without using a speed sensor. The estimated rotor rotation, torque and flux is carried out by the DTC which is inputted with stator voltage and current. To achieve the desired flux and torque estimation is used as feedback on the control system. In this final assignment, the speed regulation of the induction motor will be simulated using the DTC method using Matlab. The results obtained through the simulation show the length of time to reach the reference speed for speeds of 500rpm and 1000 rpm is around 0.5 seconds. Keywords : Induction motor, Direct Torque Control, Matlab.
DESAIN GENERATOR OZONE DENGAN TEKNOLOGI PLASMA DBD (Die-lectric Barrier Discharge) Aryadi, Ricky; Supari, Supari; Harmini, Harmini
Elektrika Vol. 11 No. 1 (2019): April 2019
Publisher : Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (911.057 KB) | DOI: 10.26623/elektrika.v11i1.1535

Abstract

Industrial sterilization is a very important problem. Ozone is a powerful oxidizer that can function for sterilization and is environmentally friendly. Plasma DBD (Dielectric Barrier Discharge) is one of the effective technologies to obtain ozone. The ozone generator currently uses a lot of manual control operations. Manual control uses a mechanical system in the form of a potentiometer to calibrate the frequency and output of the ozone generator output, so that digitization and automation are needed to operate to replace human labor. The design of the digital ozone control generator is done using an AVR microcontroller. Programming used in this research is basic language (BASCOM), then uses a DAC (Digital to Analog Converter) system which is the output of a Microcontroller with a Weighted Binnary Resistor. The output of the microcontroller is frequency and 8 bit digital with a decimal parameter of 200. The result of automation is that the timer works for 2 hours. The greater frequency the ozone produced. At a frequency of 1500Hz the power produced is 308.58 watts with an ozone concentration of 59 ppm. Efficiency using a switching system> 90%.                                                                                                                                                                                                  Keywords: Plasma, AVR Microcontroller, Ozone.
Outlier Identification Techniques in Daily Rainfall Data Sudirman, Sudirman; Irfan, Muhammad; Supari, Supari; Musta, Baba; Dzakiya, Nurul
AMPLITUDO : Journal of Science and Technology Innovation Vol. 5 No. 1 (2026): February
Publisher : Balai Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56566/amplitudo.v5i1.554

Abstract

A quality test was conducted on daily rainfall data in the Sumatra region to select good data. The data used came from 19 observation stations belonging to the Meteorology, Climatology, and Geophysics Agency (BMKG) spread across the Aceh-Lampung provinces from early 1985 to late 2023. The quality test aims to ensure data reliability, consistency, and validity. Daily rainfall data often face issues such as missing data, unrealistic extreme values, and recording discrepancies, which can reduce the accuracy of climate analysis. The quality test examined data completeness and outliers using the interquartile range. The quality test results showed a data completeness level of 93%, thus declaring the data valid. Outliers were identified in small amounts (<1%) for very high rainfall intensity at the Minangkabau meteorological station in West Sumatra (470 mm/day), the Bengkulu climatological station (400 mm/day), the FL Tobing meteorological station in North Sumatra (430 mm/day), the Fatmawati Soekarno meteorological station in Bengkulu (390 mm/day), the West Sumatra climatological station (320 mm/day), the South Sumatra climatological station (230 mm/day), and the Radin Intan II meteorological station in Lampung (265 mm/day). These values ​​were not removed from the analysis because they passed the data quality test and represented meteorologically realistic extreme rainfall events. The results of the evaluation of daily rainfall data in Sumatra during the study were representative and reliable enough to be used in further climatological analysis.
Prediction of Tropical Cyclone Trajectory and Intensity Using a Particle Motion Based Machine Learning Framework in the Southern Indian Samiaji, Budi Iman; Yulkifli, Yulkifli; Yohandri, Yohandri; Yendri Sudiar, Nofi; Supari, Supari
Prisma Sains : Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram Vol. 14 No. 2: April 2026
Publisher : Universitas Pendidikan Mandalika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/j-ps.v14i2.19982

Abstract

Tropical cyclones in the Southern Indian Ocean pose severe threats to coastal infrastructure and socio-economic stability, yet predicting their recurving trajectories and intensity remains a significant meteorological challenge. This study evaluates the performance of a particle-motion-based machine learning framework, utilizing the Trackpy library, to forecast cyclone behavior. Leveraging historical data from 2018 to 2025 (JTWC and IBTrACS), the model treats cyclones as physical particles with temporal inertia, employing a multi-lag feature to capture movement momentum. Evaluation using a dataset of 115 cyclones (78:22 train/test ratio) reveals that the Trackpy framework achieves high spatial precision, with Mean Squared Error (MSE) values of 0.1728 for latitude (±33.3 km) and 1.0250 for longitude (±53.2 km). While the intensity prediction yielded a higher MSE of 47.7544 (approximately 6.9-knot deviation), the model successfully captured major strengthening and weakening phases across prominent cyclones, including TC Wallace and TC Neville. These findings demonstrate that integrating temporal inertia is highly effective for maintaining trajectory consistency, establishing Trackpy as a robust architectural foundation for operational forecasting. Further optimization via hybrid models and additional meteorological variables is recommended to enhance intensity accuracy.
Co-Authors Al Amin, Anggara Fuad Andi Kurniawan Nugroho Ardina, Elfira Nureza Aryadi, Ricky Dzakiya, Nurul Erlinasari, Erlinasari Hamdi Akhsan Harmini, Harmini Iskhaq Iskandar Khasanah, Ulfatun Melly Ariska Muhammad Irfan Musta, Baba Nurma Gupita Dewi Putri, Jamiatul Khairunnisa Putriyani, Fena Siska Salat, Roy Samiaji, Budi Iman Saputra, Dian Nova Satria Pinandita Sianipar, Niko Ardiansa Sri Heranurweni Sudirman Sudirman Suhadi Suhadi Suhanda, Alfin Titik Nurhayati Wibawa, Tio Anta Yendri Sudiar, Nofi Yohandri Bow Yulkifli Yulkifli