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All Journal JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer Dinasti International Journal of Education Management and Social Science JAREE (Journal on Advanced Research in Electrical Engineering) Sewagati
Endroyono Endroyono
Jurusan Teknik Elektro Institut Teknologi Sepuluh Nopember
Arts Humanities Computer Science & IT Control & Systems Engineering Dentistry Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Public Health Social Sciences Other

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PREDICT URBAN AIR POLLUTION IN SURABAYA USING RECURRENT NEURAL NETWORK – LONG SHORT TERM MEMORY Faishol, Muh. Anas; Endroyono, Endroyono; Irfansyah, Astria Nur
JUTI: Jurnal Ilmiah Teknologi Informasi Vol. 18, No. 2, July 2020
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v18i2.a988

Abstract

Air is one of the primary needs of living things. If the condition of air is polluted, then the lives of humans and other living things will be disrupted. So it is needed to perform special handling to maintain air quality. One way to facilitate the prevention of air pollution is to make air pollutionforecasting by utilizing past data. Through the Environmental Office, the Surabaya City Government has monitored air quality in Surabaya every 30 minutes for various air quality parameters including CO, NO, NO2, NOx, PM10, SO2 and meteorological data such as wind direction, wind direction, wind speed, wind speed, global radiation, humidity, and air temperature. These data are very useful to build a prediction model for the forecast of air pollution in the future. With the large amount and variance of data generated from monitoring air quality in Surabaya city, a qualified algorithm is needed to process it. One algorithm that can be used is Recurrent Neural Network - Long Short Term Memory (RNN-LSTM). RNN-LSTM is built for sequential data processing such as time-series data. In this study, several analyses are performed. There are trend analysis, correlation analysis of pollutant values to meteorological data, and predictions of carbon monoxide pollutants using the Recurrent Neural Network - LSTM in the city of Surabaya correlated with meteorological data. The results of this study indicate that the best prediction model using RNN-LSTM with RMSE calculation gets an error of 1,880 with the number of hidden layer 2 and epoch 50 scenarios. The predicted results built can be used as a reference in determining the policy of the city government to deal with air pollution going forward.
Implementasi Jaringan Internet Desa untuk Mendukung Transformasi Digital di Kantor Desa Sedaeng, Kecamatan Tosari, Kabupaten Pasuruan Mukti, Prasetiyono Hari; Affandi, Achmad; Setijadi, Eko; Kusrahardjo, Gatot; Boedinoegroho, Hany; Rahayu, Sri; Wirawan, Wirawan; Hendrantoro, Gamantyo; Endroyono, Endroyono; Widjiati, Endang; Firmansyah, Mohammad Rifqi
Sewagati Vol 9 No 2 (2025)
Publisher : Pusat Publikasi ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j26139960.v9i2.2416

Abstract

Keterbatasan akses internet di Desa Sedang, Kabupaten Pasuruan, yang menghambat masyarakat dalam mengakses informasi dan layanan digital yang semakin penting di era modern. Kondisi ini menciptakan kesenjangan digital yang berdampak pada peluang ekonomi, pendidikan, dan komunikasi masyarakat desa. Implementasi jaringan internet menjadi solusi untuk meningkatkan konektivitas dan mendukung perkembangan sosial ekonomi masyarakat setempat. Metode implementasi melibatkan pemasangan dua antena Mikrotik, yaitu antena transmitter dan receiver, untuk membangun jaringan internet yang dapat menjangkau masyarakat dengan biaya yang lebih terjangkau. Pengabdian ini mencakup proses perencanaan, instalasi, dan pengujian jaringan untuk memastikan kinerjanya sesuai dengan kebutuhan warga. Hasil menunjukkan bahwa jaringan internet desa yang diimplementasikan mampu meningkatkan konektivitas di wilayah tersebut, mempermudah akses masyarakat terhadap layanan digital, serta membuka peluang baru untuk pendidikan, bisnis, dan komunikasi. Kesimpulan dari pengabdian ini menegaskan bahwa implementasi jaringan internet desa dapat menjadi solusi efektif untuk mengatasi kesenjangan digital di daerah pedesaan dan mendukung perkembangan sosial ekonomi masyarakat setempat.
Optimizing Cost and Performance of Cloud versus on Premises in Digital Wallet Start up Kurniawan, Dion; Endroyono, Endroyono
Dinasti International Journal of Education Management And Social Science Vol. 5 No. 4 (2024): Dinasti International Journal of Education Management and Social Science (April
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dijemss.v5i4.2568

Abstract

In the context of the rapid growth of the fintech industry in Indonesia, the study explores the choice of IT infrastructure in particular between on premise and cloud in digital wallet fintech start-ups to improve cost efficiency. With a lack of detailed information in the literature about the critical role of infrastructure in the development of fintech, the study uses Mixed Methods The Convergent Parallel Design to provide in-depth insights into the impact of infrastructural decisions on operational and financial efficiency. The findings show that the adoption of cloud infrastructure, chosen for its scalability, flexibility, and cost efficiency, is significant in reducing operating and maintenance costs, while strengthening market positions. However, the decision also calls for serious consideration of security aspects, data privacy, and regulatory compliance. The findings provide important contributions for policymakers, regulators, and industry stakeholders in understanding the importance of data security strategies and company-specific needs in selecting IT infrastructures. In conclusion, choosing the right IT infrastructure is key to reducing costs and supporting sustainable growth in the fintech sector, especially for digital wallet start-ups.
Shift Share Location Quotient, and ARIMA Forecasting Methods in the Analysis of the Competitiveness of Tual City and the Economic Growth of the Maluku Province. La Adisamu, Nova prista; Endroyono, Endroyono; Nugroho, Sumpeno Mardi Susiki
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 6, No 1 (2022): April
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v6i1.237

Abstract

 Abstract— Economic development and high competitiveness are significant factors in a region’s success, especially since the enactment of Law Number 32 of 2004 on Regional Government, which converted the centralized to a decentralized system. This study analyzes the GRDP data of Tual City and Maluku Province using the shift share method and the Location Quotient method, resulting in a shift share assessment of Tual City’s regional competitiveness. It can be seen that the economic state of Tual City is still influenced by the Maluku Province’s economic growth of 593,688 with an overall slowdown in Proportional Shift of (-633.686) and an differential shift of (-5,756.040) during 9 years. The ARIMA forecasting method was then used to project the province’s 5th-year economic growth of 8,486,707 (billions) in the 5th period.
Peramalan Pencemaran Udara Di Kota Surabaya Menggunakan Metode DSARIMA dengan Pendekatan Percentile Error Bootstrap (PEB) Koesoemaningroem, Novi; Endroyono, Endroyono; Nugroho, Supeno Mardi Susiki
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 5: Oktober 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2021855216

Abstract

Peramalan pencemaran udara yang  akurat  diperlukan untuk mengurangi dampak pencemaran udara. Peramalan yang belum akurat akan berdampak kurang efektifnya tindakan yang dilakukan untuk mengantisipasi dampak pencemaran udara. Sehingga diperlukan sebuah pendekatan yang dapat mengetahui keakuratan plot data hasil peramalan. Penelitian ini dilakukan dengan tujuan melakukan peramalan pencemaran udara berdasarkan parameter PM10, NO2, CO, SO2, dan O3dengan metode DSARIMA. Data dalam penelitian ini sebanyak 8.760 data yang berasal dari Dinas Lingkungan Hidup Kota Surabaya. Berdasarkan hasil peramalan selama 168 jam kadar parameter PM10, NO2, SO2 dan O3 cenderung  menurun. Hasil peramalan selama 168 jam dengan menggunakan DSARIMA memberikan hasil peramalan yang nilainya mendekati data aktual terbukti dari polanya yang sesuai atau mirip dengan grafik plot data aktual dengan hasil ramalan. Dengan pendekatan PEB, selisih antara data aktual dan data ramalan kecil dan plot grafik PEB mengikuti plot grafik di data aktual, sehingga dapat dikatakan bahwa model sudah sesuai. Hasil akurasi terbaik yang dihasilkan adalah model DSARIMA dengan RMSE terkecil 0,59 didapatkan dari parameter CO yaitu ARIMA(0,1,[1,2,3])(0,1,1)24(0,1,1)168. AbstractAccurate air pollution forecasting is needed to reduce the impact of air pollution. Inaccurate forecasting will result in less effective actions taken to anticipate the impact of air pollution. So we need an approach that can determine the accuracy of the forecast data plot. This research was conducted with the aim of forecasting air pollution based on the PM10, NO2, CO, SO2, and O3 parameters using the DSARIMA method. The data in this study were 8.760 data from the Surabaya City Environmental Service. Based on the results of forecasting for 168 hours, the levels of PM10, NO2, SO2, and O3 parameters tend to decrease. Forecasting results for 168 hours using DSARIMA provide forecasting results whose values are close to the actual data as evidenced by the pattern that matches or is similar to the actual data plot graph with the forecast results. With the PEB approach, the difference between the actual data and the forecast data is small and the PEB graph plot follows the graph plot in the actual data, so it can be said that the model is appropriate. The best accuracy result is DSARIMA with the smallest RMSE 0,59 obtained from the CO parameter, namely ARIMA(0,1,[1,2,3])(0,1,1)24(0,1,1)168.  
Co-Authors Achmad Affandi Boedinoegroho, Hany Endang Widjiati Faishol, Muh. Anas Firmansyah, Mohammad Rifqi Gamantyo Hendrantoro Gatot Kusrahardjo Irfansyah, Astria Nur Koesoemaningroem, Novi Kurniawan, Dion La Adisamu, Nova prista Nugroho, Sumpeno Mardi Susiki Prasetiyono Hari Mukti Setijadi, Eko SRI RAHAYU Supeno Mardi Susiki Nugroho, Supeno Mardi Wirawan Wirawan