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All Journal Emerging Science Journal Jurnal Penelitian Pendidikan IPA (JPPIPA) Jurnal Teknik Industri : Jurnal Hasil Penelitian dan Karya Ilmiah dalam Bidang Teknik Industri Jurnal Papatung : Jurnal Ilmu Administrasi Publik, Pemerintahan dan Politik Engineering, Mathematics and Computer Science Journal (EMACS) Jurnal Indonesia Sosial Teknologi
Christian Harito
Bina Nusantara University
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Physics Social Sciences

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Journal : Emerging Science Journal

 1 
State of Charge Estimation of Lead Acid Battery using Neural Network for Advanced Renewable Energy Systems Ryo G. Widjaja; Muhammad Asrol; Iwan Agustono; Endang Djuana; Christian Harito; G. N. Elwirehardja; Bens Pardamean; Fergyanto E. Gunawan; Tim Pasang; Derrick Speaks; Eklas Hossain; Arief S. Budiman
Emerging Science Journal Vol 7, No 3 (2023): June
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2023-07-03-02

Abstract

The Solar Dryer Dome (SDD), an independent energy system equipped with Artificial Intelligence to support the drying process, has been developed. However, inaccurate state-of-charge (SOC) predictions in each battery cell resulted in the vulnerability of the battery to over-charging and over-discharging, which accelerated the battery performance degradation. This research aims to develop an accurate neural network model for predicting the SOC of battery-cell level. The model aims to maintain the battery cell balance under dynamic load applications. It is accompanied by a developed dashboard to monitor and provide crucial information for early maintenance of the battery in the SDD. The results show that the neural network estimates the SOC with the lowest MAE of 0.175, followed by the Random Forest and support vector machine methods with MAE of 0.223 and 0.259, respectively. A dashboard was developed to help farmers monitor batteries efficiently. This research contributes to battery-cell level SOC prediction and the dashboard for battery status monitoring. Doi: 10.28991/ESJ-2023-07-03-02 Full Text: PDF
Cost-Effective Manufacturing of Microfluidics Through the Utilization of Direct Ink Writing Prajitna, Stefanus H.; Harito, Christian; Yuliarto, Brian
Emerging Science Journal Vol 9, No 1 (2025): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-01-01

Abstract

Microfluidics is essential for precise manipulation of fluids in small channels. However, conventional manufacturing processes for microfluidic devices are expensive, time-consuming, and require specialized equipment in a clean room. While recent studies have improved the cost-effectiveness of this device, there is still a need for further advancement in cost efficiency. Therefore, this study aimed to develop a custom-built direct-ink writing (DIW) printer for manufacturing microfluidic devices that is more affordable. Custom-built DIW directly printed microfluidic channels onto microscope slide glass using RTV (Room Temperature Vulcanizing) silicone sealant. To finish the microfluidics manufacturing, the printed channel will be assembled by placing the same glass on top of the printed layer. This method eliminated the need for polydimethylsiloxane (PDMS) molds and casting processes that were still found in recent studies. This innovative $250 (USD) custom-built DIW method takes 15 seconds to print microfluidics channels and showed a significant cost reduction, with each microfluidics device costing only $0.071 (USD) compared to $0.90 (USD) in previous studies. This study makes microfluidics more affordable and accessible for biomedical use. Doi: 10.28991/ESJ-2025-09-01-01 Full Text: PDF
Co-Authors Adinda Permata Sari Arief S. Budiman Barus, Maranatha Bens Pardamean Brian Yuliarto Daffa Refor Multi Ray Derrick Speaks Eklas Hossain Endang Djuana Fergyanto E. Gunawan Fin, Her G. N. Elwirehardja Hadiyanto Hadiyanto Iwan Agustono Kholid, Muhammad Arwan Kurniawan, Michael Radius Muhammad Asrol Prajitna, Stefanus H. Prajitna, Stefanus Hanifa Purwanto, Cipto Ryo G. Widjaja Sutanto, Wilson Tim Pasang Yohan Wahyudi Zulkarnaen, Joe Daniansyah Pahlevi