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All Journal Jurnal Edukasi Elektro CogITo Smart Journal
Putri, Dila Marta
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering

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Electrical Energy Audit in Pratama Tapan Hospital Putra, Nanda Okta; Aini, Zulfatri; Putri, Dila Marta
Jurnal Edukasi Elektro Vol. 8 No. 1 (2024): Jurnal Edukasi Elektro, Volume 8, No. 1, Mei 2024
Publisher : DPTE FT UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jee.v8i1.65277

Abstract

Hospitals, as large energy consumers, must adopt efficient energy-saving measures due to cost increases, regulations, and climate change concerns. In this study, an electrical energy audit was conducted at Pratama Tapan Hospital to identify energy-saving opportunities and recommend equipment replacements or technology upgrades. The primary objective was to determine the Energy Consumption Intensity (ECI) and analyze the potential for energy savings. The audit re-vealed an ECI value of 10.33 kWh/m²/year, highly efficient by ASEAN-USAID standards. However, 100% of rooms didn't meet the SNI 03-6197-2000 light intensity standard, causing discomfort. The study recommends installing specific light fixtures and adjusting lamp power to comply with the standard. These findings offer valuable insights for healthcare institutions striv-ing to achieve sustainability goals.
A Machine Learning-Based Ambiguous Alphabet Recognition for Indonesian Sign Language System (SIBI) Purbolingga, Yoan; Ridwan, Ahmad; Putri, Dila Marta
CogITo Smart Journal Vol. 11 No. 1 (2025): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v11i1.816.1-14

Abstract

One of the communication problems in deaf people is the inhibition of verbal communication. This is due to the limited hearing function which has an impact on the imperfection of language sound reception. To communicate with deaf people, extraordinary communication is needed so that the meaning of the conversation can be conveyed properly. Sign language is the main communication medium for deaf people. However, in the use of sign language, there are ambiguous letters, namely “D “,“E“,“M“,“N“,“R“, “S“, and “U“. This research uses the chain code method to identify and reconstruct the shape of hand gesture objects. Then, to solve the problem of ambiguity of alphabet letters, an artificial intelligence method, namely K-Nearest Neighbors (K-NN), is used. The sample used consists of 350 real-time images with variations in object recognition accuracy. Based on the research using chain code and K-NN classification method, it can be concluded that the recognition of ambiguous letters in sign language has 245 training data for K-NN which has 88.76% accuracy, and 105 test data with 90% accuracy. This test data is divided into seven letters: “D“, “E”, “M”, “R” and “U” at 100%, and “N” and “S” at 98.88%.
Co-Authors Ahmad Ridwan Putra, Nanda Okta Yoan Purbolingga Zulfatri Aini