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Evaluation of Reliability and Energy Not Supplied in the 20 kV Distribution System at the Tanjung Api-Api Substation Malini, Regina Septient; Barlian, Taufik; Lestari, Asri Indah
Journal of Electrical Engineering and Computer (JEECOM) Vol 7, No 1 (2025)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v7i1.10780

Abstract

The reliability of the electric power distribution system is essential for life, economy, health and safety. This reliability can be assessed from several indicators, including SAIDI, SAIFI, and ENS which can describe the economic impact of blackouts. The results of the calculation in this study show that the SAIDI and SAIFI values for four Feeders at the Tanjung Api-api Substation are in a reliable state when viewed from the PLN Target that has been set, and are not reliable for Ferry Feeders, namely SAIDI at Ferry Feeders of 6.003570985 hours/year, Cargo Feeders of 0.272152778 hours/year, Pinisi Feeders of 0.771065263 hours/year and Roro Feeders of 1.477902547 hours/year. As for SAIFI on Ferry Feeders amounting to 3.230883689 times/customer/year, Cargo Feeders 0.16666667 times/customer/year, Pinisi Feeders 0.836271676 times/customer/year and Roro Feeders 1.67529189 times/customer/year. For the ENS value index on the four Feeders based on the calculation results, 396,201.8423 Kwh was obtained with a loss of Rp. 536,118,758.6 kWh, in the Ferry Feeder that was not distributed energy of 319,128.4392 kWh with a loss of Rp. 431,461,649.8, in the Cargo Feeder of 4,896.091948 kwh with a loss of Rp. 7,073,384,037, in the Feeder of 7,136.846081 kWh with a loss of Rp. 9,649,015,901 and in the Roro Feeder of 65,040.46513 kWh with a loss of Rp. 87,934,708.86.  The results show that the higher the unchanneled energy, the greater the losses experienced by PT. PLN (Persero).
LITERATURE REVIEW: PERAN SISTEM SMART HEALTH SEBAGAI INOVASI DIGITAL DALAM UPAYA PENCEGAHAN STUNTING Malini, Regina Septient; Firdaus; Adinandra, Sisdarmanto
Jurnal Elektro Kontrol (ELKON) Vol. 5 No. 2 (2025): Jurnal ELKON
Publisher : Teknik Elektro Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/elkon.v5i2.15706

Abstract

Stunting merupakan permasalahan kesehatan masyarakat yang berdampak jangka panjang terhadappertumbuhan fisik dan perkembangan kognitif anak. Seiring dengan perkembangan teknologi digital,pendekatan smart health berbasis Internet of Things (IoT), Artificial Intelligence (AI), dan Machine Learning(ML) mulai diterapkan sebagai solusi inovatif dalam upaya deteksi dan pencegahan stunting. Penelitian inimenggunakan metode systematic literature review terhadap 20 jurnal ilmiah untuk mengidentifikasipenerapan teknologi smart health dalam tiga kategori utama: deteksi, pemantauan, dan pencegahan stunting.Hasil studi menunjukkan bahwa teknologi ini mampu meningkatkan efektivitas deteksi dini, efisiensipemantauan secara real-time, serta memperluas cakupan edukasi gizi kepada masyarakat melalui mediadigital yang interaktif. Namun demikian, implementasinya masih menghadapi sejumlah tantangan, sepertiketerbatasan infrastruktur, rendahnya literasi digital, serta kurangnya integrasi dengan sistem informasikesehatan nasional. Oleh karena itu, keberhasilan penerapan smart health membutuhkan dukungan kebijakan,infrastruktur yang memadai, serta evaluasi berkelanjutan agar dapat diimplementasikan secara optimal danberkelanjutan di berbagai wilayah, khususnya di daerah dengan sumber daya terbatas.