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Algoritma Deep Learning-LSTM untuk Memprediksi Umur Transformator Ningrum, Ayu Ahadi; Syarif, Iwan; Gunawan, Agus Indra; Satriyanto, Edi; Muchtar, Rosmaliati
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 3: Juni 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2021834587

Abstract

Kualitas dan ketersediaan pasokan listrik menjadi hal yang sangat penting. Kegagalan pada transformator menyebabkan pemadaman listrik yang dapat menurunkan kualitas layanan kepada pelanggan. Oleh karena itu, pengetahuan tentang umur transformator sangat penting untuk menghindari terjadinya kerusakan transformator secara mendadak yang dapat mengurangi kualitas layanan pada pelanggan. Penelitian ini bertujuan untuk mengembangkan aplikasi yang dapat memprediksi umur transformator secara akurat menggunakan metode Deep Learning-LSTM. LSTM adalah metode yang dapat digunakan untuk mempelajari suatu pola pada data deret waktu. Data yang digunakan dalam penelitian ini bersumber dari 25 unit transformator yang meliputi data dari sensor arus, tegangan, dan suhu. Analisis performa yang digunakan untuk mengukur kinerja LSTM adalah Root Mean Squared Error (RMSE) dan Squared Correlation (SC). Selain LSTM, penelitian ini juga menerapkan algoritma Multilayer Perceptron, Linear Regression, dan Gradient Boosting Regressor sebagai algoritma pembanding.  Hasil eksperimen menunjukkan bahwa LSTM mempunyai kinerja yang sangat bagus setelah dilakukan pencarian komposisi data, seleksi fitur menggunakan algoritma KBest dan melakukan percobaan beberapa variasi parameter. Hasil penelitian menunjukkan bahwa metode Deep Learning-LSTM mempunyai kinerja yang lebih baik daripada 3 algoritma lain yaitu nilai RMSE= 0,0004 dan nilai Squared Correlation= 0,9690. AbstractThe quality and availability of the electricity supply is very important. Failures in the transformer cause power outages which can reduce the quality of service to customers. Therefore, knowledge of transformer life is very important to avoid sudden transformer damage which can reduce the quality of service to customers. This study aims to develop applications that can predict transformer life accurately using the Deep Learning-LSTM method. LSTM is a method that can be used to study a pattern in time series data. The data used in this research comes from 25 transformer units which include data from current, voltage, and temperature sensors. The performance analysis used to measure LSTM performance is Root Mean Squared Error (RMSE) and Squared Correlation (SC). Apart from LSTM, this research also applies the Multilayer Perceptron algorithm, Linear Regression, and Gradient Boosting Regressor as a comparison algorithm. The experimental results show that LSTM has a very good performance after searching for the composition of the data, selecting features using the KBest algorithm and experimenting with several parameter variations. The results showed that the Deep Learning-LSTM method had better performance than the other 3 algorithms, namely the value of RMSE = 0.0004 and the value of Squared Correlation = 0.9690.
Perubahan Fungsi Lahan Untuk Status Rawan Bencana Dengan Remote Sensing Di Daerah Mandalika: Changes in Land Function for Disaster Prone Status Using Remote Sensing in the Mandalika Area Yadnya, Made Sutha; Kanata, Bulkis; Zainuddin, Abdullah; Paniran, Paniran; Ramadhani, Cipta; Rosmaliati, Rosmaliati
Jurnal Pepadu Vol 5 No 4 (2024): Jurnal PEPADU
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/pepadu.v5i4.5952

Abstract

Masalah utama Desa Tangguh Bencana (Destana)  di Desa Penyanggaya Sirkuit Madalika adalah bahaya tanah longsor akibat kemiringan tanah yang terjal,  masyarakat harus tahu kalau potensi tanah longsor dan menghidari pembuatan pemukiman akibat hujan atau gempa yang membuat retakan tanah. Situasi yang berbahaya tanah longsor dengan perubahan fungsi lahan dari perbukitan menjadi tanah urug. Universitas Mataram memiliki obsevatorium di Rembitan bagian dari Pusat Unggulan Iptek (PUI) Geomagnetik mengukur magnet bumi dengan satuan magnet bumi nTesla (Nano Tesla). Hasil pengukuran terjadi anomali (penurunan nilai magnet bumi. Ini merupakan precursor akan terjadinya gempa. Desa Sade dan Rembitan merupakan satu kawasan yang menjadi satu kesatuan yang harus dijaga dan memberikan pengetahuan akan bahaya banjir dan tanah longsor akibat cuaca ekstrim. Proses menggunaka remote sensing dengan foto udara. Hal hasil telah didapatkan bebarapa titik rawan bencana.
PROGRAM PEMENUHAN ENERGI DI RUMAH QUR’AN SEMBALUN DESA SEMBALUN BUMBUNG, KECAMATAN SEMBALUN, KABUPATEN LOMBOK TIMUR Yadnya, Made Sutha; Ramadhani, Cipta; Zubaidah, Teti; Kanata, Bulkis; Rosmaliati, Rosmaliati
Jurnal Pepadu Vol 6 No 1 (2025): Jurnal Pepadu
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/pepadu.v6i1.6977

Abstract

Sembalun Bumbung Village, East Lombok, faces the problem of river pollution due to the disposal of livestock manure and garbage, which on the other hand has great potential to be processed into biogas as an economical, environmentally friendly, and sustainable alternative energy. This program aims to design and implement a biogas system at Rumah Qur'an At-Tazkiyyah Sembalun, a boarding school that is also a center for community empowerment, to meet energy needs while reducing environmental pollution. The methods used include training and assistance to students and the community about biogas processing, starting from organic waste fermentation, the use of fermented gas for cooking and electricity, to the use of residual waste as organic fertilizer, as well as education on livestock care and waste management to support the sustainability of the program. Expected outputs include the production of renewable energy in the form of biogas for cooking and electricity, reduction of waste that pollutes the environment, increasing public awareness about waste management, and creating a cleaner and healthier environment. Keyword : livestock manure; garbage; energy; biogas; organic fertilizer
PEMBUATAN TEH HERBAL DARI DAUN KELOR (Moringa oleifera) UNTUK MENINGKATKAN KESEHATAN TUBUH Hakim, Muhamad Shaufil; Sari, Ainayya Amalia; Al Aqad, Yuniar Rizki Rahmawati; Amara, Nadya; Putri, Aida Musyarrifah Hasri; Putra, Muhammad Septian Dwi; Sani, Nabila Aulia; Khaerunnisa, Khaerunnisa; Darmawan, Adi; Susanto, Oki Novian; Rosmaliati, Rosmaliati
Jurnal Wicara Vol 1 No 5 (2023): Jurnal Wicara Desa
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/wicara.v1i4.3396

Abstract

Moringa is a type of plant that belongs to the Moringaceae family. This plant is also known as (Moringa oleifera). Moringa has many uses and has long been used by various cultures because various parts of this plant have high nutritional value and health properties that are considered beneficial. Some parts of the Moringa plant that are commonly used are the leaves, fruit, flowers, seeds, and roots. Moringa (Moringa Oleifera) originates from India and Arabia and then spreads to various regions. years, and withstand extreme heat conditions. This plant comes from tropical and subtropical regions of South Asia. In Indonesia, Moringa trees are widely planted as living fences, planted along fields or on the edges of rice fields, functioning as green plants. In addition, the Moringa plant is also known as a nutritious medicinal plant by utilizing all parts of the Moringa plant, starting from the leaves, bark, seeds, to the roots. This plant has been studied for its health benefits, has antifungal, antioxidant, antibacterial, anti-inflammatory, diuretic, and as a hepatoprotector. According to Folid, Moringa leaves can be consumed as a vegetable, consumed in the form of Moringa leaf tea, flour, powder or Moringa leaf capsules. Moringa leaf tea is a caffeine-free herbal tea which is very good for health and has a pretty good taste. Moringa leaf tea contains many nutrients that can increase the body's metabolism. Tea is a drink prepared by soaking the leaves or certain parts of the tea plant (Camellia sinensis) in hot water. This tea plant is the main source for various types of tea known throughout the world. There are several main types of tea that are produced from the Camellia sinensis tea plant, and these differences are mainly derived from the processing of the tea leaves.
PEMANFAATAN ECOBRICK SEBAGAI MEDIA KREATIVITAS DI KELURAHAN TANJUNG, KOTA BIMA Agustiansyah, Muhammad Rizki; Agustiansyah, Muhammad Rizki Agustiansyah; Rousanfikr, Sava Arcadia; Maulinda, Ade Azahra; Hening, Beta Tiva Ratu; Putri, Andi Nirmala; Az-Zahra, Annisa; Azmi, Muhammad; Puspita, Intan Imda; Hamdani, Muhammad Ananda Rizki; Rosmaliati, Rosmaliati
Jurnal Wicara Vol 2 No 6 (2024): Jurnal Wicara Desa
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/wicara.v2i6.5628

Abstract

The problem of plastic waste is a serious issue in Indonesia, especially in Tanjung Village, Bima City, where waste management is still less than optimal. One solution implemented is the use of Ecobrick, a plastic waste management technique by filling used bottles with plastic until they are solid and hard. This program involves socialization and training at SDN 29 Tanjung and SMPN 13 Bima City, where students are taught how to process plastic waste into products with economic value such as furniture. The results of this program show that Ecobrick is effective in reducing the volume of plastic waste while increasing public awareness of the importance of waste management. The use of Ecobrick not only helps maintain environmental cleanliness but also provides economic benefits and has the potential to reduce negative environmental impacts such as coastal abrasion. It is hoped that this program can be the first step in forming new habits in the community related to waste management.
Pemanfaatan Biogas untuk Mendukung Penerangan Mandiri Berbasis Energi Terbarukan di Rumah Qur’an Sembalun Rosmaliati, Rosmaliati; Kanata, Bulkis; Yadnya, Made Sutha; Zainuddin, Abdullah; Rachman, A. Sjamsjiar; Paniran, Paniran; Akbar, Lalu Muhamad Roviq; Suharyadi, Farhan Ahmad
Jurnal Pustaka Mitra (Pusat Akses Kajian Mengabdi Terhadap Masyarakat) Vol 5 No 6 (2025): Jurnal Pustaka Mitra (Pusat Akses Kajian Mengabdi Terhadap Masyarakat)
Publisher : Pustaka Galeri Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55382/jurnalpustakamitra.v5i6.1363

Abstract

Keterbatasan pasokan listrik dan ketergantungan pada energi fosil menjadi permasalahan utama yang dihadapi masyarakat di Rumah Qur’an Sembalun. Kondisi ini mendorong perlunya pengembangan sumber energi alternatif yang ramah lingkungan dan berkelanjutan. Kegiatan pengabdian ini bertujuan untuk memanfaatkan biogas sebagai sumber energi listrik mandiri melalui penerapan sistem digester dan penampungan plastik berkapasitas 8 m³ yang terhubung dengan generator berkapasitas 700 watt. Metode pelaksanaan meliputi pengolahan limbah kotoran sapi dalam digester, penyaluran biogas ke penampungan, dan pengujian kinerja generator dalam menyalakan lampu LED hemat energi. Hasil pengujian menunjukkan bahwa sistem biogas mampu menghasilkan daya listrik antara 8 hingga 58 watt, dengan lama nyala total mencapai 60 menit. Daya rata-rata yang dihasilkan sebesar 15,28 watt dibandingkan daya nominal 15 watt, sehingga diperoleh efisiensi konversi energi sebesar 98,13%. Kegiatan ini membuktikan bahwa penerapan biogas berbasis penampungan plastik berkapasitas 8 m³ efektif untuk mendukung penerangan mandiri, sekaligus memberikan manfaat tambahan berupa pengelolaan limbah ternak dan pengurangan emisi gas rumah kaca, yang berkontribusi terhadap upaya kemandirian energi dan keberlanjutan lingkungan di wilayah pedesaan.
Co-Authors A'yunin, Intan Qurratun A. Sjamsjiar Rachman Abdul Natsir Abdulah Zainuddin Abdullah Zainuddin Abdullah Zainuddin Adi Darmawan Agung Budi Muljono Agustiansyah, Muhammad Rizki Agustiansyah, Muhammad Rizki Agustiansyah Akbar, Lalu Muhamad Roviq Al Aqad, Yuniar Rizki Rahmawati Amara, Nadya Ardyono Priyadi Asror, Hazinatul Az-Zahra, Annisa Bernandus Anggo Seno Aji Bulkis Kanata Bulkis Kanata Bulkis Kanata Cipta Ramadhani Derajat, Dirga Dama Dwi Ratnasari Dzulfikar Ats Tsauri Edi Satriyanto Eka Meilia Suryanti Gunawan, Agus Indra Hakim, Muhamad Shaufil Hamdani, Muhammad Ananda Rizki Hazi, Khaerul Hening, Beta Tiva Ratu Ida Ayu Sri Adnyani Ida Bagus Fery Citarsa Ilmiatul Masfufiah Imam Wahyudi Farid Isa Hafidz iwan Syarif Jurnal Pepadu Kenya Damayanti Priyatna Khaerunnisa Khaerunnisa, Khaerunnisa Lalu Muhamad Irfan Made Sutha Yadnya Majdi, Shafwatul Maulinda, Ade Azahra Mauridhi Hery Purnomo Misbahuddin, Misbahuddin Misbahul Munir Muhammad Azmi, Muhammad Nababan, Sabar Natsir, Abdul Ni Luh Sinar Ayu Ratna Dewi Ni Made Seniari Ni Made Seniari Ningrum, Ayu Ahadi Novie Elok Setiawati Paniran Paniran Puspita, Intan Imda Putra, Muhammad Septian Dwi Putri, Aida Musyarrifah Hasri Putri, Andi Nirmala Ramdani, M. Rosyantita, Tania Tri Rousanfikr, Sava Arcadia Sabar Nababan Sani, Nabila Aulia Sari, Ainayya Amalia Sevyanto, Yusril Bagas Sudi Maryanto Al Sasongko Suharyadi, Farhan Ahmad Supriyatna Supriyatna Susanto, Oki Novian Teti Zubaidah Teti Zubaidah Teti Zubaidah Tri Putri, Geby Harlia Trisna Wati Yeni Rahmawati, Yeni Zainuddin, Abdullah