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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Epsilon: Jurnal Matematika Murni dan Terapan Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Telematika KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Komputasi Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Journal of Electronics, Electromedical Engineering, and Medical Informatics Indonesian Journal of Electrical Engineering and Computer Science JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Pengabdian Ilung (Inovasi Lahan Basah Unggul) Journal of Data Science and Software Engineering Jurnal Teknik Ilmu dan Aplikasi Jurnal Informatika Polinema (JIP)
Saragih, Triando Hamonangan
Universitas Lambung Mangkurat
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Journal : KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal)

 1 
EFESIENSI ENERGI PADA BANGUNAN MENGGUNAKAN MULTIVARIATE RANDOM FOREST Triando Hamonangan Saragih; Mohammad Reza Faisal; Muhammad Haekal
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 9, No 1 (2022)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v9i1.421

Abstract

Energy is needed by humans. Energy utilization is often carried out in daily activities, such as helping with work, household activities to lighting both at home and on the road. Recently, there has been a lot of research on concerns about the waste of energy and its lasting adverse impact on the environment. Previous research conducted by Tsanas and Xifara in 2012 has carried out energy efficiency in buildings using Statistical Machine Learning. Their research focuses on calculating outcomes one by one, not directly on all outcomes. In this study using the Multivariate Random Forest method. Multivariate Random Forest has similarities compared to Random Forest, while the Multivariate Random Forest method is more used if more than one output is produced. Based on the tests that have been carried out, it can be concluded that the best parameter that gives maximum results is the number of trees as many as 200 with a data division of 60% training data and 40% testing data with RMSE results of 2.602036 and MSE result of 6.770589. Based on the tests that have been carried out, it proves that the more the number of trees does not prove that it can provide maximum results.Keywords: Energy, Efficiency, Prediction, Multivariate Random ForestEnergi sangat dibutuhkan oleh manusia. Pemanfaatan energi sering dilakukan dalam kegiatan sehari-hari, seperti membantu pekerjaan, kegiatan rumah tangga hingga penerangan baik dalam rumah maupun di jalan. Akhir-akhir ini banyak penelitian tentang kekhawatiran mengenai pemborosan energi dan dampak buruknya yang abadi terhadap lingkungan. Penelitian sebelumnya yang dilakukan oleh Tsanas dan Xifara pada tahun 2012 telah melakukan efesiensi energi pada bangunan menggunakan Statistical Machine Learning. Penelitian mereka berfokus pada perhitungan luaran secara satu persatu, tidak secara langsung semua luaran. Pada penelitian ini menggunakan metode Multivariate Random Forest. Multivariate Random Forest memiliki kesamaan dibandingkan dengan Random Forest, sedangkan metode Multivariate Random Forest lebih digunakan jika luaran yang dihasilkan lebih dari satu. Berdasarkan pengujian yang sudah dilakukan, dapat disimpulkan bahwa parameter terbaik yang memberikan hasil maksimal yaitu pada jumlah pohon sebanyak 200 dengan pembagian data sebanyak 60% data latih dan 40% data uji dengan hasil RMSE sebesar 2.602036 dan MSE sebesar 6.770589. Berdasarkan pengujian yang sudah dilakukan membuktikan semakin banyak jumlah pohon tidak membuktikan bisa memberikan hasil yang maksimal.Kata kunci: Energi, Efesiensi, Prediksi, Multivariate Random Forest
OPTIMASI FUNGSI KEANGGOTAAN FIS TSUKAMOTO MENGGUNAKAN SIMULATED ANNEALING UNTUK IDENTIFIKASI PENYAKIT GIGI Triando Hamonangan Saragih; Rahmat Ramadhani; Muhammad Itqan Mazdadi; Ahmad Rusadi Arrahimi; Mohammad Reza Faisal
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 7, No 3 (2020)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v7i3.349

Abstract

Teeth are one of the tools in the framework related to the human stomach which fills as a food destroyer for simple processing. Diseases that attack teeth can withstand this action and cannot be distinguished quickly by young dental specialists. This problem can be solved by methods in the field of technology. The algorithm that can be used is FIS Tsukamoto in classification. Optimization of the membership function at FIS Tsukamoto is needed to improve accuracy. Optimization of FIS Tsukamoto membership function using Simulated Annealing produced the highest accuracy at 92.5% of the 100 test data.Keywords: Simulated Annealing; FIS Tsukamoto, Dental Disease, Optimization Gigi adalah salah satu alat dalam kerangka terkait perut manusia yang mengisi sebagai penghancur makanan untuk pemrosesan sederhana. Penyakit yang menyerang gigi dapat menahan tindakan ini dan tidak dapat dibedakan dengan cepat oleh dokter muda spesialis gigi. Masalah ini dapat diselesaikan dengan metode di bidang teknologi. Algoritma yang bisa digunakan yaitu FIS Tsukamoto dalam melakukan klasifikasi. Optimasi fungsi keanggotaan pada FIS Tsukamoto diperlukan untuk meningkatkan akurasi. Optimasi fungsi keanggotaan FIS Tsukamoto menggunakan Simulated Annealing menghasilkan akurasi paling tinggi yaitu 92,5% dari 100 data uji.Kata kunci: Simulated Annealing; FIS Tsukamoto, Penyakit Gigi, Optimisasi
Co-Authors Abdul Latief Abadi Ahmad Rusadi Arrahimi - Universitas Lambung Mangkurat) Ahmad Rusadi Arrahimi - Universitas Lambung Mangkurat) Ajwa Helisa Alfita Rakhmandasari Amelia Aditya Santika Andi Farmadi Andi Farmadi Dina Arifah Diny Melsye Nurul Fajri Diny Melsye Nurul Fajri Dodon Turianto Nugrahadi Dwi Kartini Dwi Kartini, Dwi Fatma Indriani Fatma Indriani Friska Abadi Haekal, Muhammad Irwan Budiman Ivan Sitohang MARIA ULFAH Mariana Dewi Muhamad Fawwaz Akbar Muhammad Al Ichsan Nur Rizqi Said Muhammad Darmadi Muhammad Fauzan Nafiz Muhammad Haekal Muhammad Haekal Muhammad Itqan Mazdadi Muhammad Meftah Mafazy Muhammad Reza Faisal, Muhammad Reza Muhammad Ridho Ansyari Muhammad Rofiq Muliadi Muliadi Muliadi Muliadi Muliadi Muliadi Muliadi Muliadi Nurlatifah Amini Purwoko, Agus Radityo Adi Nugroho Rahmat Ramadhani Rahmat Ramadhani Ramadhani, Rahmat Ratna Septia Devi Regina Rudy Herteno Rudy Herteno SALLY LUTFIANI Salsha Farahdiba Siti Napi'ah Suci Permata Sari Sulastri Norindah Sari Totok Wianto Vivi Nur Wijayaningrum Wayan Firdaus Mahmudy Yanche Kurniawan Mangalik Yusuf Priyo Anggodo