Article Per Year (5 Year)
p-Index From 2021 - 2026
2.804
P-Index
This Author published in this journals
All Journal Al Ishlah Jurnal Pendidikan Jurnal Inovasi dan Pelayanan Publik Makassar Journal of Telenursing (JOTING) Community Development Journal: Jurnal Pengabdian Masyarakat Madaniya Jurnal Dedikasi Jurnal Abdimas ADPI Sosial Dan Humaniora Proceedings of The International Conference on Social and Islamic Studies Seminar Nasional Pengabdian Kepada Masyarakat INOVASI: Jurnal Hasil Pengabdian Masyarakat IPTEK: Jurnal Hasil Pengabdian kepada Masyarakat Seminar Nasional Hasil Penelitian LP2M UNM Prosiding Seminar Nasional Dies Natalis Universitas Negeri Makassar
Nurlita Pertiwi
Dosen Universitas Negeri Makassar
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Energy Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

Published : 23 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Seminar Nasional Hasil Penelitian LP2M UNM

 1 
Sifat Workability Beton Ramah Lingkungan Irma Aswani Ahmad; Nurlita Pertiwi; Nur Anny Suryaningsih Taufieq
Seminar Nasional LP2M UNM 2017
Publisher : Seminar Nasional LP2M UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (288.376 KB)

Abstract

Salah satu sifat dari beton segar yang mempengaruhi kualitas beton ramah lingkungan yaitu workability dikaji dalam penelitian ini. Beton ramah lingkungan yang diteliti adalah jenis beton yang menggunakan limbah abu sekam padi (ASP) sebagai pengganti sebagian semen.Penelitian ini adalah penelitian eksperimental yang dilakukan pada Laboratorium Uji Bahan Jurusan PTSP FT UNM. Benda uji beton segar dibuat berdasarkan rancangan campuran mutu beton 20 MPa dengan fas 0.45. Persentase ASP yang digunakan adalah 0% , 5% dan 7.5% dari berat semen.Sifat workability ini diukur dengan 3 parameter yaitu hasil dari uji slump, faktor kepadatan dan bleeding. Berbeda dengan penelitian lain, semen yang digunakan adalah tipe Portland Composite Cement. Hasil penelitian menunjukkan bahwa semakin tinggi persentase ASP, maka nilai slump, faktor kepadatan dan bleeding semakin rendah. Hasil penelitian ini memberikan gambaran jelas mengenai pengaruh persentase abu sekam padi terhadap workability. Hal ini bermanfaat dalam penentuan jumlah air sehingga mendapatkan workability yang layak dalam menciptakan beton ramah lingkungan. Kata kunci: workability, ramah lingkungan, bleeding, faktor kepadatan, slump
Ecobehavior dalam Pengelolaan Sungai dengan Analisis Neural Network Nurlita Pertiwi; Dyah Darma Andayani; Fhatiah Adiba
Seminar Nasional LP2M UNM SEMNAS 2019 : PROSIDING EDISI 7
Publisher : Seminar Nasional LP2M UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Abstract.The using of neural network methods is an alternative analysis to predict community behavior in river protection. Therefore this study aims to describe the factors that must be considered in the use of Neural network analysis in compiling eco behavior models in river management. This study uses a neural network analysis with a backpropagation approach. The data presented in the analysis were 210 respondents representing the farming community managing land along the river. This research is located in Soppeng Regency, South Sulawesi. The stages of the study are 1) Compiling a backpropagation architecture, 2) Conducting a validation of the model and 3) Conducting a test of the model to obtain the accuracy of the model. The results of the study that describe ten factors as input in the analysis of neural networks are not accurately used in the eco behavior model. This is based on an accuracy value of 48.57%. Therefore, as an effort to develop eco behavior models with Neural network analysis, it should be done in-depth by arranging diverse architectures. Keywords: accuracy, backpropagation, behavior
Co-Authors Agustang, Andi Anas Arfandi Armi Indrayuni Armiwaty Armiwaty Aswar Annas Awaluddin Awaluddin BAKHRANI RAUF Erma Suryani Sahabuddin Faizal Amir Fhatiah Adiba Fitriani, Lisna Annisa Frederik Palallo Gufran D. Dirawan Gufran D. Dirawan Gufran Darma Wirawan Hadrawi Machmud Hamsu Abdul Gani Hasni Hasni Husnah Katjina Irma Aswani Ahmad Irma Aswani Ahmad, Irma Aswani Irwan Syarif Iskandar Jaudin Jaudin Lahming Lahming Maghfirah Hariyanti Syamsul Bahri Mandra, Moh. Ahsan S. Mithen Lullulangi Mithen Mithen Muh. Rais Muhammad Ardi Muhammad Azwar Muhammad Haristo Rahman Muhammad Rais Muhasidah Muhasidah Noor Fadilah Romadhani Nur Anny Suryaningsih Taufieq Nurul Muhlisa Abdal Panennungi Panennungi Putri, Andi Nur Raeny Tenriola Idrus Rahmatan Rahmatan Ratnawati Tawani Sahrul Alam Syamsuddin Mustafa Tri Astuti Yulis Sayang Yulis, Dian Meiliani