Article Per Year (5 Year)
p-Index From 2021 - 2026
1.578
P-Index
This Author published in this journals
All Journal JURNAL SISTEM INFORMASI BISNIS JOIV : International Journal on Informatics Visualization Petra International journal of Business Studies (IJBS) INSIST (International Series on Interdisciplinary Research) Jurnal Teknologi Terpadu MULTINETICS Jurnal ABDINUS : Jurnal Pengabdian Nusantara Jurnal Abdi Insani BHAKTI PERSADA Jurnal Aplikasi IPTEKS (Journal of Applied Sciences and Technology) Jurnal Ilmu Kesehatan Immanuel
Maria Agustin
Fakultas Psikologi Universitas Merdeka Malang
Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Transportation Veterinary Other

Published : 12 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : MULTINETICS

 1 
Pemantauan Dan Pengendalian Pintu Air Berbasis Komunikasi Radio Full Duplex Dengan Algoritma Decision Tree Kurniawan, Asep; Hermawan, Indra; Agustin, Maria
MULTINETICS Vol. 9 No. 1 (2023): MULTINETICS Mei (2023)
Publisher : POLITEKNIK NEGERI JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/multinetics.v9i1.5156

Abstract

Provision, management and distribution of water on agricultural land is one of the important factors that affect the quantity and quality of agricultural products. An irrigation canal technology is needed that is able to flow through all agricultural land according to the water needs of each land. Smart irrigation systems can be a solution to this problem. The smart irrigation technology that was previously developed has several limitations such as the length of time data transmission takes to reach the client, sensor devices in the field must take turns sending data and receiving data resulting in data not being sent or not being read properly, besides that the system that has been developed previously depends on to one factor, namely the water level to determine the degree of openness of the floodgates. In this research a fast sensor to cloud communication system is designed using websocket technology. This system is also designed to send and receive data simultaneously using full duplect communication technology. As well as using artificial intelligence with the decision tree algorithm to regulate the openness of the floodgates based on the water requirement for the rice fields, the water level in the irrigation canals and the speed of the water flow. This research produced a prototype of an intelligent irrigation system that can send data to clients with an average time of 417ms, the system is also able to handle 500 clients that are connected directly to the server. The system can also send and receive data simultaneously with a difference in time when data is received at the sensor node or at the central node which can reach 0ms. This prototype also succeeded in making an artificial intelligence system that is accurate, fast and real-life. This artificial intelligence can handle 500 requests simultaneously with an execution time of 544ms.
IMPLEMENTASI ALGORITMA DECISION TREE DENGAN FITUR SELEKSI WEIGHT BY INFORMATION GAIN Ali, Euis Oktavianti; Agustin, Maria; Sari, Risna
MULTINETICS Vol. 9 No. 2 (2023): MULTINETICS Nopember (2023)
Publisher : POLITEKNIK NEGERI JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/multinetics.v9i2.5715

Abstract

This paper aims to apply the weight selection feature by considering the Gain Ratio value in the decision tree algorithm in classifying student academic scores. We determine the feature selection from the gain ratio based on the split value information to reduce the feature's (attribute) bias value. The highest Gain Ratio' value will be the root of the branching in the tree in which becomes a determining feature (attribute) of student graduation. We use 82 data which are divide into two classes called a pass and a not pass. From the data, we know that the attribute ip smt 7 got the highest gain ratio value with 0.581. On the other hand, the multimedia introduction attribute got the lowest gain ratio value with 0.070. The calculation model using cross-validation with a value of k = 5 resulted in optimal performance. The resulting accuracy is 79.19% and AUC 0.778 using the decision tree algorithm. The threshold value of the gain ratio used is 1.00 so that four attributes are not used in this paper. feature selection using weights with information gain ratio will select the attribute selection process to be built in the model.
Co-Authors Ali, Euis Oktavianti Aprilia, Puput Dwi Asep Kurniawan Asep Taufik Muharram Dautrey, Jean Marc Defiana Arnaldy Dewi Yanti Liliana Herlina Herlina Hermayanti, Elva HR, Des Fitria Putri Huzaifa, Malisa INDRA HERMAWAN Kadarwati, Dinda Kana, Vera Radja Marcheta, Noorlela Matin, Iik Muhamad Malik Mulyani, Meutia Tri Munawaroh Munawaroh Nalawati, Rizki Elisa Nathanael, David Prihatin Oktivasari Putri, Dini Marsela Ratna Widya Iswara, Ratna Widya Saarce Elsye Hatane Sari, Risna Sukma, Yunila Supani, Ahyar Susanti Susanti Toni Prahasto Warsuta, Bambang Widyono, M. Farishanif Yuli Andriani Zain, Ayu Rosyida