Article Per Year (5 Year)
p-Index From 2021 - 2026
0.659
P-Index
This Author published in this journals
All Journal ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika
Mili Alfhi Syari
Unknown Affiliation
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Penerapan Data Mining Pengelompokan Data Pengguna Air Bersih Berdasarkan Keluhannya Menggunakan Metode Clustering Pada PDAM Langkat Karin Annisa; Budi Serasi Ginting; Mili Alfhi Syari
ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA Vol 6, No 1 (2022): April 2022
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/algoritma.v6i1.11624

Abstract

Customer problems are indeed very complex, therefore they must be handled properly, clearly, and thoroughly. Good service from a company can show the professionalism of the company itself, meaning that seriousness, certainty of time, punctuality and work results that can be accounted for in solving all problems can prove the quality of a company. Clustering is the process of partitioning a set of data objects into subsets called clusters. Objects in the cluster have similar characteristics to each other and are different from other clusters. Clustering is very useful and can find unknown groups or groups in the data. From 2056 customer complaint data, the results obtained are Cluster 1, namely 12, 5, 5, in cluster 2, namely 4, 5, 5 and cluster 3, namely 8, 2, 2. With the number of cluster members 1 883 members, cluster 2 635 members and cluster 3 namely 538 members. From the results of the Matlab cluster, there are similar results, namely the types of complaints in cluster 1 and cluster 2, namely code 5 types of leaking pipe complaints with handling damage to connecting water pipes (gibout join). Keywords : Clustering, Custome Problems, Matlab
Design Of An LPG Leak Detection System Using Iot Based MQ-2 Sensor Mhd. Iqbal Prananda; Siswan Syahputra; Mili Alfhi Syari
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.337

Abstract

The IoT-based LPG gas leak detection system with MQ-2 and automatic regulator aperture is designed to protect the environment from the dangers of gas leaks and optimize gas use. The MQ-2 sensor is used to detect LPG gas accurately and sensitively. This system is connected to IoT which allows remote monitoring via smart devices. When the sensor detects that the LPG gas concentration exceeds a safe threshold, the system will send an alert with notification and automatically activate the regulator to cut off the gas supply. This helps prevent the accumulation of harmful gases. This design combines reliable gas detection with automatic operation to improve environmental safety and gas efficiency. LPG gas is very commonly used by the community because it has many advantages, but there are also many risks associated with using LPG gas, such as poisoning, shortness of breath and even fire. It is therefore important to have a leak detection system to prevent accidents that may occur, by integrating the programmable MQ-2 sensor and NoteMCU ESP8266.
Jaringan Syaraf Tiruan Memprediksi Jumlah Kebutuhan Semen pada Toko Bangunan Bintang Makmur Menggunakan Metode Backpropagation Dhovan Damara Santoso; Relita Buaton; Mili Alfhi Syari
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 2 No. 5 (2024): September : Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/jupiter.v2i5.559

Abstract

Every company is required to plan the need for goods as effectively as possible in order to maximize profits. Bintang Makmur Building Shop is a building shop that provides building materials, especially cement. Cement is one of the basic materials for buildings. The need for cement has recently continued to increase due to the large number of developments, both housing projects and road construction. In addition to the increasing demand for cement, cement prices also experienced price volatility which tended to fluctuate. This is done so that there is no stockpiling or even a shortage of cement. With prices that tend to go up and down if there is too much stock, it will cause losses if there is a price decrease. Vice versa if there is a shortage of cement stock, it can cause disappointment to customers. To deal with the above, it is necessary to build a prediction system that can predict cement needs in prosperous shops. The system that will be built uses an Artificial Neural Network (Artificial Neural Network) which is part of the science of artificial intelligence which has been widely used to solve various kinds of problems related to prediction or forecasting by utilizing the Backpropagation Method. The system is designed with the MATLAB programming application. From the results of the research that has been carried out, it was found that the total demand for Andalas cement for January of the following year is 0.2532 or 2532, thus the predicted total demand for Andalas cement is 2532 sacks.
Co-Authors Buaton, Relita Budi Serasi Ginting Dhovan Damara Santoso Karin Annisa Mhd. Iqbal Prananda Siswan Syahputra