Article Per Year (5 Year)
p-Index From 2020 - 2025
0.562
P-Index
This Author published in this journals
All Journal JURNAL INTEGRASI
Diono Diono
Unknown Affiliation
Other

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

Found 3 Documents
Search

 1 
Sistem Semi Otomasi pada Proses Tinning Pin Lampu di PT. Excelitas Technologies Batam Diono Diono; Gindo Leonard Manahan Simanjuntak; Handri Toar; Muhammad Syafei Gozali; Adlian Jefiza
JURNAL INTEGRASI Vol 14 No 1 (2022): Jurnal Integrasi - April 2022
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/ji.v14i1.3889

Abstract

The tinning process is the process of coating a thin sheet of wrought iron or steel with tin and the resulting product is known as tinplate. The tinning process at PT. Excelitas Technologies Batam is done by clamping the lamp using your finger and then dipping it into flux and molten tin repeatedly until the lamp pin is evenly coated with tin which is done manually and is very dangerous for workers. Therefore, we need a Semi Automation System for the PLC-based Lamp Tinning Process. The method used is the use of a timer in the PLC-based flux dyeing and tining process. The tool testing process is carried out on 10 pcs lamp pins which are immersed 2 times in the flux and tinning process. The result of this research is that the cycle time loading / unloading of the lamp pin tinning process is reduced from 14.4 seconds to 11 seconds.
Rancang Bangun Prototype Sistem Monitoring dan Data Logger pada Sistem Listrik 3-Phase Arif Febriansyah Juwito; Diono Diono; Miftahul Jihad
JURNAL INTEGRASI Vol 14 No 2 (2022): Jurnal Integrasi - Oktober 2022
Publisher : Pusat Penelitian dan Pengabdian Masyarakat Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/ji.v14i2.4344

Abstract

Electrical energy is one of the basic needs in life today, but in its utilization, several problems can cause losses in the electricity system, one of the causes is nontechnical shrinkage that often occurs on the customer's side in the form of electricity theft. Therefore, innovation is carried out using IoT (Internet of Things) in order to easily monitor the parameters of electricity magnitude. In this study, a stage of collecting parameters of the amount of electricity was proposed. The electric power observation method uses a voltage sensor (ZMPT101B) and a current sensor (SCT-013-000). Arduino Nano microcontrollers are used in measurement systems and the Wemos D1 Mini is used as a link to internet connections over Wi-Fi networks. Measurement data is sent and stored to the MySQL Database in the form of a data logger. The media used is a Website-based GUI. The results showed that remote monitoring using GUI can be done, where this tool can send parameters measuring the amount of electrical voltage, current, active power, and power factor as well as calculations of energy consumption and electricity usage costs to the GUI with a period of once every 10 minutes.
Analisis Data Monitoring proses pengelasan FCAW (Flux Core Arc Welding) berbasis Multi Layer Perceptron Adlian Jefiza; Diono Diono; Sumantri Lukito
JURNAL INTEGRASI Vol 14 No 2 (2022): Jurnal Integrasi - Oktober 2022
Publisher : Pusat Penelitian dan Pengabdian Masyarakat Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/ji.v14i2.4538

Abstract

Pengelasan FCAW sangat dipengaruhi oleh parameter pengelasan agar tidak terjadi cacat las seperti Undercut, Underfill dab Overlap. Parameter tersebut terdiri dari Tavel Speed, Arus DC, Tegangan DC dan Heat Input. Untuk monitoring data parameter tersebut sudah dirancang dan digunakan di Industri. Namun untuk memprediksi kemungkinan cacat las, dibutuhkan klasifikasi data monitoring pengelasan FCAW. Metode yang digunakan dalam klasifikasi adalah Multi Layer Perceptron (MLP). Data yang digunakan adalah 400 data untuk klasifikasi, dan 201 data untuk prediksi. Hasil klasifikasi menggunakan MLP memperoleh akurasi sebesar 98,99 % dengan RMSE sebesar 0,0624. Sedangkan untuk prediksi, berdasarkan 201 data terdapat 169 data normal dan 32 data cacat las.
Co-Authors Adlian Jefiza Arif Febriansyah Juwito Gindo Leonard Manahan Simanjuntak Handri Toar Miftahul Jihad Muhammad Syafei Gozali Sumantri Lukito