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All Journal Jurnal Teknik Jurnal Rekayasa Sistem Industri Politeknosain Integrasi: Jurnal Ilmiah Teknik Industri
Yustina Tritularsih
Politeknik ATMI Surakarta
Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering

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Analisis Pemanfaatan RFID terhadap Efisiensi Biaya dalam Global Supply Chain Management yustina tritularsih
Jurnal Rekayasa Sistem Industri Vol. 7 No. 1 (2018): Jurnal Rekayasa Sistem Industri
Publisher : Universitas Katolik Parahyangan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (671.387 KB) | DOI: 10.26593/jrsi.v7i1.2798.47-54

Abstract

Supply Chain Management (SCM) has been assumed to play an important role in the company's performance and has attracted academician’s attention to research seriously in these recent years. A number of literatures reveal the research of supply chain management developmenth that has implemented RFID technology. Generally, the method is implemented by combining and informing the journal about cost-benefit analysis model in a company that applies RFID tag technology integratedly from production line, delivery up to management of retailer part. Currently, all links from the entire supply chain need to integrate those different parts and have better controls to get better returns. This integration must offer the ability for the company to have a thorough and transparent insight into its supply chain activities. Intelligent supply chains that are primarily supported by RFID technology can meet these integration needs. By using RFID, a company can benefit from several advantages. One of them is cost reduction and time efficiency. This paper attempts to recommend a model to estimate the benefits of implementing RFID in companies that have an integrated supply chain process. The proposed model is used to find out the value of depreciation and RFID price tag that can provide maximum benefit from RFID implementation. Examples of case studies provide a better understanding of calculation model
Analisa Pengembangan Sistem Pemantau Daya Listrik Berbasis IoT Fenty Pandansari; Hoedi Prasetyo; Yustina Tri Tularsih
Jurnal Teknik Vol 19 No 2 (2021): Jurnal Teknik
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37031/jt.v19i2.185

Abstract

The IoT-based power monitoring device is a device composed of a CT sensor of type SCT-013, an AC-AC power adapter, an Arduino, and a Raspberry Pi. The tool is used to monitor voltage, current, frequency, real power, apparent power and power factor. The measured basic quantities are voltage, current, and frequency. The purpose of the measurement and monitoring processes is to conserve, control the quality, and control the use of electrical energy. In the measurement and monitoring process, tool accuracy is very important because it is closely related to the quality of electrical energy. This study presents an analysis of the accuracy of the power monitoring tool according to the variations in voltage, current, and frequency at the source. The method used is to vary the voltage, current and frequency used as input to the system and compare the measurement results of the power monitor with the Fluke True RMS Multimeter. The test results show that the level of accuracy of the IoT-based power monitoring device on the voltage parameter is 99.1%, the current parameter is 98.75%-99.25% and the frequency is 100%, so it is a proper tool to measure the quality of electrical energy.
Purwarupa Sistem Keamanan Locker Laboratorium Berbasis Raspberry Pi Biometrik dan RFID Yustina Tritularsih; Yohanes Sugiarto; Hizkia Urianto
Politeknosains Vol 19 No 1 (2020): Jurnal Politeknosains Volume 19 Nomor 1 - Maret 2020
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LPPM) Politeknik Pratama Mulia Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (446.87 KB)

Abstract

Laboratory is a very crucial place in doing practice learning. Generally, there are high value research equipment and component. It needs completing with electronic security system to improve the security system of laboratory locker user. This research will make a prototype of laboratory locker security system based on Raspberry pi biometrik and RFID. This system combines the fingerprint recognition system with fingerprint sensor R307 and the method of id matching by using RFID Card MIFARE RC522. Raspberry Pi is used as the main controller connected to database MySQL. Integration process with database is successfully done by using Python language as the device connector with database. Data of id tag from the reading result of RFID reader and scanning from sensor of fingerprint on device are successfully delivered to database and sucessfully receive reply response in the form of the user identity which is shown on LCD screen. The process takes less than five seconds as long as the device has been connected with Wifi network. The security lock system of locker box is also equipped with logger data therefore it will make investigation easy if the loss on laboratory equipment happens.
Penerapan Machine Learning untuk Pencarian Pelanggan Loyal Berpotensi Menggunakan Metode Python Pandas Seaborn Tritularsih, Yustina; Prasetyo, Hoedi
Integrasi: Jurnal Ilmiah Teknik Industri Vol 10 No 1 (2025): Integrasi : Jurnal Ilmiah Teknik Industri
Publisher : Program Studi Teknik Industri, Fakultas Teknik, Universitas Muhammadiyah Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32502/integrasi.v10i1.292

Abstract

Kunci kesuksesan berbisnis agar target penjualan tercapai dengan menjaga kepercayaan dan minat daya beli konsumen untuk tetap menjadi pelanggan setia. Salah satu faktor penunjangnya di bidang pemasaran yaitu dengan cara memprediksi untuk pencarian pelanggan loyal berpotensi. Untuk membangun model tersebut, perlu data demografi, sosial, transaksional, metrik perilaku, dan fitur pendukung lainnya. Masalah utama yang terjadi saat ini terbatasnya bagian pemasaran memiliki data pelanggan dan hanya mengandalkan informasi yang disediakan oleh sistem ERP yang sebagian besar datanya berorientasi transaksional. Tujuan utama dari penelitian ini adalah untuk mengusulkan kombinasi analisis RFM (Recency, Frequency and Monetary) dan algoritma machine learning untuk memprediksi potensi pelanggan berdasarkan sebagian besar data transaksional. Dataset diambil dari sistem ERP perusahaan sheet metal di PT.ABC. Skor RFM dihitung untuk setiap pelanggan dalam jangka waktu 6 bulan sebelum tanggal akhir pemeriksaan. Nilai target untuk model prediksi  ini adalah metrik pelanggan berpotensi yang menunjukkan apakah pelanggan telah melakukan transaksi dalam 6 bulan ke depan setelah analisis RFM atau tidak. Eksperimen dilakukan dengan metode Python Pandas Seaborn. Hasil menunjukkan batasan skor dan metrik RFM menggunakan algoritma machine learning, perusahaan dapat memprediksi pelanggan loyal berpotensi. Skor terbaik ditunjukkan pelanggan platinum cenderung berbelanja lebih sering dan lebih banyak berbelanja dibandingkan pelanggan lain.
Co-Authors Fenty Pandansari Hizkia Urianto Hoedi Prasetyo Prasetyo, Hoedi Yohanes Sugiarto