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Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika
Published by Asosiasi Riset Ilmu Teknik Indonesia
ISSN : 3031500X     EISSN : 3031349X     DOI : 10.61132
Core Subject : Science, Engineering,
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering
open Industrial Engineering Science Cluster Research journal. This journal is a peer-reviewed and open research journal of the Engineering Science Clump
Arjuna Subject : Teknik (semua kategori) - Tenik Industri dan Manufaktur
Articles 237 Documents
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Analisa Risiko K3 dengan Metode Job Safety Analysis (JSA) dan Risk Assessment pada Proses Mesin Sizing di PC GKBI Medari Sleman Muh. Dawami Sholichin; Yunita Primasanti; Erna Indtriastiningsi; Bekti Nugrahadi; Anita Oktaviana Trisna
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 3 No. 2 (2025): Maret: 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.v3i2.781

Abstract

Occupational Health and Safety (OHS) is a crucial aspect of the textile industry to ensure worker protection and maintain smooth production processes. This study aims to identify and analyze potential occupational accident risks in the sizing machine process. The methods used in this research are Job Safety Analysis (JSA) and Risk Assessment to evaluate workplace hazards that may disrupt operations. The results indicate several major risks in the sizing process, including mechanical hazards due to direct contact with machines, ergonomic hazards caused by improper working postures, and chemical hazards from exposure to cotton dust and sizing solution vapors. The main risk factors include human aspects, the work environment, and machinery. The recommended improvements in this study include enhancing work supervision and control, providing safety training for workers, optimizing workplace ergonomics, and conducting regular machine maintenance to reduce accident risks. The proper implementation of safety strategies is expected to improve production efficiency and create a safer and more conducive work environment.
Desain dan Implementasi Sistem Penyiraman Otomatis Berbasis IoT Menggunakan Mikrokontroler ESP Diyajeng Luluk Karlina
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 3 No. 2 (2025): Maret: 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.v3i2.762

Abstract

This research develops a prototype of an automatic watering device based on the Internet of Things (IoT) and a soil moisture sensor to improve the efficiency of watering crops in agricultural fields. The main problem addressed is the consistency and efficiency of watering in large agricultural fields, where traditional management is prone to human error and inefficient water use. The developed prototype uses an ESP8266 microcontroller (NodeMCU) as the brain of the system connected to a Wi-Fi network, allowing remote monitoring and control via the Blynk application. A soil moisture sensor is used to detect soil conditions in real-time, triggering watering only when needed. This helps optimize water use and increase agricultural productivity sustainably. This research outlines the methodological steps from design, manufacturing, to implementation of the prototype in the field. Evaluation of the results shows that the system successfully regulates watering effectively based on soil conditions, with positive responses from farmers as end users.
Percepatan Proyek pada Schedule Penjadwalan Kapal Perang dengan Precedence Diagram Method di Perusahaan Galangan Kapal Surabaya Pratama, Deflin Riendra; Waluyo, Minto
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 3 No. 2 (2025): Maret: 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.v3i2.766

Abstract

The Shipyard Company is a company that operates in the shipping sector, including ship production, overhaul and ship maintenance. In this case, the Shipbuilding Company has an important role in providing quality and timeliness in every project that has been accepted. Quality and timeliness are closely related to the planned production schedule, with efficient and effective scheduling it will have an impact on the quality results and production progress carried out, and cut excess production costs. Based on these needs, an analysis was carried out using the Precedence Diagram Method (PDM) on the Install Machinery Engine Deck 1 sub-job on the Warship project. The data needed in this research is the work breakdown structure (WBS). Based on the analysis that has been carried out, it was found that the most efficient path was found by eliminating dummy factors, so that work can be carried out simultaneously without waiting for previous work. In this case, it was found that the processing time for the Install Machinery Engine Deck 1 work on the Warship project was 471 days, compared to 657 days previously. Thus, the conclusion of this research is that the PDM method schedule has more efficient results than previous planning.
Pemilihan Supplier Urea Menggunakan Metode Analytic Network Process : (Studi Kasus di PT. Delta Setia Sandang Asli Tekstil 1) Anindya Manggar Iwarani; Yunita Primasanti; Bekti Nugrahadi
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 3 No. 2 (2025): Maret: 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.v3i2.791

Abstract

Supplier selection is a strategic element in supply chain management to ensure operational efficiency and business sustainability. This study aims to determine the best urea supplier for PT DSSA 1, a textile company specializing in dyeing and finishing processes, using the Analytic Network Process (ANP) method. This method was chosen for its ability to systematically analyze interdependencies among criteria, leading to more accurate and comprehensive decision-making. Data were collected through direct observation, in-depth interviews with internal company sources, and relevant literature reviews. The analysis was based on five main criteria: quality, price, service, delivery, and flexibility, each further broken down into sub-criteria. The results indicate that quality is the most critical criterion, with the highest weight of 23.19%, followed by price, service, and delivery, each with relatively balanced weights of 19.93%. Flexibility, although ranked last with a weight of 17.01%, remains relevant, especially for urgent orders. Based on the analysis, Supplier A was identified as the best choice with the highest overall weight, followed by Supplier B and Supplier C. This study provides practical contributions by offering strategic recommendations for PT DSSA 1 in selecting suppliers that support production efficiency and business sustainability. The study is limited in the scope of criteria and the number of suppliers analyzed. Future research is recommended to explore more variables, expand the sample size, and consider the implementation of digital technologies to optimize the supply chain.
Rancang Bangun Alat Pemotong Kerupuk Terasi dengan Menggunakan Senar Gitar Muhamad Zainudin; Jaelani Jaelani; Fitri Nur Fauziah
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 3 No. 2 (2025): Maret: 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.v3i2.792

Abstract

Crackers are a typical Indonesian food that is very popular with various groups because of its crunchy texture and distinctive savory taste. One type of cracker that is often found is shrimp paste crackers, which are made from flour with the addition of shrimp paste, spices, and raising agents. In the production process, sophisticated technology is needed to increase production efficiency so that it can save energy, time, and costs. However, production equipment produced by factories is often expensive and difficult for the public to reach. Therefore, appropriate technology has emerged that is designed to help the community, one of which is a manual cracker cutter. This tool is designed to speed up and simplify the process of cutting crackers with uniform cutting results, namely 2-5 mm thick. Based on the trial, the cracker cutter using guitar strings showed significant time efficiency compared to a kitchen knife. The total cutting time with a kitchen knife reached 6 minutes 88 seconds, while using a cutter only took 42 seconds, with a time difference of 6 minutes 18 seconds. These results show that a manual cracker cutter based on guitar strings can increase efficiency and productivity in the cracker production process.
Pengembangan Model Deep Learning LSTM dan CNN untuk Peramalan Penjualan Sepeda Motor di Indonesia Yohanes Anton Nugroho; Hotma Antoni Hutahaean
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 3 No. 2 (2025): Maret: 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.v3i2.795

Abstract

Accurate sales forecasting is essential for stakeholders to make strategic decisions. This study aims to compare the performance of two deep learning models, namely Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN), in forecasting domestic motorcycle sales produced by AISI member manufacturers. The forecast is based on historical data from January 2021 to December 2024. The model was trained using time series data and the forecasting results for the period January to March 2025 were evaluated using the metrics Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE). The results show that the LSTM model produces lower MAE and MAPE values than CNN, which shows its superiority in providing more accurate and consistent predictions. On the other hand, the CNN model has lower RMSE and MSE values, thus being able to reduce large prediction errors. By comparing the results of LSTM, CNN, and actual data forecasting, the LSTM model is more suitable for forecasting motorcycle sales in Indonesia
Transformasi Digital dalam Warehouse Management: Eksplorasi Faktor Kunci Keberhasilan Implementasi Teknologi Internet of Things (IoT) pada Sistem Penyimpanan Barang Steven Andreas Gunawan
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 3 No. 2 (2025): Maret: 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.v3i2.798

Abstract

Digital transformation through Internet of Things (IoT) in warehouse management represents a paradigmatic revolution in contemporary logistics systems. This research comprehensively explores the complexity of IoT implementation, analyzing critical factors influencing digital transformation in storage systems. Utilizing a systematic literature review methodology, the research unveils multidimensional dynamics involving complex interactions between advanced technology, organizational structures, and human resources. Findings indicate that successful IoT implementation requires a holistic approach that transcends mere technological adoption, demanding a fundamental reconstruction of business ecosystems. Key factors include top management support, sustainable infrastructure investment, human resource competency development, and innovation culture creation. The research affirms that digital transformation is not simply a technological project, but a complex strategic journey requiring long-term commitment and sustainable adaptive capabilities. Research implications provide profound insights for academics and practitioners in designing effective digital transformation strategies in warehouse management.
Perbandingan SQL dan NoSQL: Studi Literatur Tentang Keunggulan, Kelemahan, dan Penerapannya Chandra Ramadhan; Mamok Andri Senubekti; Suhendri Suhendri
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 3 No. 3 (2025): Mei : 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.v3i3.785

Abstract

A database is a fundamental element in an information system that is used to manage and store data. Two commonly used database types are NoSQL (Not Only SQL) and SQL (Structured Query Language). SQL uses a structured relational model with a fixed schema, while NoSQL is more flexible with various storage models such as document, key-value, column-width, and graph. This research aims to conduct a literature study on the comparison of these two types of databases, including their advantages, disadvantages, and applicability in various information system scenarios. The study results show that the choice between SQL and NoSQL is highly dependent on the specific needs of the application, in terms of performance, scalability, and data complexity.
Perbandingan Xgboost dan Logistic Regression dalam Memprediksi Credit Card Customer Churn Rearizth Muhammad Daffaa; Deris Santika; Fathoni Mahardika
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 3 No. 3 (2025): Mei : 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.v3i3.807

Abstract

With the times, cash transactions that used to use cash are now turning to credit cards. However, the increasing use of credit cards presents challenges, especially in maintaining customer loyalty. Customer churn is the loss of customers within a certain period for various reasons. Logistic Regression is a machine learning algorithm that studies the relationship between a dependent variable and several independent variables and Extreme Gradient Boosting (XGBoost) is a Gradient tree-boosting algorithm that offers out-of-core learning and sparsity awareness.The purpose of this study is to compare the performance between Logistic Regression and Extreme Gradient Boosting (XGBoost) algorithms in predicting customer churn in credit card services using evaluation metrics such as accuracy, precision, recall, and F1-score. Based on the research results, it can be concluded that XGBoost has better performance in all evaluation metrics, both in terms of precision, recall, F1-score, and accuracy. Based on the research, XGBoost shows superior performance compared to Logistic Regression in all evaluation metrics.
Rancang Bangun GPS Tracker di Kapal dengan Menggunakan Internet of Things (IoT) Muchammad Muzammil Arrozak; Antonius Edy Kristiyono; Prihastono Prihastono
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 3 No. 3 (2025): Mei : 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.v3i3.822

Abstract

This study aims to design and develop a GPS tracking system for ships integrated with Internet of Things (IoT) technology. The system enables real-time ship position monitoring via the Telegram application by utilizing ESP32, SIM800L, and GPS Neo 6M modules. The research employs an experimental method with both static and dynamic testing of hardware components such as GPS modules, SD cards, and battery performance. The test results demonstrate that the system successfully transmits accurate coordinate data to Telegram and logs the location on the SD card module. This system is expected to serve as an alternative solution to improve ship tracking security and efficiency, particularly in emergency situations or AIS signal loss.

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