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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 226 Documents
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Analisis Harga Pokok Produksi pada Belt Conveyor dan Roller Conveyor dengan Metode Job Order Costing pada PT. XYZ Nur Laili Rahmawati; Yoniv Erdhianto
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 3 No. 4 (2025): Juli: 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.v3i4.969

Abstract

In global competition, companies must be able to set competitive selling prices. Production cost components such as raw material costs, direct labor costs, and factory overhead costs are all included in the cost of goods manufactured. This study analyzes the COGS with Job Order Costing at PT. XYZ, a make-to-order company. The study was conducted by comparing COGS with Job Order Costing between Box Roller Conveyor and Bag Stop & Go Belt Conveyor as well as material usage and outsourcing. The results of the study indicate that Job Order Costing at PT.XYZ accurately traces the contribution of material costs and outsourcing to total production costs, and evaluates efficiency and cost control on each project with different characteristics. The use of Job Order Costing shows that Bag Stop & Go Belt Conveyor has a higher COGS of Rp299,655,813 than the COGS of Box Roller Conveyor of only Rp209,740,142. The cost structure shows that outsourcing is the most dominant component, reaching more than 98% of HPP on Bag Stop & Go Belt Conveyor, while raw material costs contribute less than 3%, so it can be concluded that the outsourcing vendor management strategy greatly affects the efficiency of production costs at PT. XYZ.
RISC vs CISC: Studi Kinerja dan Efisiensi dalam Organisasi Arsitektur Komputer Achmad Maulana; Allyssa Putri; Muhamad Alif Farras Syakir; Revan Sabilillah Saputra; Maulina Diah Lestari
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 3 No. 4 (2025): Juli: 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.v3i4.973

Abstract

The evolution of computer architecture has given rise to two main approaches: RISC (Reduced Instruction Set Computer) and CISC (Complex Instruction Set Computer). These architectures differ significantly in terms of instruction design, efficiency, and performance. This study aims to analyze the performance and efficiency of RISC and CISC in the context of computer architecture organization. The methodology includes a literature review, comparative analysis, and performance evaluation based on parameters such as processing speed, power consumption, and design complexity. The results indicate that RISC tends to be more efficient in terms of power consumption and execution speed for simple instructions, while CISC excels in handling complex instructions with fewer lines of code. The findings of this study can serve as a reference for the development of modern computer architectures that balance performance and efficiency.
Penerapan Sistem Informasi dan Jaringan Komputer dalam Literasi Digital Siswa SMP MA`ARIF NU 1 Purwokerto Dinda Isna Nur Laeli; Niessye Hani Wijaya; Muhammad Izzedien Pratama; Nur Muhamad Dwi Jayanto
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 3 No. 4 (2025): Juli: 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.v3i4.976

Abstract

The rapid advancement of information technology demands that the younger generation possess adequate digital literacy from an early age. This study aims to evaluate the effectiveness of a community service activity focused on educating junior high school students at SMP Ma’arif NU 1 Purwokerto about computer systems and computer networks. The research employed a descriptive qualitative approach with data collection techniques including observation, semi-structured interviews, documentation, as well as pre-tests and post-tests. The activity involved students from classes 9A, 9B, and 9C, who participated in interactive learning sessions covering basic materials on computer systems, computer networks, and digital safety. The results indicate an increase in students' understanding of information technology concepts, as reflected by improved comprehension scores and positive responses toward the program. Students demonstrated high enthusiasm, actively engaged in discussions, and were able to explain the material presented. These findings suggest that an educational approach based on hands-on practice is effective in enhancing digital literacy among students. The implication of this activity highlights the importance of continuous technology education at the basic education level to prepare the younger generation for the challenges of the digital era and to encourage their active contribution to a technology-based society.
Analisis Klasifikasi Risiko Dropout Mahasiswa Menggunakan Algoritma Decision Tree dan Random Forest Abdah Syakiroh Gustian; Fathoni Mahardika
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 3 No. 4 (2025): Juli: 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.v3i4.980

Abstract

This study aims to develop an accurate predictive model for identifying students at risk of academic dropout using Decision Tree and Random Forest algorithms. The research utilizes a publicly available dataset sourced from Kaggle, which includes academic and demographic features such as GPA, attendance, credit load, financial aid status, and exam scores. The methodology involves several stages: data collection, preprocessing (handling missing values, encoding categorical variables, and feature scaling), model training, and evaluation using performance metrics such as Accuracy, Precision, Recall, F1-Score, and Confusion Matrix. Results show that the Random Forest algorithm outperforms Decision Tree in terms of accuracy and robustness, with notable feature importance on math, reading, and writing scores. The findings highlight the potential of machine learning in early detection of dropout risks and provide actionable insights for academic institutions to design timely interventions. This research contributes to the growing field of educational data mining and supports data-driven decision-making processes in higher education management.
Pengaruh Penambahan Volume Air dalam Cat Akrilik Terhadap Kualitas Warna Suminagashi Pada Scarf Polyester Rizki Laillatul Zakiyah; Ma’rifatun Nashikhah
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 3 No. 4 (2025): Juli: 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.v3i4.982

Abstract

Suminagashi is a technique for decorating fabric or paper by dropping ink or paint onto the surface of water or a water-gelmixture, then placing the fabric or paper on the liquid so that the color is absorbed. The study aims to examine the effect of increasing water volume in acrilylic paint on the color quality of the suminagashi technique appiled too polyester scraves, specifially in terms of color sharpness and color absorption. Additionally, it investigates the variations in color outcomes across different water-to-point ratios. An experimental method was employed using three paint-to-water ratios 1:1, 1:2, and 1:3. Color quality was evaluated through observations by 30 respondents and analyzed using the Kruskal-Wallis H test with SPSS version 30. The result indicate that the volume of water in the acrylic paint mixture significantly influences color quality. The 1:1 ratio produced the higest color sharpness, while the 1:3 ratio showed the best color absroption. Distinct color differences were observed among the scarves produced with each ratio.
Analisis Pengaruh Penggunaan Jenis Detektor Gas Metana terhadap Akurasi dan Waktu Respon di PT. Pertamina Hulu Mahakam Samsul Anwar; Aulidina Dwi Nur Indriyanti
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 3 No. 4 (2025): Juli: 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.v3i4.986

Abstract

Methane gas detection is crucial in the oil and gas sector to enhance safety and operational efficiency. This study examines the impact of three types of gas detectors—catalytic, infrared, and ultrasonic sensors—on accuracy and response time. The research was conducted at PT PHM's onshore and offshore sites to evaluate sensor performance in operational environments. A quantitative approach with direct field observation was used. Data were collected by measuring methane gas concentrations indicated by detectors, which were then compared to standard gas concentrations. Response times were recorded when the detectors were exposed to methane concentrations of 2.5% LEL until the alarm triggered at 40% of full scale. Data analysis was performed using descriptive statistics, homogeneity test, normality test, ANOVA, and post hoc tests. The results show that the infrared detector had a response time of 2.87 seconds with an accuracy of 0.218%. The catalytic detector had a response time of 8.91 seconds and accuracy of 0.489% and the ultrasonic detector had a response time of 6.15 seconds and accuracy of 0.842%. Overall, the infrared detector demonstrated the best performance in response time and is recommended for use at PT PHM.
Analisis Konsumsi Energi Listrik pada Mesin Drilling Duduk Type RYU RDB 13 Dengan Variasi Parameter Pemesinan Purwoto, Eko; Eko Yudiyanto
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 3 No. 4 (2025): Juli: 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.v3i4.998

Abstract

This study aims to analyze the electrical energy consumption of a bench-type drilling machine, RYU RDB 13, by varying machining parameters in the form of spindle speed and feed rate. Electrical energy is a critical aspect of production efficiency in the manufacturing industry, particularly in machining processes that require continuous power consumption throughout the cutting operation. The material used in this study is aluminum 6061, chosen for its lightweight, corrosion resistance, and wide application in the automotive and aerospace industries. The drilling process was carried out using three spindle speed variations: 620 rpm, 920 rpm, and 1280 rpm, along with three feed rate variations: 0.04 mm/rev, 0.08 mm/rev, and 0.1 mm/rev. Current and voltage were measured using a digital wattmeter in real-time, and energy consumption was calculated in wattseconds (Ws) using power calculation formulas. The results indicate that increasing the feed rate and spindle speed leads to higher instantaneous power consumption. However, total energy consumption tends to decrease at higher speed and feed combinations due to shorter machining times. The optimal parameter combination was found at a feed rate of 0.1 mm/rev and a spindle speed of 1280 rpm, which resulted in the lowest energy consumption of 387 Ws and the fastest drilling time. This demonstrates that selecting the right machining parameters not only improves energy efficiency but also maintains or enhances productivity. The observed power consumption pattern typically shows a sharp increase at the beginning of the drilling process, a stable phase during the main cutting stage, and a rapid decrease towards the end of the cut. These findings contribute to a better understanding of the relationship between machining parameters and energy efficiency, serving as a basis for developing sustainable production strategies in the manufacturing sector that prioritize energy savings and cost reduction.
Model Perawatan Generator di PLTU Paiton menggunakan Metode Naive Bayes Bambang Minto Basuki
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 3 No. 4 (2025): Juli: 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.v3i4.1002

Abstract

The Paiton Steam Power Plant (PLTU) is one of the main sources of electrical energy in East Java, which plays a vital role in maintaining a sustainable electricity supply. The reliability of generator units is a key element in maintaining stable energy distribution. However, the high frequency of sudden generator failures poses serious challenges, such as increased downtime and increased maintenance costs. To address these challenges, this study aims to design a generator maintenance prediction model based on the Naive Bayes algorithm with a predictive maintenance approach. This study uses historical maintenance data and key sensor parameters such as temperature, oil pressure, and vibration as input. The data is analyzed through several stages, namely data preprocessing, selection of relevant features, and labeling generator conditions into three categories: Normal, Warning, and Critical. The Naive Bayes model is trained to classify the data probabilistically to generate predictions of future generator conditions. Model evaluation using accuracy metrics and a confusion matrix shows that the model successfully achieved an accuracy rate of 89% and was able to provide early warnings of potential failures up to 3 days before failure occurs. The implementation of this system is expected to support the shift in maintenance strategies from reactive and scheduled systems to data-driven predictive systems. Implementing failure predictions allows the technical team at the Paiton PLTU to conduct planned maintenance, avoid sudden disruptions, and extend equipment lifespan. Thus, this model has the potential to reduce operational downtime by up to 25%, while providing significant savings in operational and logistics costs. This research also shows that integrating machine learning technology into energy facility management can improve the efficiency and resilience of the overall electric power system.
Perancangan Front End Tampilan Aplikasi Pendeteksi Sayuran Berbasis Android Maulana Mahessar; Isram Rasal
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 3 No. 4 (2025): Juli: 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.v3i4.1008

Abstract

This research focuses on the development of an Android-based vegetable detection application by utilizing digital image processing technology and data communication through Application Programming Interface (API). This application is designed to make it easier for users to visually recognize different types of vegetables using the device's camera. The detection process is carried out by sending the image to a cloud server, where the image analysis process is carried out to identify the type of vegetable, displaying its name, characteristics, and benefits. The app's implementation includes an intuitive and user-friendly user interface, with key features such as login, registration, and an interactive dashboard. The dashboard displays user information, location, ambient temperature, vegetable detection history, and direct access to the camera for real-time detection processes. The utilization of cloud computing technology not only keeps application performance lightweight and responsive, but also enables high processing efficiency and data scalability. This allows the application to continue to evolve according to the increasing number of users and incoming data. Image processing is done with machine learning algorithms that are trained to recognize the shape, color, and texture of different types of local vegetables. In addition, this system is also equipped with a periodic data update feature to be able to adjust to the development of new vegetable classifications. The test results show that the app is able to recognize different types of vegetables with a high level of accuracy, as well as provide additional relevant information quickly and accurately. Tests are carried out on a variety of lighting and background conditions to ensure the reliability of the system. The success of the development of this application reflects the integration of modern technology in supporting the digital agriculture sector.
Analisis Efektivitas Perawatan Preventif Menggunakan OEE dan Six Big Losses Pada Mesin Simplex di PT. XYZ Adinda Rosmalia; Priyo Ari Wibowo; Rikzan Bachrul Ulum
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 3 No. 4 (2025): Juli: 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.v3i4.991

Abstract

This study aims to analyze the effectiveness of preventive maintenance on the Simplex machine at PT. XYZ by applying the Overall Equipment Effectiveness (OEE) method and identifying the primary causes of production losses through the Six Big Losses framework. Preventive maintenance is an important strategy to ensure machine reliability, reduce downtime, and improve production efficiency. OEE is a widely recognized performance measurement tool consisting of three key indicators: Availability, Performance, and Quality. These indicators collectively reflect the overall effectiveness of equipment in supporting the production process. The results of this study indicate that the OEE value of the Simplex machine is 79%, which remains below the world-class benchmark of 85% as recommended by the Japan Institute of Plant Maintenance (JIPM). This finding suggests that the machine’s performance has not yet reached the optimal standard and requires improvement efforts. Further analysis using the Six Big Losses approach reveals that the most significant contributors to reduced machine effectiveness are equipment failure and idling or minor stoppages. These two categories account for the majority of productivity losses, thereby affecting both machine utilization and production output. To further explore the underlying issues, a root cause analysis was conducted using a fishbone diagram, which enabled the identification of several critical factors related to human resources, methods, machines, materials, environment, and measurement systems. Based on this analysis, improvement proposals were developed through the 5W+1H method, providing a systematic strategy to enhance preventive maintenance practices. The recommended actions include scheduling more frequent inspections, improving operator training, upgrading spare parts management, and implementing stricter monitoring of machine performance. In conclusion, this study highlights the importance of continuous preventive maintenance to optimize machine productivity and reduce unplanned downtime. By adopting the proposed improvement strategies, PT. XYZ can increase the effectiveness of its Simplex machine, moving

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