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FAKULTAS SAINS DAN TEKNOLOGI UIN SULTAN SYARIF KASIM RIAU Kampus Raja Ali Haji Gedung Fakultas Sains & Teknologi UIN Suska Riau Jl.H.R.Soebrantas No.155 KM 18 Simpang Baru Panam, Pekanbaru 28293
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SITEKIN: Jurnal Sains, Teknologi dan Industri
Published by Universitas Islam Negeri Sultan Syarif Kasim Riau
ISSN : 24070939     EISSN : 27212041     DOI : https://doi.org/10.24014/sitekin.v18i1.12062
Core Subject : Economy, Science, Education, Engineering,
Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Industrial & Manufacturing Engineering Other
Sesuai dengan standard ISO 45001 bahwa karyawan harus berpartisipasi dalam melakukan pencegahan kecelakaan. Untuk itu perusahaan telah menetapkan Program Hazob (Hazard Observation) untuk mengidentifikasi bahaya dan melakukan tindakan koreksinya. Penerapan Program Hazob masih dengan metode konvensional, mengisi lembar form, sehingga tidak efektif, efisien dan tidak berintegrasi dengan sistem lain. Transformasi digitalisasi diperlukan dengan merubah bisnis proses pelaporan dari konvensional ke aplikasi website atau mobile Apps. Hasil dari penelitian ini terjadi peningkatan kinerja operasional keselamatan kerja dengan program Hazob (i) pengisian form secara manual bertransformasi ke system digitalisasi aplikasi website dan mobile Apps; (ii) leading indikator pelaporan hazob meningkat menjadi 1.364 dari seluruh lokasi. Ini bermakna, bahwa perusahaan telah mengidentifikasi bahaya sejumlah tersebut dalam kuran waktu 3 bulan, dan melakukan tindakan koreksi sebelum terjadi kecelakakan. Data persentasi kontribusi menunjukan bahwa semua pihak bagian di perusahaan berkontribusi untuk melakukan pelaporan hazob. Hal ini menunjukan komitmen semua tingkatan untuk melakukan pecegahan kecelakaan. Angka terbesar pada tingkatan karywan ( 63 %) berkontribusi ; (iii) dampak implementasi berupa tingkat penurunan angka kecelakaan dengan Lagging Indikator sebagai berikut : LTIR = 0 (Nol), TRIR, yang sebelumnya 0.87 di bulan juni, turun menjadi 0 (nol) dari bulan Juli sampai September 2020, dan IFT, turun terus setiap bulan dan di bulan September di angka 12.33.
Arjuna Subject : Bisnis, Menejemen, dan Akutansi (semua kategori) - Strategi dan Menejemen
Articles 607 Documents
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Measuring the risk level of worker discomfort due to computer use using the ROSA method Nugroho, Zhafif Radithya; Rizka Aulia, Baiq Putri; Firjatullah, Aji Adinata; Annisa, Putri Dwi
SITEKIN: Jurnal Sains, Teknologi dan Industri Vol 22, No 2 (2025): June 2025
Publisher : Fakultas Sains dan Teknologi Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/sitekin.v22i2.32957

Abstract

Computer work carried out for long periods of time can increase the risk of musculoskeletal disorders (MSD) in workers. Working posture is important to increase work productivity among workers. Unergonomic posture is one of the main factors causing MSD. This research aims to analyze risks to computer workers using the Rapid Office Strain Assessment (ROSA) method and provide recommendations for improvements to improve work compatibility. The Rapid Office Strain Assessment (ROSA) method is used to determine the risk value of work activities that use computers and sitting posture. The research results obtained showed that office employees were categorized as requiring further assessment and required follow-up action. Office employees have risky working postures and experience muscle complaints. Based on these results, there are several recommendations such as engineering controls and administrative controls.
Smarthome Design Using Raspberry Pi 3 Based on Internet Of Things (IoT) Putra, Urief Arsani Atma; Syamsul Irfan Akbar, L Ahmad; Ramadhani, Cipta
SITEKIN: Jurnal Sains, Teknologi dan Industri Vol 22, No 2 (2025): June 2025
Publisher : Fakultas Sains dan Teknologi Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/sitekin.v22i2.37496

Abstract

Advances in Internet of Things (IoT) technology have driven the development of smart, efficient, and widely accessible home automation systems. This study aims to determine how to design and integrate Raspberry Pi technology with Bylnk to control relays remotely manually using widgets and automatically using LDR and DHT11 sensors. The research method employs an engineering research approach focused on the design, development, and testing of a prototype smart home system based on the Internet of Things (IoT) using Raspberry Pi 3. The process begins with a literature review on IoT concepts and Raspberry Pi characteristics, followed by the design of hardware and software that integrates the Raspberry Pi 3, LDR and DHT11 sensors, a four-channel relay module, and the Blynk platform for the user interface. After assembly, the system is tested through experimental scenarios observing LED responses to four input conditions: light intensity, ambient temperature, automatic timer, and manual commands via the Blynk app. The collected data is quantitative observational, including LED status (on/off), response time, and analyzed descriptively and comparatively by comparing actual results against the success criteria established in the design. The test results show that the system operates reliably in executing each control function, both automatic and manual, with fast and accurate responses. This research contributes to the development of a modular, cost-effective, and easily implementable smart home system in real residential environments.
Risk Management Approach in Solar Power Plant Projects Using the SLR Method Agistin, Veriza; Whardani, Putri Nurul Kusuma; Nasution, Soraya Muthma Innah; Revolis, Messa; Sahti, Armia Lara
SITEKIN: Jurnal Sains, Teknologi dan Industri Vol 22, No 2 (2025): June 2025
Publisher : Fakultas Sains dan Teknologi Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/sitekin.v22i2.37273

Abstract

Utilizing solar energy is among the renewable energy sources that are both abundant and kind to the environment. Therefore, the development of Solar Power Plants (PLTS) in Indonesia continues to grow as part of the clean energy transition and efforts to meet national renewable energy targets. However, solar power plant (PLTS) projects face various risks ranging from technical risks, resource risks, environmental risks, social and community risks, economic risks, occupational health and safety risks, to regulatory and legal risks that can hinder their success and efficiency in implementation, necessitating risk management. Structured risk management is crucial for ensuring that the solar power plant project can operate efficiently, safely, and sustainably. This research was conducted to identify the most significant risks in a solar power plant construction project using a qualitative method through a systematic literature review approach. Then, the findings from previous studies were synthesized to provide a comprehensive overview by identifying and classifying the main risks documented in the literature. This research aims to enhance the development of policies and risk management strategies for renewable energy initiatives in Indonesia
Design and Implementation of a Machine Learning-Based Adaptive IDS on Raspberry Pi for Smart Home Network Security Adrian, Ronald; Mandasari, R. Deasy; Alam, Sahirul
SITEKIN: Jurnal Sains, Teknologi dan Industri Vol 22, No 2 (2025): June 2025
Publisher : Fakultas Sains dan Teknologi Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/sitekin.v22i2.33485

Abstract

The rapid growth of the Internet of Things (IoT) has accelerated the adoption of smart home technologies, offering convenience and automation in daily life. However, this interconnected environment increases the risk of cyber threats, making information security a pressing concern. To address this, the study presents the design and implementation of an adaptive Intrusion Detection System (IDS) based on machine learning, deployed on a Raspberry Pi platform as a low-cost, flexible, and energy-efficient solution for smart home security. Unlike traditional IDS approaches that rely on static, rule-based detection, the proposed system leverages adaptive learning algorithms to identify evolving attack patterns in real time. It integrates network traffic monitoring with carefully selected sensors and detection algorithms to improve responsiveness across various threat types from application-level exploits to network infrastructure attacks. System performance was evaluated through simulated attacks, including DDoS, brute force, and malware injection scenarios. Results show that the adaptive IDS significantly improves detection accuracy to 85%, surpassing the 65% accuracy achieved by conventional methods. The response time was also reduced from 5 seconds to just 2 seconds, demonstrating the system’s suitability for real-time threat mitigation in resource-constrained environments. The Raspberry Pi acts as the IDS host and a firewall enhancement tool, supporting custom iptables rules, whitelist-based access control, and integration with the Elastic Stack for real-time logging and visualization. The system also supports continuous learning by updating its detection models based on new traffic patterns, making it scalable and resilient to future threats. This research contributes to IoT cybersecurity by demonstrating that an adaptive, machine learning-based IDS can be effectively implemented on lightweight hardware without sacrificing performance. It offers a cost-effective and scalable solution to secure smart home networks against increasingly sophisticated cyberattacks.Keywords: Firewall, IDS, IoT, Raspberry, Smart Home
Analysis of Spare Parts Inventory Planning for Machinery with Monte Carlo Simulation, Reorder Point, and Safety Stock Farisan, Fahreza; Purba, Arini Anestesia; Arham Pratikno, Faishal
SITEKIN: Jurnal Sains, Teknologi dan Industri Vol 22, No 2 (2025): June 2025
Publisher : Fakultas Sains dan Teknologi Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/sitekin.v22i2.36921

Abstract

PT. XYZ is a company engaged in the management of mall buildings. The implementation of operations in malls often experiences obstacles, namely the availability of machine spare parts which is less than 95% of the standard inventory availability. The impact of this problem is the ability of PT. XYZ in meeting the needs of consumers. The results of observations and interviews with supervisors show that there is a lack of stock of escalator spare parts, especially for Sigma brands such as Ballasstrude Newel Chain Roller Escalator Sigma Vera, Roller Press Handrail (70x60) Sigma Ares, Roller Press Handrail Escalator Sigma Vera and Roller Step ESC Sigma (6204). This study compares three forecasting methods: exponential smoothing, linear regression, and Monte Carlo simulation. The stages of the research consist of problem identification, determination of data patterns, inventory planning with montecarlo simulations, raw material planning with safety stock and reorder points. The results of this study were obtained that the best method to handle this case was Monte Carlo simulation because it has a high level of accuracy compared to other methods. The accuracy result obtained was a Mean Absolute Percentage Error (MAPE) of 17.03%. The results of the Montecarlo simulation obtained safety stock of 9-16 units and reorder points of 18-28 units. This research can reduce delays in fulfilling production demand, if safety stock and reorder point policies can be implemented.
Muslimah's Purchase Interest in Halal Cosmetic Products through E-Commerce Platforms: Analysis of Supporting Factors Afiatna, Fatma Ayu Nuning Farida; Muflihah, Nur; Mayasari, Andhika; Sumarsono, Sumarsono; Nudin, Salamun  Rohman
SITEKIN: Jurnal Sains, Teknologi dan Industri Vol 22, No 2 (2025): June 2025
Publisher : Fakultas Sains dan Teknologi Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/sitekin.v22i2.33887

Abstract

This research investigates the various factors that affect the purchasing intentions of Muslim women regarding halal grooming and cosmetic products in an online context. Drawing upon the theory of planned behaviour, the study evaluates how attitudes, subjective norms, and perceived behavioural control contribute to these purchasing intentions. Furthermore, this study examines the role of religiosity as a moderating variable that influences the interplay among attitudes, subjective norms, perceived benefits, and risks in relation to buy intention. Notably, religiosity has demonstrated significant moderating effects across various contexts, encompassing self-regulation, mental health, ethical behaviour, brand compliance, and overall well-being. The observed effect intimates that religiosity possesses the potential to either amplify or mitigate the influence of independent variables on the anticipated outcome, contingent upon the specific contextual nuances and an individual's subjective religious interpretation. Employing a convenience sampling methodology, the research disseminated questionnaires electronically through digital communication platforms including WhatsApp, Telegram, and Facebook, targeting respondents who had attained a minimum age of 18 years. The subsequent data analysis was rigorously conducted utilising Structural Equation Modeling (SEM) via the Partial Least Squares approach (SEM-PLS). The empirical findings reveal a statistically significant correlation among religiosity and the buy intention of halal products, thereby underscoring the profound significance of religious values in shaping the consumer decision-making processes of Muslim women.
Proposed Scheduling of Preventive Maintenance on Co₂ Welding Machines Based on Reliability Analysis and FMEA Methods at PT. Sub Automotive Umar Dana, Rizko; Suhara, Ade; Roban, Roban; Sayuti, Muhamad
SITEKIN: Jurnal Sains, Teknologi dan Industri Vol 22, No 2 (2025): June 2025
Publisher : Fakultas Sains dan Teknologi Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/sitekin.v22i2.37605

Abstract

As the industry increases its dependence on production machinery, machine maintenance is a vital aspect in ensuring the smooth operation of the company. PT. Sub Automotive, as a dump truck carousel manufacturer, faces the problem of high downtime in CO₂ welding machines caused by component damage. This research aims to design an appropriate preventive maintenance schedule to reduce the frequency of damage and increase machine availability. The methods used include Mean Time Between Failure (MTBF), Mean Time To Repair (MTTR), and Overall Availability (Ao) analysis, as well as the Failure Mode and Effect Analysis (FMEA) approach to identify critical components based on the Risk Priority Number (RPN) value. The results showed an average machine availability value of 97%, exceeding the global standard of 90%. The components with the highest RPN values, namely the Control PCB (180), Nozzle (168), and Contact Tip (126), were identified as the main contributors to downtime. Based on these results, preventive maintenance recommendations were prepared focused on these components to improve the overall reliability of the system
Property Price Prediction Using the Random Forest Regression Algorithm Utami, Putri; Jundi, Muhamad; Rahmaddeni, Rahmaddeni; Sinaga, Leonardo
SITEKIN: Jurnal Sains, Teknologi dan Industri Vol 22, No 2 (2025): June 2025
Publisher : Fakultas Sains dan Teknologi Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/sitekin.v22i2.35804

Abstract

This study uses an innovative approach to predicting property prices using machine learning with the Random Forest Regression method. The dataset was obtained from Kaggle and consists of 500 rows with 12 attributes, comprising 10 numerical attributes and 2 categorical attributes. The evaluation results, calculated using the R² score on the test dataset, show strong performance, achieving the highest R² score of 81.88% with a dataset split ratio of 90:10. The scatter plot visualization indicates shows the model's predictions often correspond closely with the actual values, showing strong accuracy, despite a tiny gap between the anticipated and real values. The graph comparing the training data and the actual data shows no significant signs of overfitting or underfitting, demonstrating the Random Forest Regression model's strong accuracy in predicting house prices and its capacity to effectively capture the relationship between independent and dependent variables.
Analysis of Causes of Fleet Delays to Stuffing Locations (On Time Pick-Up) Using the Root Cause Analysis (RCA) Method (Case Study of Logistics Company in Surabaya) Purba, Ari Pranata Primisa; Salsabila, Selvin; Zahrina, Nadhilah
SITEKIN: Jurnal Sains, Teknologi dan Industri Vol 22, No 2 (2025): June 2025
Publisher : Fakultas Sains dan Teknologi Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/sitekin.v22i2.35849

Abstract

PT ABC Logistics is a company engaged in logistics services, especially providing truck and container services for land transportation. This company operates various types of trucks, including 20 feet, 40 feet, 21 feet, CDD, CDE, Fuso, and Tronton trucks. In carrying out its operations, as a logistics company, it must plan fleet needs accurately to fulfill each order. However, problems are still found in the form of fleet delays when heading to the stuffing location to the customer. To overcome this problem, the Root Cause Analysis (RCA) method is used to identify the root of the problem and reduce potential delays. The approaches applied include the use of Pareto Diagrams, Fishbone Diagrams, Failure Mode and Effect Analysis (FMEA), and proposing improvements using the 5W + 1H method. The results of the analysis show two main factors causing delays, namely fleet wait and container shortage. Priority improvements for fleet wait include optimizing route plans that have not been updated, incompatibility between delivery times and slot times, and lack of communication between the company and vendors. Meanwhile, to overcome delays due to container shortages, the focus of improvements is focused on improving communication systems, repairing damaged containers (such as leaks or holes), and optimizing communication between vendors and companies.
Construction Project Scheduling Optimization with Critical Path Method (CPM) and Precedence Diagram Method (PDM) (Case Study: PT Samara Insan Sentosa) Aji, Nuke Maheswara; Nindiani, Aina; Tri Sasmi, Weni; Fadli Perdana, Mohammad
SITEKIN: Jurnal Sains, Teknologi dan Industri Vol 22, No 2 (2025): June 2025
Publisher : Fakultas Sains dan Teknologi Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/sitekin.v22i2.37258

Abstract

Delays in construction projects often occur due to suboptimal scheduling, which results in increased costs and decreased efficiency. PT Samara Insan Sentosa faces a similar problem, where the planned project duration does not match the realization in the field. This study aims to optimize project scheduling using the Critical Path Method (CPM) and Precedence Diagram Method (PDM). The research methods used include secondary data analysis, interviews, and scheduling calculations with both methods. The results of the study show that CPM and PDM can identify critical paths and optimize project completion duration. A comparison of the two methods shows that PDM is more flexible than CPM, with a shorter project completion duration. Implementation of the PDM method can reduce project completion time without sacrificing the quality of work. The conclusion of this study is that scheduling optimization using the right method can increase project efficiency and reduce the risk of delays. The impact of this study can help companies improve the effectiveness of project management.

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