MUSTEK ANIM HA

Analysis of the Effect of Rumble Strips on Vehicle Speed and Level of Service When Approaching a Hazard Zone on Langko, Mataram City

2026-08-20T09:07:10+09:00

The rapid development of Mataram City has increased traffic density, making road safety facilities such as rumble strips necessary to improve driver awareness and safety. This is due to the increase in traffic accidents in Mataram City, which reached 637 cases in 2025. This study aims to determine the effect of rumble strips on vehicle speed and the level of service when entering a hazard zone. The study was conducted over three days: Monday, May 18, 2026; Wednesday, May 20, 2026; and Saturday, May 23, 2026. This study employed a quantitative descriptive method by analyzing data using PKJI 2023 through processing the survey data that had been collected, and the level of effectiveness was determined based on the increase and decrease in the average vehicle speed before and after passing the rumble strips. The results showed that the highest traffic volume occurred on Wednesday, reaching 2,854.20 pcu/h. The average vehicle speed before passing the rumble strips was 32.05 km/h, while the average vehicle speed after passing the rumble strips was 40.10 km/h. Furthermore, the highest level of service result obtained a q/C ratio of 0.61, which is classified as Level C, with the description, “Stable traffic flow, but operating speed begins to be restricted by traffic conditions.” The analysis of the effect of rumble strips on vehicle speed on Langko Road showed a decrease in vehicle speed before passing the rumble strips compared to after passing the rumble strips.

Analysis of the Effect of Substituting Paving Block Waste as Coarse Aggregate on the Compressive Strength of Concrete

2026-08-24T21:40:50+09:00

Demand for concrete as primary building material has increased in Indonesia alongside the ongoing expansion of infrastructure development, the components of concrete rely on natural resources, specifically natural aggregates, which are a finite resource. Similarly, constructuction waste continues to accumulate, according to Law No. 18 of 2008 on waste Management, 3R (Reduce, Reuse, Recycle). This study aims to evaluate the impact of substituting paving block waste as a coarse aggregate substitute on the compressive strength of concrete with a target of f’c=25 Mpa. Material testing, mix design (variations of 0%, 5%, 10%, 15%, 20%), casting of cylindrical test specimens measuring 150x300 mm, concrete curing, and compressive strength testing at 14 and 28 days were conducted in accordance with SNI. The results showed a decrese in compressive strength at 14 days (with the lowest value of 15.7 Mpa in the 5% variation and the highest result of 24,5 Mpa in 0% variation). There was a significant increase in the value at 28 days, with the 20% substitution reaching 25 Mpa. A 20% substitution of paving block waste yields optimal results for sustainable concrete, reduces hazardous constraction waste such as heavy metals, and open opportunities for environmental friendly application.

Improving Fabric Cutting Efficiency and Quality Through Automation At PT Apparel One Indonesia 3

2026-08-26T23:26:25+09:00

The manual fabric preparation and cutting process in the pre-production warehouse area of PT Apparel One Indonesia 3 leads to cycle time delays, high defect rates (dirty cuts, slanted cuts, and size discrepancies), and financial losses for the company. This study aims to design, implement, and evaluate the effectiveness of an automated dual-function fabric cutting machine (roll-to-roll and roll-to-sheet) based on digital sensors to replace manual methods in the warehouse area. The research adopts a structured four-stage approach: baseline data collection, root cause analysis using fishbone diagrams, 5 Whys, and a 5W+2H matrix, machine design and implementation, and comparative evaluation (before-after) of operational parameters. Operational trial results over three months (October–December 2025) demonstrate that the automated machine significantly enhanced cutting speed by 125%, increasing from 80 m/hour to 180 m/hour. Furthermore, accumulated fabric defects were drastically reduced by 98.1%, dropping from 126.25 m to only 2.4 m. The implementation of this automation innovation proves successful in achieving cutting size standardization while delivering a positive economic impact with cost savings of IDR 23,277,000 from material waste reduction.

Comparative Analysis of Self-Training XGBoost and Label Propagation for Blue Tourism Sentimen Analysis in Lampung Province

2026-08-29T22:04:52+09:00

Blue tourism in Lampung Province is one of the tourism sectors with significant potential to support regional economic development. Tourists' perceptions of tourism destinations can be analyzed through reviews published on various digital platforms, such as Twitter/X, Instagram, and Google Maps Reviews. However, the limited availability of labeled data presents a major challenge in developing sentiment analysis models, making it necessary to employ approaches that can utilize both labeled and unlabeled data simultaneously. This research aims to compare the performance of the XGBoost-based Self-Training method and Label Propagation within a Semi-Supervised Learning approach for sentiment classification of blue tourism reviews in Lampung Province. The dataset consists of 3,947 reviews, including 500 labeled data and 3,447 unlabeled data. The research process includes text preprocessing, feature extraction using TF-IDF, partitioning labeled data into training and testing subsets with an 80:20 ratio, model training, and performance evaluation based on accuracy, precision, recall, and F1-score metrics. The trial outcomes show that XGBoost-based Self-Training reached 83% accuracy, 83.14% precision, 83% recall, and 82.98% F1-score. Conversely, Label Propagation yielded 55% accuracy, 71.31% precision, 55% recall, alongside a 50.11% F1-score. These findings demonstrate that the XGBoost-based Self-Training method outperforms Label Propagation, making it a more effective approach for sentiment classification of blue tourism reviews within a Semi-Supervised Learning framework.

The Influence of Sheet Laminating Machine on the Quality of Wood Products

2026-08-29T22:10:51+09:00

Sheet lamination is a common finishing method for enhancing the aesthetics of engineered wood panels such as MDF and Particle Board (PB). This study analyzes the effect of conveyor speed, air pressure, and room temperature on the lamination quality of four material combinations: MDF and PB laminated with PL adhesive + PVC sheet and with woodlook adhesive + paper sheet. Using an experimental method, conveyor speed (10 and 20 m/min), air pressure (2 and 4 bar), and room temperature (25 and 30 °C) were varied, then evaluated through visual observation and bond strength testing. The optimal threshold was ≥2 kgf for PL adhesive + PVC sheet and ≥1 kgf for the thinner woodlook adhesive + paper sheet. The optimal pressure depends on the sheet type: PVC sheet is optimal at 4 bar, whereas paper sheet is optimal at 2 bar because excessive pressure causes wrinkling. The optimal conveyor speed and temperature depend on the substrate: MDF at 20 m/min and 25 °C, and PB at 10 m/min and 30 °C. The best combinations were MDF + PL + PVC sheet (20 m/min, 4 bar, 25 °C; 3.25 kgf), PB + PL + PVC sheet (10 m/min, 4 bar, 30 °C; 2.50 kgf), MDF + woodlook + paper sheet (20 m/min, 2 bar, 25 °C; 1.35 kgf), and PB + woodlook + paper sheet (10 m/min, 2 bar, 30 °C; 1.20 kgf). These findings serve as a practical reference for setting operational parameters to minimize product defects.

Design and Implementation of a Real-Time Monitoring and Early Warning System for Sulfur Dioxide (SO₂) Gas in the Tapping Operation Furnace Area of the Nickel Processing Industry

2026-09-03T15:39:51+09:00

Sulfur dioksida (SO₂) merupakan salah satu polutan udara berbahaya yang dihasilkan dari proses pembakaran bahan bakar fosil dan aktivitas peleburan logam. Paparan SO₂ secara terus-menerus dapat menimbulkan gangguan kesehatan bagi pekerja industri, sehingga diperlukan sistem monitoring yang mampu mendeteksi konsentrasi gas secara real-time sebagai bagian dari penerapan keselamatan dan kesehatan kerja (K3). Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem monitoring gas sulfur dioksida berbasis sensor MQ-136 dan mikrokontroler Arduino Uno pada area Tapping Furnace di industri pengolahan nikel. Sistem yang dikembangkan terdiri atas sensor MQ-136, Arduino Uno, LED Matrix P10 sebagai media informasi, warning light sebagai sistem peringatan dini, dan modul relay sebagai pengendali keluaran. Kalibrasi sensor dilakukan menggunakan Gas Detector DZ-10 sebagai alat referensi melalui lima kali pengujian. Hasil kalibrasi menunjukkan bahwa sensor MQ-136 memiliki tingkat kesalahan yang rendah sehingga layak digunakan untuk pemantauan konsentrasi SO₂. Pengujian lapangan dilakukan pada area Tapping Furnace 10 lantai 3 selama proses tapping berlangsung. Hasil pengujian menunjukkan bahwa konsentrasi SO₂ meningkat dari 0,8 ppm sebelum tapping menjadi 129 ppm pada menit ke-45 proses tapping. Sistem peringatan dini mulai aktif pada konsentrasi 9,2 ppm pada menit ke-10 dan terus menyala selama kondisi waspada dan bahaya. Setelah proses tapping selesai, konsentrasi SO₂ menurun secara bertahap namun masih berada pada kategori waspada hingga 15 menit setelah proses berakhir. Hasil penelitian menunjukkan bahwa sistem yang dikembangkan mampu melakukan monitoring konsentrasi SO₂ secara real-time dan memberikan peringatan dini secara efektif, sehingga berpotensi meningkatkan keselamatan kerja pada industri pengolahan nikel.