University of Bangka Belitung

Pembangunan infrastruktur oleh korporasi di wilayah desa kerap kali menimbulkan konflik antara masyarakat dan pihak perusahaan, terutama jika dilakukan tanpa persetujuan atau melanggar hak atas tanah desa. Salah satu kasus yang terjadi di sebuah desa di Kabupaten Bangka Barat menunjukkan bahwa aktivitas dugaan pembangunan oleh pihak swasta telah menimbulkan keresahan masyarakat karena dilakukan di atas lahan desa tanpa persetujuan resmi. Artikel ini bertujuan untuk mengkaji secara normatif apakah tindakan pembangunan tersebut memenuhi unsur tindak pidana sebagaimana diatur dalam Kitab Undang-Undang Hukum Pidana (KUHP) maupun peraturan perundang-undangan lain yang relevan, seperti Undang-Undang Lingkungan Hidup dan Undang-Undang Desa. Hasil kajian menunjukkan bahwa dalam kondisi tertentu, tindakan penguasaan dan/atau perusakan tanah desa oleh perusahaan dapat dikualifikasikan sebagai tindak pidana apabila memenuhi unsur melawan hukum, kesengajaan atau kelalaian, serta menimbulkan kerugian bagi masyarakat.

The capture fisheries sector is a strategic priority in Indonesia, including Jepara Regency (northern Java), where small-scale fishers rely on economically important commodities such as short mackerel (Rastrelliger spp.). Limited systematic information on seasonal dynamics is available. This study analyzed production trends, fishing effort (monthly trips), and seasonal patterns of short mackerel in Jepara waters to support sustainable fisheries logistics planning. Secondary monthly landing data from the Ujungbatu Fish Landing Site (2020–2024) were used, with effort defined as the total number of mini purse seine trips per month. Catch per unit effort (CPUE) and the fishing season index (FSI) were calculated using a simple moving average (SMA). The results showed highly fluctuating monthly production, a gradual decline in fishing effort during 2022–2024, and fluctuating CPUE (highest 238.38 kg/trip in July 2024 and lowest 7.84 kg/trip in December 2020). FSI analysis identified March to July as the productive fishing season, with a peak in July, while January to February and August to December were mostly non-seasonal. The findings indicate that CPUE dynamics are influenced not only by fish stocks but also by socioeconomic and logistical factors, including labor constraints and operational costs. Seasonal information provides a scientific basis for adjusting fishing effort and planning logistics to stabilize supply and support sustainable short mackerel fisheries in Jepara, Indonesia.

Accurate forecasting of tourism demand is crucial for regional economic planning, yet existing studies often rely on univariate time-series models or single forecasting techniques without considering spatial interdependence among regions. This study proposes a correlation-based comparative forecasting framework to evaluate the performance of ARIMA, Long Short-Term Memory (LSTM), and Prophet in predicting domestic tourist trips in Pangkal Pinang City, Indonesia. Monthly data from January 2019 to July 2025 were obtained from Statistics Indonesia, and highly correlated neighboring regions were systematically selected using a heatmap correlation analysis to enhance model input relevance. After applying Min–Max normalization and an 80:20 train–test split, all models were evaluated using Root Mean Squared Error (RMSE) under identical experimental settings. The results indicate that Prophet consistently achieves the lowest RMSE, demonstrating superior capability in capturing non-linear dynamics, seasonal variability, and abrupt structural changes in tourism demand compared to ARIMA and LSTM. These findings provide empirical evidence that decomposable time-series models with automatic trend and seasonality handling offer distinct advantages over both classical statistical and deep learning approaches in medium-term tourism forecasting. The proposed framework contributes a concise, data-efficient, and replicable methodology that supports evidence-based tourism planning and strategic decision-making.

This study aims to utilize used PET plastic waste as a basic material for 3D filaments with the addition of talc resin as a reinforcing material. Literature review shows that talc resin can increase stiffness and mechanical strength in polymer composites. The experimental process was carried out through mixing, molding, and tensile and impact tests according to ASTM standards. The test results showed that the addition of 10% talc resin provided optimal tensile strength and toughness compared to other varia tions. Thus, filaments based on used plastic and talc resin are suitable for use in environmentally friendly 3D printing applications.

The development of modern manufacturing industries demands increased process efficiency and high-precision machining quality. One of the key factors determining product quality is surface roughness, particularly in Aluminum 6061, which is widely used in the automotive and precision manufacturing industries due to its light weight, strength, and corrosion resistance. An improper combination of machining parameters can reduce surface quality and process efficiency. Therefore, this study aims to analyze the effect of cutting speed, depth of cut, and feed rate on the surface roughness of Aluminum 6061 and to determine the optimal parameter combination. The analysis was conducted using the statistical method Response Surface Methodology (RSM). The results show that all three machining parameters significantly affect surface roughness, with the optimal combination obtained at a cutting speed of 70 m/min, feed rate of 318.3 mm/min, and depth of cut of 0.7 mm, producing the lowest surface roughness value of 0.224 µm (Ra).

This study aims to analyze the effect of variations in the number and diameter of dimple holes on the stiffness of mild steel plates using the Dimple Dies Triangle Profile forming method. Plate stiffness is important for reducing vibrations, especially in vehicle components. The material used was a 0.6 mm thick galvanneal plate, with dimple diameters of 25 mm and 30 mm, and hole quantities of 16 and 20. Testing was conducted using a Vibroport 80 device to measure natural frequency as an indicator of stiffness. The experimental design employed the Taguchi method with an L4 orthogonal array to analyze the influence of each parameter. The results showed that the number of dimple holes significantly affected the plate’s natural frequency, while the dimple diameter had no significant effect. The optimal combination producing the highest stiffness was a 25 mm dimple diameter with 16 holes. ANOVA and S/N ratio analysis supported these findings, indicating that the number of holes contributed more than 90% to the variation. This research is expected to serve as a reference for developing stiffer and more vibration-resistant metal plate designs, particularly for automotive and other engineering structure applications.

This study aims to investigate the effect of sintering temperature variations on the hardness and density of brake pad composites fabricated using the powder metallurgy method. The fabrication process consisted of material preparation, powder mixing, cold compaction, and sintering with the weight fraction of matrix and filler wt.% being 40/60, 48/52, and 56/44 wt.%. Powder mixing was carried out using a horizontal ball mill with a ball-to-powder weight ratio (BPR) of 10:1, a rotational speed of 90 rpm, and a milling time of 4 hours. Cold compaction was performed uniaxially at a pressure of 5300 PSI for 10 minutes, followed by sintering at temperatures of 50°C, 60°C, and 70°C for 10 minutes. Density testing was conducted based on Archimedes’ principle in accordance with ASTM B962-17, while hardness was measured using a portable Brinell hardness tester following ASTM E110-14. The highest hardness value of 103.0 HB was obtained at 48% matrix composition with a sintering temperature of 60°C, while the highest density of 1.453 g/cm³ was achieved at 40% matrix composition with a sintering temperature of 70°C. These findings demonstrate that sintering temperature has a significant influence on the mechanical and physical properties of the brake pad composite.

ABSTRACT This paper presents a new dynamic motion control method using a fast nonsingular finite time control approach based on an adaptive disturbance observer to solve the trajectory tracking problem of nonholonomic autonomous mobile robots (AMR) with uncertain disturbances. The proposed method combines fast nonsingular terminal sliding mode control (FNTSMC) with an adaptive sliding mode observer (ASMO), referred to as FNTSMC+ASMO. The ASMO estimates disturbances in finite time, and its output is used by FNTSMC to enhance system robustness and ensure fixed‐time convergence of tracking errors under practically bounded initial conditions via Lyapunov stability theory. Additionally, an artificial potential field (APF) technique is incorporated to achieve effective obstacle avoidance, further improving its practical applicability. The validity and superiority of the proposed method are well exemplified through extensive simulations and experiments, demonstrating superior tracking accuracy and excellent disturbance rejection compared to other sliding‐mode control methods.