Center for Scientific Publication
Not a member yet
4029 research outputs found
Sort by
Comprehensive Study on Cr(VI) Adsorption and Regeneration Behavior of Alkali-Treated Wood Charcoal: Isotherms and Kinetics Models
Full text linkThe present study considers the adsorption and regeneration behavior of alkali-treated wood charcoal (WC-NaOH and WC-KOH) for Cr(VI) removal. Adsorption isotherms (Langmuir, Freundlich, Temkin, and Dubinin-Raduskevich) and kinetics (Pseudo-first-order and Pseudo-second-orderare being investigated utilizing a non-linear method that provides precise parameter prediction and mechanism elucidation. The outcomes suggested that both WC-NaOH and WC-KOH exhibit good Cr(VI) removal efficiency, with the Langmuir model best explaining the adsorption phase, indicating single-layer adsorption. The kinetic study revealed that the Pseudo-second-order model aligns remarkably well with the data, thereby affirming that chemical adsorption is the predominant mechanism in consideration. A comparative analysis revealed that WC-KOH exhibits a higher amount of adsorption than WC-NaOH, attributable to its enhanced larger surface area as well as micro-porous structure.. Regeneration studies showed the possibility of reuse of both adsorbents. It shows the efficiency of alkali-treated wood charcoal for Cr(VI) decontamination and the advantages of non-linear modeling in adsorption experiment
Intelligent Fault Prediction in Diesel Engines: A Comparative Study of SVM and BPNN for Condition-Based Maintenance
No full textThis study discusses the application of Support Vector Machine (SVM) and Backpropagation Neural Network (BPNN) in predicting diesel engine health based on operational data that has been relabeled using K-Means Clustering. Two types of SVM kernels were tested, namely Radial Basis Function (RBF) and Sigmoid, with various parameter combinations. The results indicate that SVM with a Sigmoid kernel achieved an accuracy of 94.06% but was less sensitive in detecting unhealthy engine conditions. In comparison, the BPNN method with a three-hidden-layer configuration (1-2-1 neurons) and the tansig activation function demonstrated superior performance, achieving an accuracy of 97.13%, MSE of 0.03, recall of 94%, precision of 100%, and an F1-score of 97%. These results confirm that BPNN outperforms SVM in capturing complex data patterns and is more accurate in detecting unhealthy engine conditions. Furthermore, dataset relabeling significantly improved prediction accuracy from 72.3% to 97.13%, emphasizing the importance of data balance in modeling. Overall, this study demonstrates that BPNN with an optimal configuration is more effective in predicting diesel engine health than SVM, making it a more reliable approach for engine condition monitoring.Keywords: Diesel Engine; Machine Health Prediction; Support Vector Machine; Backpropagation Neural Network; Condition-Based Maintenance; Artificial Intelligenc
Predicting Failure using Machine Learning and Statistical Based Method: a Production Machine Case Study
Full text linkThis research investigates the applicability of failure detection models based on machine learning and statistical approaches to reduce unplanned downtime in a food production company. Sensor data is utilized to for identifying early failure symptoms. To capture temporal and sequential dependencies in time-series data, we employ one of potential network based method so called the Long Short Term Memory (LSTM) Autoencoder. Furthermore, we contrast the performance of the result with the traditional statistical method, the multivariate Exponentially Weighted Moving Average (EWMA). While both models successfully detected all failures, LSTM-AE demonstrated superior performance by reducing false alarms and providing true alarms with a longer time-to-failure. The findings highlight the potential of leveraging limited data for failure prediction, demonstrating the effectiveness of both models in detecting anomalies while emphasizing their role in enhancing productivity through early failure detection
INTEGRATION OF GENDER EQUALITY AND SOCIAL INCLUSION (GESI) IN PARTICIPATORY PLANNING OF INFORMAL SETTLEMENTS: CASE STUDY OF TAMMUA URBAN VILLAGE, MAKASSAR
Full text linkRT 002 RW 004, Tammua Urban Village in Makassar City is an informal settlement with the highest level of vulnerability, characterized by high population density, irregular building structures, limited access to clean water, sanitation, and open spaces, as well as overlapping land uses among residential, industrial, and transportation areas. This study evaluates the integration of Gender Equality and Social Inclusion (GESI) principles in the participatory planning of informal settlements through a review of the Tammua Community Settlement Environmental Planning (RPLP) document. Spatial analysis was used to identify correlations between housing density, building feasibility, and access to basic infrastructure with the distribution of vulnerable groups through a GESI lens. Results indicate that the RPLP has attempted to thematically mainstream GESI using the Analysis, Participation, Control, and Benefit (APKM) framework. Thematic maps reveal spatial correlations between housing density, building feasibility, and infrastructure access with the distribution of vulnerable groups. However, participation of vulnerable communities remains limited; housing density reaches 711.11 units/ha, 82 households lack access to clean water, and drainage infrastructure is damaged over 7,359 meters. Due to inadequate sanitation, most residents still rely on dug wells for bathing, washing, and defecation. The study concludes that the integration of GESI in participatory planning in Tammua needs improvement, particularly in substantially involving vulnerable groups, creating adaptive spatial designs, and equitably distributing infrastructure to realize adequate, resilient, and equitable urban housing conditions
IMPACT OF HOLTEKAMP BRIDGE CONSTRUCTION ON DISASTER MITIGATION IN JAYAPURA’S COASTAL ZONE, PAPUA
Full text linkCoastal areas are increasingly under pressure from various activities and natural phenomena. The construction of the Holtekamp Bridge in Jayapura has made Holtekamp Beach increasingly attractive as a trade and service area. However, these activities also increase the risk of disasters and affect the community's preparedness to deal with disasters. This article is the result of a descriptive qualitative study showing that the construction of the bridge has influenced the level of disaster mitigation both structural and non-structural at Holtekamp Beach. The novelty of this research article is to explore disaster mitigation in a coastal area in which settlement and business areas grow simultaneously. However, the existing mitigation measures are still uneven between the coastal area and the commercial area at Holtekamp Beach. Therefore, Holtekamp Beach needs to enhance disaster mitigation measures that are responsive to the area as a commercial and service hub due to reducing the risk of disasters that may occur in the future
Budget Tracking Anggaran Percepatan Penurunan Stunting: Analisis Multisektoral di Kabupaten Tuban
Full text linkStunting remains an alarming problem in Indonesia, with profound implications for human capital development and long-term economic productivity. Despite the national government’s commitment, including Presidential Regulation No. 72/2021, inefficiencies in local budget execution continue to challenge targeted outcomes. This study aimed to track stunting-related budgets in Tuban Regency between 2021 and 2022, with a focus on allocation trends, sectoral involvement, and realization performance across specific and sensitive interventions. Budget allocations for stunting reduction increased sharply from IDR 17.5 billion in 2021 to IDR 51.1 billion in 2022 (a 192% increase), with participating government offices expanding from 4 to 9. The Health Department remained the lead implementer, implementing IDR 17.6 billion in 2022, or 34.5% of the total stunting-related budget with community nutrition services absorbed most of the budget. Meanwhile, the public works spent IDR 10.6 billion for rural water infrastructure, reinforcing the importance of WASH in sensitive interventions. The education sector experienced a threefold increase, yet its share remained under 0.5% of the total. While the environmental sector emphasized infrastructure-based waste management. These findings highlight fiscal expansion yet persistent implementation gaps. It is essential to strengthen budget tagging, intersectoral collaboration, and evidence-based planning to optimize the impact of increased investments in stunting reductio
Seismic Hazard Identification On North Banda Arc Region Using Gutenberg-Richter Law
Full text linkNorth Banda Arc region has high risk of significant earthquake due its complex tectonic configuration. in order to assess seismic hazard potential on north Banda Arc region, Gutenberg-Richter (G-R) Law is applied using Earthquake catalogue from 1970 to 2023. The results are G-R parameters including Mc, a, and b, where the the spatial parameters (a and b values) and temporal parameter (b-value) are applied to investigate the seismic hazard in the north Banda Arc Region. The spatial results show that two regions with high risk to release stress in strong earthquake are on eastern Seram Island and between eastern Buru and western Seram Island including its smaller island nearby. On the other side, temporal earthquake shows decreasing b-value indicates increasing effective stress that could lead to strong earthquake
Load Variation Analysis Of Generator On Lembar-Padang Bai Ro-Ro Ships For Safety Maritime
Full text linkA generator is vital for ship operations, serving as a source of electrical power generation on board. The electrical system changing loads every second. Even with these changes, the power demand stays steady and must be supplied correctly. Voltage stability shows how well the system can keep the voltage steady during normal operation or after something goes wrong. Things like added loads or changes in the system setup can also affect this stability. The method used in this research is circuit modeling that conducted using the Electrical Transient Analysis Program (ETAP) software to collect data. This modeling is essential for designing a system that can be effectively simulated. The result is the voltage and frequency stability values while the air compressor motor operates at 4.5kW showed no significant voltage changes. In contrast, when the electric bow thruster motor, operating at 335kW, runs, the voltage dropped to 85% within 6.5 seconds. During a short circuit at the 15th second compartment bus, the engine room bus experiences a voltage dropped of 77%, while the hull compartment bus dropped by 45%. This showed that the system is unsafe for the equipment, as the as a voltage
Penerapan Multi Boezem Dalam Upaya Pengendalian Banjir di Kawasan Industri JIIPE Kabupaten Gresik
Full text linkAlih fungsi lahan pada kawasan industri JIIPE seluas 1607 Ha menyebabkan meningkatnya koefisien limpasan dan debit banjir. Untuk itu, diperlukan infrastruktur pengendalian banjir yaitu dengan membangun boezem pada zona 1, zona 2, dan zona 3. Perhitungan debit banjir sungai digunakan HSS Nakayasu (Q25). Untuk debit banjir kawasan menggunakan metode Rasional (Q25). Dalam merencanakan dimensi serta pola operasi boezem didasarkan pada volume inflow, ketersediaan lahan, muka air Sungai Mireng dan Teluk Lamong. Hasil analisis didapatkan volume tampungan zona 1 sebesar 120.229,96 m3, zona 2 sebesar 606.145,29 m3, dan zona 3 sebesar 314.613,06 m3. Kapasitas pompa zona 1 3m3/detik, zona 2 10 m3/detik, dan zona 3 5 m3/detik
Comparison of Polylactic Acid Polycondensation Using LASC Fe(DS)3 Catalyst and FeCl3 Metal Catalyst
Full text linkPolylactic acid (PLA), also known as lactic acid, has become a promising candidate as a renewable resource for plastic production. The use of PLA as a plastic material can significantly reduce the problems caused by waste. In the production of Polylactic acid (PLA), there are byproducts such as water, while metal Lewis such as Fe (III) used in PLA production can rapidly decompose and be deactivated by water. This research aims to synthesize a water-resistant Lewis catalyst by Fe (III) Lewis metals with a surfactant called Sodium dodecyl sulfate (SDS), which will bond together to form Fe (III) dodecyl sulfate [Fe(DS)3]. This catalyst will then be compared to FeCl3 metal catalysts in terms of performance in PLA synthesize using the polycondensation method. The water-resistant Lewis catalyst is characterized using Fourier Transform Infrared (FTIR), X-Ray Diffraction (XRD), and Thermogravimetric Analysis (TGA). As for the PLA synthesized with Fe(DS)3 and FeCl3 catalysts under the same operating conditions, it is analyzed using viscometry to determine its molecular weight, Fourier Transform Infrared (FTIR), and X-Ray Diffraction (XRD). The results of the analysis of the LASC catalyst include: 1) FTIR spectra of Fe(DS)3 and SDS show similarity in stretching and bending vibration bands. 2) Crystallinity indices of 36.81% and 15.82% are obtained for SDS and Fe(DS)3, respectively. Results of the PLA analysis include: 1) The optimum temperature is 180 ℃, as it leads to an increase in molecular weight, while at 200 ℃, degradation occurs, resulting in a decrease in molecular weight. 2). FTIR result shows that lactic acid polymerization was achieved. 3) XRD analysis shows gentle diffraction from 10° to 26° which similar with literature. 4) The yields of PLA molecules synthesized by Fe(DS)3 gain with higher molecular weight compared to FeCl3 catalyst