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Forecasting Futures Gold Prices Using Pulse Function Intervention Analysis Approach
Full text linkGold is a precious metal that plays an important role in global trade and is often use as a financial standard in various countries. In 2024, gold prices surged sharply due to global macroeconomic factors, such as economic uncertainty, positioning gold as a safe haven for investors. Accurate predictions of future gold prices are crucial for helping investors make informed decisions and adapt to market changes. In line with Sustainable Development Goal (SDG) 8 on Decent Work and Economic Growth, this study uses the pulse function intervention analysis approach to predict gold prices by identifying patterns of changes in the pre-intervention and post-intervention periods. This study aims to make a significant contribution to the use of comprehensive and relevant predictive tools by considering the effects of interventions, supporting investor decision-making, and contributing to economic growth. The best model was obtained at ARIMA (0,2,1) with intervention parameters b=0, r=2, and s=0. The prediction results show a close alignment with actual data, yielding a MAPE value of 1.289%. Additionally, this model produces the smallest AIC value of 1125.1, an SBC value of 1135.86, and an MSE value of 1403.11, demonstrating excellent predictive capability
Implementing Markov Switching Regression Using Best Subset Approach For BSI Stock Price Prediction Analysis
Full text linkStocks are evidence of ownership of the capital or funds of a company or institution and are represented by a document that includes the par value, the company name, and the rights and obligations described for each owner. Since so many factors affect the rise and fall of stock prices, investors should pay attention to the factors that influence the rise and fall of stock prices to avoid incurring losses or profits when buying and selling stocks. The rise and fall of stock prices can be analyzed with Markov switching regression by trying all possible placements of factors to get the best subset. Public holdings will continue to increase due to nation-building and Sharia Bank Indonesia (BRIS) stock price appreciation. This study aims to determine the impact of increases and decreases in the closing price of BSI stock. The modeling used in this study is Markov switching regression using the best subset approach. The data used in this study are secondary in the form of daily data for the closing price of Bank Syariah Indonesia shares, Inflation, BI Rate, Selling Exchange Rate, Money Supply, and Gross Domestic Product (GDP). Data are obtained from the official BPS website. The results of this study show that Markov switching regression modeling can identify the feasibility of regimes as "bull" and "bear" periods. State 2 indicates an uptrend or "bullish," and state 1 indicates a downtrend or "bearish." The best subset approach obtains the best model with the lowest SSE value. The study concluded that the statistical modeling results of BSI stock's closing prices during "bull" and "bear" periods provide significant predictors: BI Rate, Selling Exchange Rate, and Money Supply
A comparative study of pi and eems on emu for hybrid fuelcell power systems
Full text linkThis study investigates the Energy Management Unit (EMU) for a hybrid power system integrating PEMFC, batteries, supercapacitors, and Photovoltaic (PV) as renewable energy sources. The EMU is designed to support power supply, reduce the load on the PEMFC, and enhance operational efficiency and reliability. It intelligently manages power distribution by adjusting the use of energy sources based on system conditions, such as battery state of charge (SOC), load changes, or PV energy availability. Two types of management algorithms used in the EMU were tested: Proportional Integral (PI) and External Energy Management Strategy (EEMS). The comparison results show that EEMS outperforms PI in terms of stability and efficiency, with an average efficiency of 88.85% for EEMS compared to 88.77% for PI. Furthermore, the EEMS method demonstrates superior performance by maintaining minimal fluctuations ranging from 0.02 to 0.03, even under dynamic load conditions, while the PI method shows greater fluctuations, varying between 0.05 and 0.08
Design and performance testing of a safety instrumented system for water level control simulator using plc with cause-effect matrix implementation
Full text linkSafety Instrumented Systems (SIS) are widely employed in industrial settings to ensure operational safety and prevent system failures that could pose risks to the environment, personnel, and assets. This research presents the design of an SIS for a water level control system, utilizing Programmable Logic Control (PLC) to enhance safety and mitigate the risk of leakage or flooding. The SIS design is developed based on the Layers of Protection Analysis (LOPA) methodology, incorporating multiple protective layers, including water level measurement instruments, controllers, and final control elements to manage risk effectively. Following the LOPA-based design process, system testing was conducted using a cause-and-effect matrix to evaluate performance under various operational scenarios. The findings indicate that implementing SIS in water level control systems significantly enhances operational safety. In simulated test conditions, the SIS effectively detected potentially hazardous situations, such as excessive water levels that could lead to overflow or dangerously low levels that might disrupt process continuity. The system then executed appropriate mitigation measures, such as alerting operators or automatically shutting off water flow, to prevent accidents and equipment damage. The results demonstrate that integrating an SIS into water level control systems provides substantial benefits in managing operational risk, ensuring system reliability, and safeguarding industrial processes
Analysis of PVD Installation Methods Due to Limited Vertical Clearance in the Lamongan North Ring Road Construction Project Section 1 STA 0+400 to STA 0+426
Full text linkThe construction of the Lamongan North Ring Road is planned to be built on soft soil. Based on the results of the soil investigation, it is known that the subgrade condition is classified as soft to very soft soil with a depth of 18 meters. One of the problems of this very soft soil is the settlement. Therefore, the National Road Implementation Agency of East Java - Bali Region conducted subgrade improvement using preloading combined with Prefabricated Vertical Drain (PVD). The configuration of the PVD installation is 18 meters deep with a triangular pattern and the distance between PVDs is 1 meter. To stake the PVDs 18 meters deep, a piling rig with a minimum height of 24 meters is required. In the STA 0+400 to STA 0+426 section there is a 150 kV Lamongan - Paciran High Voltage Air Line (SUTT) cable crossing the road with a conductor to platform distance of 18 meters. The existence of this cable is a challenge in the PVD driving as deep as 18 meters. Therefore, this journal will analyze the PVD piling implementation method that can be carried out in this segment. The method carried out in this study is to start with the collection of secondary data such as shop drawings as a reference for the implementation of work in accordance with the planned design. Based on the design plan, an implementation method that can be applied to limited vertical clearance conditions is obtained. Based on the results of the research, an 18-meter deep PVD installation method was obtained that can be applied to limited vertical clearance conditions in the Lamongan North Ring Road construction project Section 1 STA 0+400 to STA 0+426. In addition, it was also found that the time required was 34.75 minutes to stake 1 PVD point using the pulled hole PVD method
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No full textAnalysis of Temporary Preloading for Bridge Approach Embankment to Eliminate Secondary CompressionCase Study: Probolinggo – Banyuwangi Toll Road Construction Project Section 3 STA 40+550 Muhammad Rizal Permadi, Indrasurya B. Mochtar, Noor Endah Mochtar & Reza KazhimiThe Effect of Prefabricated Vertical Drain Length on Soft Soil Settlement (Case Study: The North Ring Road of Lamongan STA. 3+200)Henniko Okadha, Herman Wahyudi, Yudhi Lastiasih & Sifa' UdukhaAnalysis of Excavated Soil Utilization as Embankment Material and Foundation Layer on Singaraja – Mengwitani Road Section (BALI) Dinul Hadi, Ria Asih Aryani Soemitro, Trihanyndio Rendy Satrya & Noor FachrieAnalysis of PVD Installation Methods Due to Limited Vertical Clearance in the Lamongan North Ring Road Construction Project Section 1 STA 0+400 to STA 0+426 Fanny Rumintha Br Barimbing, Yudhi Lastiasih, Herman Wahyudi & Sifa` UdukhaDetermination of Building Assets and Equipment Requirements Based on Sustainable Warehouse Cencepts for PT Kansai Prakarsa Coatings Putri Dewi Purnama & Halla Nur Aziza
Optimization of Bioethanol Production From Chlorella Vulgaris With Ca2+,Mg2+, and Zn2+ Ion Suplements Through Separated Hydrolysis and Fermentation Using Respon Surface Methodology
Full text linkIndonesia, with its wealth of natural resources, has the potential to develop bioethanol as an alternative to diminishing fossil energy sources. Third-generation bioethanol is a form of renewable energy and an environmentally friendly fuel derived from non-conventional biomass resources, particularly from microorganisms such as algae and cyanobacteria. This study focuses on optimizing the bioethanol production process from the microalga Chlorella vulgaris using the Separated Hydrolysis and Fermentation (SHF) method, with the addition of Ca2+, Mg2+, and Zn2+ ions to enhance bioethanol yield and concentration. The research procedure includes raw material pretreatment, acid hydrolysis, liquefaction, saccharification, fermentation, and distillation. The distillate samples are analyzed for bioethanol concentration using a refractometer and bioethanol density with a pycnometer. The effect of added medium components on the fermentation process is statistically analyzed using Analysis of Variance (ANOVA) in MINITAB Statistical Software and Response Surface Methodology (RSM) in DESIGN EXPERT 13. Statistical optimization of the fermentation process is performed using Central Composite Design (CCD). ANOVA analysis reveals significance with a P-Value <0.0001 for bioethanol yield and concentration. Optimization results indicate an optimal yield of 17.087% with a concentration of 165.592 g/L, achieved with the addition of Ca2+ at 164.755 ppm, Mg2+ at 146.279 ppm, and Zn2+ at 38.516 ppm
FROM CULTURE TO VIRALITY: THE SOCIAL MEDIA EFFECT ON TOURIST DESTINATION IN GREATER JAKARTA AREA
Full text linkSocial media platforms such as Instagram or TikTok have shifted how tourists perceive architectural designs of both local and international destinations. The clickbait-driven content and algorithms used within these platforms expose users to see similar things repeatedly, which subconsciously change people’s preferences. Builders used this opportunity to recreate “viral” places to repeat the glory of its predecessor. This research investigates how this phenomenon has shifted architectural typology, particularly within Greater Jakarta. Through a mixed method approach that blends architectural theory content analysis from social media posts, surveys, and statistical data, this study aims to investigate the rising trend of “copycat” design to attract a larger audience. Findings reveal a significant correlation between viral destinations and architectural development in greater Jakarta. While this trend potentially promotes tourism and potentially economic growth, it also sparks debate around the erosion of cultural identity and authenticity. This paper demonstrates that while the so-called “form follows Instagram” approach might work on a superficial level, it fails to embrace the deeper beauty and locality of architectural design. Furthermore, this paper aims to open a dialogue on the future of architectural expression in a media-saturated society, where likes and shares shape the built environment, where copying and pasting are seen as a mere habit
ANALISIS PENGARUH KONFLIK KERJA, TINGKAT KEPERCAYAAN, DAN KINERJA TIM TERHADAP KEBERHASILAN PELAKSANAAN PROYEK KONSTRUKSI DI PROVINSI JAWA TIMUR
Full text linkDalam proses pelaksanaan proyek konstruksi di Provinsi Jawa Timur, berpotensi terjadi permasalahan yang dapat menyebabkan konflik kerja, kemudian berdampak terhadap tingkat kepercayaan dan kinerja tim, sehingga dapat mempengaruhi keberhasilan proyek. Tujuan dari penelitian ini adalah untuk menyelidiki hubungan dan dampak dari setiap variabel terhadap keberhasilan proyek. Langkah awal dari penelitian ini yaitu dengan kajian literatur terhadap penelitian sebelumnya untuk mendapatkan variabel dan indikatornya. Kemudian menyusun kuesioner sebagai alat untuk pengumpulan data primer. Penelitian ini menggunakan metode SEM-PLS. Hasil penelitian menunjukkan bahwa variabel konflik kerja berdampak negatif dan signifikan secara langsung terhadap variabel tingkat kepercayaan, kemudian variabel tingkat kepercayaan berdampak positif dan signifikan secara langsung terhadap varibel kinerja tim, sedangkan variabel kinerja tim berdampak positif dan signifikan secara langsung terhadap variabel keberhasilan proyek
Small Area Estimation of Child Poverty on Java Island In 2021 (Comparison of EBLUP and Hierarchical Bayes)
Full text linkInformation about child poverty is very important to ensure that children get their rights. Indonesia's decentralized system requires child poverty data in each district/city. Data provision at this level is constrained by a non-specific sample design used for certain age groups, so the sample age group for children is not always sufficient for each district/city. Therefore, direct estimation produces a high relative standard error (RSE), so it requires small area estimation (SAE). SAE that is often used is EBLUP, which assumes that the variable of interest is normally distributed. Child poverty data does not meet the normality assumption, so SAE with Hierarchical Bayes with Beta distribution (HB Beta) is proposed in this study. The result is direct estimation, EBLUP, and HB Beta produce relatively similar estimated values, but HB Beta has the lowest RSE