Prices In Indonesia Research Articles

Stock Price Prediction in Indonesia's Mining Sector Using a Hybrid Conv1D-LSTM Model

This study presents a novel approach to forecasting stock prices in Indonesia's mining sector by leveraging a hybrid model combining Convolutional Neural Networks (Conv1D) and Long Short-Term Memory (LSTM) networks. Given the volatile nature of stock markets and the specific characteristics of the mining industry, accurate prediction models are essential for investors and analysts. The hybrid Conv1D-LSTM model integrates the feature extraction capabilities of Conv1D with the sequence learning strengths of LSTM, providing a robust framework for time series forecasting.

Implementation of anti-dumping duties on iron and steel products: Effects on the Indonesian economy

This research aims to empirically study the impact of Indonesia's anti-dumping measures on the performance of related imported products in 2011. Using the GTAP-E model, the region is divided into 9 regions and the industrial sector is grouped into 2 industries. Empirical results indicate that the imposition of a 20% Anti-Dumping Duty (BMAD) is ineffective in restricting trade from targeted countries. The GDP of non-targeted countries increased, but international trade balances correlated negatively with each BMAD imposition. Additionally, domestic prices in Indonesia appear to be high due to the implementation of BMAD, which has resulted in increased prices of iron and steel in the domestic market.

Comparison of Fuzzy Grey Markov Model (1,1) and Fuzzy Grey Markov Model (2,1) in Forecasting Gold Prices in Indonesia

Currently, gold investment is considered promising despite the ever-changing price of gold. However, obtaining optimal profits is a challenge for investors. Therefore, a proper forecasting method is needed to forecast the gold price so investors can know the best transaction time. This study used two forecasting methods: the Fuzzy Grey Markov Model (1,1) and a new, never-before-used approach, the Fuzzy Grey Markov Model (2,1). The Fuzzy Grey Markov Model (2,1) approach is interesting because it can be considered for forecast data that shows varying increases and decreases, such as the gold price data used in this study. Both methods are combined models that utilize fuzzy logic to handle uncertainty in data; the Grey model forms a forecasting model, and the Markov chain determines the state transition probability matrix. Next, the error rates of the two methods are compared based on the Mean Absolute Percentage Error (MAPE) value to obtain the best forecasting method. As a result of this study, the Fuzzy Grey Markov Model (1,1) was chosen as the best forecasting method with a MAPE value of 0.28%.

PREDICTION OF CRUDE OIL PRICES IN INDONESIA USING FOURIER SERIES ESTIMATOR AND ARIMA METHOD

Crude oil is one of the non-renewable natural resources that is crucial for countries around the world in driving economic development. However, the availability of crude oil is decreasing over time. The high demand for crude oil results in scarcity which causes price fluctuations. Low oil prices can reduce state revenues, disrupt development programs, and even trigger budget deficits. On the other hand, an increase in crude oil prices can make a positive contribution to state revenues. Crude oil exports become more profitable, which can increase state revenue through royalties and taxes levied on the oil and gas sector. This additional revenue can be used to support infrastructure development, social programs, and investment in key sectors of the economy. High oil prices can also harm the economy. With the many impacts that can be caused by crude oil prices, the government must be able to anticipate and prepare for it. The data used in this study are data on crude oil prices in Indonesia for monthly periods from January 2018 to October 2023 sourced from the official website of the Ministry of Energy and Mineral Resources (ESDM) of the Republic of Indonesia. The researcher tried to compare two analysis methods, namely the Fourier series and the ARIMA estimator. The results of this study show that the best method in predicting crude oil prices in Indonesia is the Fourier series estimator with Cos-Sin function which produces RMSE and MAPE values of 7.93 and 8.4%. The prediction results can be used as a reference for the government to anticipate and make programs or policies that are more focused and targeted toward the impacts that can be caused by changes in crude oil prices.

Analisis Dilema Kebijakan Pemerintah dalam Menaikkan Harga Subsidi Bahan Bakar Minyak di Indonesia pada Tahun 2022

The government officially increased the price of fuel oil as a result of the increase in world oil prices and made the state budget funds swell. This research was conducted with the aim of examining various considerations made by the government when raising fuel prices in Indonesia. This research uses a literature study research method with a qualitative descriptive method. The data sources used are secondary data obtained through journal articles, books, news, and websites. The results of this study found that the government felt a dilemma so that it was forced to increase fuel prices due to the swelling of state budget funds for fuel oil consumption, but on the other hand, the impact if fuel prices increased, the prices of goods and services would increase so that inflation occurred. On the other hand, there is an alternative solution to buy oil from Russia which is below the market price, however, if that happens, it can offend western countries and hurt Indonesia's foreign policy with non-aligned movements. An alternative that the government can take is to increase fuel prices while still providing assistance to ensure that the community does not experience the impact too deeply. In addition the government invite people to switch to using electric vehicles to reduce fuel consumption and reduce the impact of carbon emissions produced, as electric vehicles are considered more economical and environmentally friendly

UNVEILING THE DYNAMICS OF DOMESTIC PRICES OF CACAO BEANS IN INDONESIA

This study is crucial for understanding the factors affecting cacao bean prices in Indonesia. Cacao is a vital commodity in the country's economy, and fluctuations in its price impact various stakeholders. By analyzing these factors, we can make informed decisions benefiting the government, industry, and cacao farmers. The purpose of this study is to analyze the domestic price of cacao beans in Indonesia. The dependent variable in this study is the domestic price of cacao in Indonesia, while the independent variables are volume of cacao bean exports, volume of cacao bean imports, global price of cacao beans, volume of domestic production of cacao beans, Rupiah to USD exchange rate, the federal reserve rate, Gross Domestic Product (GDP) annual growth rate of Indonesia, and export duties imposed on export of cacao beans. This research design utilizes time series data from 1996 to 2022 to analyze the factors influencing the domestic price of cacao beans in Indonesia. The results of the analysis show that the variables of the volume of cacao bean imports, the global price of cacao beans, Rupiah to USD exchange rate, and dummy variable for export duties imposed on export of cacao beans are significant affecting the domestic price of cacao. While volume of cacao bean exports, the federal reserve rate, volume of domestic production of cacao beans and GDP annual growth rate of Indonesia are not significant. The non-significance of volume of cacao bean exports, the federal reserve rate, volume of domestic production of cacao beans, and GDP annual growth rate could be caused by weak relationships, multicollinearity, data issues, or model specification limitations.

Comparison of Extreme Learning Machine Methods and Support Vector Regression for Predicting Bank Share Prices in Indonesia

Comparison of Extreme Learning Machine Methods and Support Vector Regression for Predicting Bank Share Prices in Indonesia

The Effort of The Government and Its Impact on Maintaining the Stability of Cooking Oil Prices

The phenomenon of oil scarcity and rising world oil prices have had an impact on the increase in cooking oil prices in Indonesia. The Indonesian government, through the Ministry of Trade, is trying to intervene in the price of cooking oil by providing oil subsidies and export bans. This article aims to describe the policy process carried out by the Indonesian government to reduce the price of cooking oil and its impact on the traditional market economy. This field research was conducted at the Srijaya Sayur Traditional Market, in Madiun City using qualitative methods. Primary data was collected using interviews with traders, sales from cooking oil distributors, and market managers. The findings of this research reveal that the price intervention policy implemented by the government was initially carried out suddenly. However, as time goes by, the Indonesian government has taken steps to improve the price of cooking oil which is well spread throughout Indonesia. This is in line with Ibn Taymiyah's thoughts on the concept of distribution justice and price policy through government intervention. The positive impact of the policy of banning petroleum exports and providing subsidies has made the price of cooking oil affordable and in line with people's purchasing power. The negative impact is that many market distortions, starting from distribution processes, hoarding and selling prices that do not comply with the policy, to shortages of goods that occur in traditional markets, especially at the beginning of the policy. In the end, this negative impact began to subside along with the abundance of oil stocks on the market which was strengthened by the government's efforts to eradicate all individuals involved in becoming mafias and breaking the law.

Price to Book Value Drives Stock Prices in Indonesia, While DER and PER Falter

This study examines the impact of the Debt to Equity Ratio (DER), Price to Book Value (PBV), and Price Earning Ratio (PER) on stock prices of food and beverage companies listed on the Indonesia Stock Exchange (IDX) from 2016 to 2018. Using secondary data from financial reports and statistical analysis via SPSS 23, the research found that DER does not significantly affect stock prices, PBV positively influences stock prices, and PER has no significant impact. These findings suggest that investors prioritize market confidence and financial prospects (as indicated by PBV) over debt levels and earnings ratios when making investment decisions in this sector. Highlights: 1. DER Impact: Debt to Equity Ratio does not affect stock prices significantly.2. PBV Significance: Price to Book Value positively influences stock prices.3. PER Irrelevance: Price Earning Ratio does not impact stock prices significantly. Keywords: Debt to Equity Ratio, Price to Book Value, Price Earning Ratio, Stock Prices, Indonesia Stock Exchange

Analysis of Fundamental Factors Affecting Islamic Bank Share Prices in Indonesia

While investing in the stock market can generate profits, it can also generate losses. Understanding the impact of certain important components on stock prices can help investors make more profitable investment decisions. The study investigated the key components that influenced the price of sharia bank Indonesian shares. Secondary data used for research. The information comes from monthly financial statements compiled from June 2018 to December 2020. The study looked at the impact of the shock and long-term response of each variable on the stock price using the Vector Error Correction Model (VECM). In the long run, PER and ROE variables have a positive effect on the stock price, but EPS has a negative effect. Unlike other variables, DER and PBV do not affect the stock price. The main factor is the EPS, which has a big and positive impact on the stock price in the short term. DER and PER have a very negative impact on the value of stocks. PBV has a negative but non-significant impact, while ROE has a positive but not significant impact. Keywords: Fundamental Factor, Stock Price, Vector Error Correction Model

The effect of the road rationing policy on housing prices: evidence from the odd-even policy in Jakarta

Purpose The purpose of this study is to examine the effects of the Odd-Even Road Rationing Policy (RRP) on housing prices in Jakarta, Indonesia. It aims to evaluate the net effect of the RRP on housing prices. Design/methodology/approach The study uses the monocentric model and employs the difference-in-differences (DD) method. Annual neighborhood-level housing price data is analyzed to assess the impact of the RRP on housing prices. Additionally, propensity score matching is used to address potential biases resulting from non-random policy assignments. Findings The results demonstrate that houses located within the RRP-restricted area experience a decrease in price that is relative to those in the control group. The findings indicate a decrease in housing prices ranging from 7.59% to 14.7% within the RRP-restricted area. This suggests that the positive impacts resulting from the RRP have not fully compensated for the restricted accessibility experienced by individuals who have limited behavioral changes. The study also confirms the significance of commuting costs in individuals' location decisions, aligning with predictions from urban economics models. Originality/value This study contributes to the literature by providing insights into the effects of a RRP on housing prices. It expands understanding beyond the immediate effects on traffic conditions and air pollution, which previous studies have primarily focused on. Furthermore, to the best of the authors’ knowledge, this research will be the first conducted to identify the impacts of RRP on housing prices in Indonesia.

PERANCANGAN POWER SUPPLY UNTUK CHARGING STATION KENDARAAN LISTRIK RODA DUA DENGAN SISTEM PLTS ON GRID

Electric vehicles use electrical energy as a substitute for fossil energy. Like gasoline vehicles that require gasoline filling facilities, electric vehicles also require electric energy charging facilities or commonly referred to as charging stations. One of the utilizations of solar power plant can be used for charging electrical energy at the charging station. In this study, a Power Supply Design was carried out for Charging Station for Two-Wheeled Electric Vehicles with Solar Power Plant System on grid in Widya Sabha Building Parking Lot, Udayana University. With the calculation of the energy needed in the Power Supply, the solar power plant design and manufacturing costs can be made. The design of this charging station can accommodate 10 electric motorbikes with solar power plant that can provide energy for 2 electric motorbikes per day for 9 hours of work alternately. By using 11.450 Wp solar panels arranged in series and 1 inverter with a capacity of 4.6 kW, this design produces 8.229 MWh per year. The total initial investment in this design based on market prices in Indonesia is IDR 99.213.000. Based on the investment feasibility, it shows that the investment in this design is feasible to implement.

The Company Share Prices in Indonesia During the Covid-19 Pandemic

The Covid-19 pandemic in 2019 to 2021 affected world economic conditions, including inflation, currency exchange rates and world gold prices. This situation changed the direction of investment from the real sector to investing in gold and stocks. This study analyzed the variables of inflation, the rupiah exchange rates, the price of gold on the share prices of PT ANTM, Tbk. The approach used causalistic quantitative by processing secondary data in the form of monthly report data that had been published on the official website. The population and sample were 36 samples of monthly reports obtained by total sampling technique. To test and analyze the hypothesis SPSS version 20 was used. The results of the study: first, inflation has a significant effect on share prices, with a significance value of 0.030.; second, the price of gold has no effect and is not significant on stock prices, with a significance value of 0.422; third, the exchange rate has no effect and is not significant on stock prices, with a significance value of 0.093; fourth, inflation, gold price and exchange rate variables simultaneously have a significant effect on share prices, with a significance value of 0.002. 0.05). Investors were interested in investing in Mining Company shares during the Covid-19 pandemic. This investment decision was regardless of Indonesia's economic situation at the time of Covid-19 which was completely uncertain, especially in investment.

ARCH/GARCH Analysis: Estimating Beef Price Volatility in Indonesia

This study analyses the volatility of beef prices in Indonesia, a strategic commodity that significantly impacts the welfare of producers and consumers. The sustained and erratic price fluctuations pose an economic risk to producers and threaten farmers' economic stability. ARCH / GARCH models were used to analyze daily beef price data from 10 July 2017 to 31 December 2023, obtained from the National Strategic Food Price Information Centre of Bank Indonesia. The GARCH (2,2) model is the most suitable for estimating the volatility of beef prices in Indonesia, with low and sustainable volatility in the long run. Factors that affect this volatility include feeder cattle and beef imports, exchange rates, livestock diseases, the COVID-19 pandemic, and government policies such as PPKM and PSBB during the new normal era. Important events such as Ramadan, Eid al-Fitr, Christmas, and New Year also influence price volatility of beef. This research aims to assist the government to design more effective market stabilization policies in the short, medium, and long term period. Keywords: beef, ARCH/GARCH, price volatility, fluctuation

PRICE FLUCTUATIONS AND VOLATILITY OF NATIONAL STRATEGIC FOOD COMMODITIES IN INDONESIA

Meeting the food needs of the Indonesian population is a top priority, and national strategic food plays a vital role in achieving this goal. However, the unstable nature of national strategic food prices can have significant implications, particularly for those with low incomes. This volatility can hinder access to healthy and nutritious food, ultimately impacting the nation's food security. In recent times, food prices have risen sharply, which is expected to have far-reaching consequences. Therefore, it is imperative to analyze the volatility of national strategic food prices to comprehend price fluctuations and patterns. This study analyzed the volatility of national strategic food prices in Indonesia from 2018 to 2022, focusing on commodities such as shallots, garlic, red chilies, cooking oil, and rice. The ARCH-GARCH method used to conduct the analysis, revealing that all five commodity prices were volatile at the national level. The red chili and shallot exhibits a distinctive pattern, characterized by an increase volatility during the second quarter of each year. This can be attributed to the rise in demand during the Ramadan. Conversely, garlic volatility was high in early 2019 and 2020, while remaining relatively stable during other periods. Cooking oil volatility remained stable until the end of 2020, but started to increase in early 2021. This closely related to cooking oil crisis that occurred in Indonesia. Lastly, rice price volatility was high in early 2018. Subsequently, exhibited relatively stable volatility until first quarter of 2022, although there were some periods where the volatility exceeded its average.

Forecasting Gold Prices in Indonesia using Support Vector Regression with the Grid Search Algorithm

Investment is an effort to increase economic growth in Indonesia. A popular investment in the community is gold investment. The value of gold investments tends to increase but is not immune from price fluctuations, therefore it is important to forecast the price of gold in Indonesia. The method that can be used to make this forecast is Support Vector Regression (SVR). SVR is a method that looks for a function that has a deviation of no more than ε to get the target value from all training data. The best SVR model with a linear kernel was obtained from a combination of parameters C=0,0625 and ε=0,001 with a RMSE value of 0,19734 and a value of 0,974112. So, the SVR method is appropriate to use for forecasting gold prices in Indonesia.

Market Intervention Policy in The Case of Rising Rice Prices in Indonesia From The Perspective of Ibn Taimiyah

Rice is an important commodity and is needed by the wider community, its existence is vital as a means to fulfil the needs of life, therefore the Indonesian government's intervention in this commodity is very high. The price of rice in Indonesia continues to rise for many factors. This research employs qualitative methods which is called library research. The result of this study is the increase in rice prices in Indonesia according to Ibn Taymiyyah is entirely caused by market forces. According to Ibn Taymiyyah what is needed therefore is market intervention, instead of price intervention. The market intervention carried out by the Indonesian government is by intensifying the social assistance program, running market operations with the SPHP program, and strengthening the stock of government rice reserves (CBP). Meanwhile, the policy of setting the price ceiling should not be carried out by the government because the market conditions related to this rice commodity run perfectly and there is no market distortion.

SHALLOTS PRICE PARADIGM IN INDONESIA AND ITS INFLUENCED FACTORS

Shallot is a horticultural commodity that, although it is minor, works as a culinary flavor enhancer in Indonesia. The fluctuations and dynamics of shallot prices contribute to the inflation rate in the Republic of Indonesia. Consequently, the government includes this commodity in the national strategic food group. This study aims to examine the factors that influence the dynamics of shallot prices in Indonesia. It analyzes the causes and provides alternative solutions to stabilize the shallot price. This research is a systematic literature review, which utilizes secondary data available on government information/data websites and several supporting articles. It used descriptive and explanatory methods to analyze the qualitative and quantitative components. The research also used the statistical regression methods, anova by Excel, and R software as differential analysis. This study shows that the most significant factors in determining shallot price are trade margin and transportation margin. Meanwhile, production factors have almost no effect regionally. The consumption factor and the length of the supply chain considerably affect certain areas. Expansion of the planting area, especially in the northern part of Indonesia, can be used as a complementary means to meet the demand for shallots on an ongoing basis. This research is a compilation of advanced analyses of reports on the performance of departments in the government of the Republic of Indonesia, taking into account and referring to the results of research by other academics.

Legal Effects of Default on Land and Building Sale and Purchase Agreement in PPJB

Along with the increase in property prices in Indonesia every year, many people choose to buy houses with installment payments. Therefore, the sale and purchase process is carried out by making an agreement, namely the Sale and Purchase Binding Agreement (PPJB) before the signing of the Sale and Purchase Deed (AJB). However, over time there is a problem where one party does not implement the contents of the agreement or is called default. This research was conducted with the aim of knowing how the legal consequences caused by defaults in land and building sale and purchase agreements and how to resolve disputes due to defaults in land sale and purchase agreements. Using normative juridical research methods, it can be concluded: 1. Legal consequences arising from default in a sale and purchase agreement, especially if one party does not implement the contents of the mutually agreed sale and purchase agreement, then the party has violated the agreement so that it is called committing a default act. 2. Settlement of disputes due to default in the sale and purchase agreement, can be done through deliberation from the parties for the settlement of the obligations of the parties in dispute to then be fulfilled / realized / paid by the parties who are considered in default. In addition, a party who feels aggrieved by the other party in the sale and purchase agreement, has the right to sue the other party who does not carry out the contents of the agreement through the intercession of a court judge or through existing legal channels.

Analyzing Twitter Users’ Sentiments on the Surge of Fuel Oil Prices in Indonesia using the K-Nearest Neighbor Algorithm

Sentiment analysis offers an effective solution for automating the classification of text data based on polarity, facilitating the assessment of public opinion. Among various social media platforms, Twitter stands out as a significant source of concise textual data reflecting users’ viewpoints on diverse topics. Notably, the recent surge in the price of fuel oil (BBM) in Indonesia has sparked considerable discussion and expression on Twitter. In this study, our objective was to perform a comprehensive sentiment analysis of Twitter users’ reactions to the rising fuel prices in Indonesia by employing the K-Nearest Neighbor (K-NN) algorithm. The research followed a structured approach encompassing data collection, text preprocessing, data labeling, feature extraction, data splitting, classification, and algorithm performance evaluation. The results revealed a dominance of negative sentiments among the 5,000 collected tweet data. The sentiments were categorized as 54.6% negative, 31.8% positive, and 13.6% neutral. This indicates a prevailing level of dissatisfaction and concern expressed by Twitter users regarding the fuel price increase. The K-NN algorithm’s classification performance was most promising when evaluated in an 80:20 data ratio experiment, yielding an accuracy rate of 65%, precision of 74%, recall of 45%, and an error rate of 35%. These findings suggest that the K-NN algorithm is valuable for effectively gauging public sentiment towards the escalating fuel prices in Indonesia. This research highlights the potential of sentiment analysis and the K-NN algorithm in assessing public reactions to significant events, providing valuable insights for policymakers and stakeholders in the energy sector.