Karya Tbk Research Articles

Peran Negara dalam Ekspansi PT Wijaya Karya Tbk ke Afrika: Tinjauan Kapitalisme Negara

In the past few years, publicly-listed construction firm PT Wijaya Karya Tbk. (WIKA) has been actively expanding to the African market amidst the high needs of domestic infrastructure development. At the same time, studies on rising state intervention in the global economy are gaining attention from IPE scholars. Based on these factors, this paper examines the role of the government in WIKA’s expansion to Africa from the perspective of state capitalism. By examining the role of President Joko Widodo's regime through (1) centralized planning; (2) economic diplomacy; and (3) capital assistance, this paper argues that WIKA's expansion is aimed not only at generating profits, but is also influenced by political factors to meet national interests. As a state-owned enterprise (SOE), WIKA is positioned as the national champion in the infrastructure sector, which is deemed as a strategic industry for President Widodo’s regime. This paper is expected to fill the void of political economy research on the expansion of national SOEs abroad.
 
 Keywords: SOEs, state role, state capitalism, overseas expansion, WIKA.

The Comparison of ISO 14001 Implementation in Indonesia Construction Companies (Case Study: PT. Waskita Karya Tbk, PT. Wijaya Karya Tbk, PT. PP (Persero) Tbk)

Growing the economy is a concern for President Joko Widodo's (Jokowi) government, which is why attention is so important to the construction companies. Some of the largest construction firms reported major rises throughout the value of federal contracts. Attempts to improve the infrastructure services of the organization can be made through a control system of factors affecting the performance of the company which ultimately determines the business success in achieving its goals. PT. Waskita Karya Tbk and PT. Wijaya Karya Tbk implement green construction, and green building for their environmental management quality standard, meanwhile PT PP (Persero) implement 3R (Reduce, Reuse, Recycle) theory. Regarding raw materials / products which come mainly from nature. Those three businesses have received no reports over the course of the year about the environmental business. The environmental management system then proves that improve the management standard will increase productivity and decrease the risk.

To Define Window Dressing in the State Owned Enterprises and Private Companies (Case Study in Indonesia Stock Exchange LQ45)

Window dressing in capital market can be defined as the activities of company to increase the stock price. This study was conducted to observe all the activities of window dressing in some companies listed in stock market. The detection of window dressing in this study was focused based on the samples from state owned companies (Telekomunikasi Indonesia Tbk, and Adhi Karya Tbk) and private sector from Astra Agro Lestari (Agriculture Industry). GARCH model was used while window dressing was analyzed by using the method given by Owens and Wu (2011). Results indicate that the best model to explain the behavior of volatility is AR(1)-GARCH(1,1). However, window dressing for three companies mentioned was occurred in 2014-2016; 2014 and 2016, respectively. In additional to that the t-test, was found to be significant for the three companies while the short-term average was above than the long-term average of the year.

Analisis Kemampuan Rasio Likuiditas dan Profitabilitas dalam Mengukur Financial Distress

Financial distress is a condition where the results of the company's performance are unable to meet the company's obligations. The purpose of this research is to find out the effect of Liquidity and Profitability in measuring financial distress in PT .eterindo wahanatama Tbk and PT. Waskita Karya Tbk. The analysis technique used is multiple linear analysis techniques, and for hypothesis testing is a partial statistical test (t test) and simultaneous test (f test). The results of the t test show that liquidity (CR) (X1) has an effect but not significant to financial distress, Profitability (ROA) (X2) has a significant effect on financial distress. Based on the simultaneous F test means that together Liquidity (CR) and Profitability (ROA) have no significant effect on purchasing decisions (Y). Based on the test of the coefficient of determination of 0.354 it can be interpreted that the effect of Liquidity (CR) and Profitability (ROA) on purchasing decisions is equal to 28.4%. The remaining 71.6% is influenced by other factors not explained in this study.
 Keywords : Liquidity, Profitability, financial Distress.

The feed forward neural network with genetic algorithm for daily stock prediction

The power of Feed Foward Neural Network (FFNN) in conjungtion with Genetic Algorithm (GA) was applied in this research to predict daily stock price. Finance time series data has a high complexity, so that the acurate prediction is hard to be gained by standard model. Machine learning becomes the new prediction tool which is often used because of its adaptive properties. Neural Network (NN) is one of the machine learning which able to complete inference tasks such as prediction, especially in large data sets. FFNN is one of the NN models that has simple network architecture. In the standard optimization method, the initial weights is randomly selected to desire the optimum solution. But It usually raises the problem of unsteady estimation. The GA optimization method was applied in this research to overcome this lack. GA optimizes any function effectively and seeks a global optimum solution efficiently. GA implementation on the FFNN was aimed to obtain optimum weights that minimizing the error. The daily stock price prediction of PT. Adhi Karya Tbk had RMSE of training and testing data at 51.2531 and 44.8706 respectively. This result was equivalent with MAPE values at 1.5714% and 1.5501%.

PEMBENTUKAN DAN PENGUJIAN PORTFOLIO SAHAM-SAHAM OPTIMAL: PENDEKATAN SINGLE INDEX MODEL

Buying stock is one of the way investors do to obtain profit from their money. Every investor should consider two important things, return and risk. To minimize the risk, one can diversify their investment by creating optimal portfolio, which consists of different stocks with optimal return and certain degree of risk. The aim of this research was to establish and determine the optimization of optimal portfolio composed by LQ45 stocks over the period of February 2011 to January 2015. The research was trying to create optimal portfolio from thirty-eight non-financial companies stocks listed in LQ45 using single index model. From the research, the optimal portfolio is composed of TLKM (PT Telkom Indonesia Tbk), BMTR (PT Global Mediacom Tbk), JSMR (PT Jasa Marga Tbk), SSIA (PT. Surya Semesta Internusa Tbk), AKRA (PT AKR Tbk), MNCN (PT Media Nusantara Citra Tbk), WIKA (PT Wijaya Karya Tbk), ASII (PT Astra International Tbk), KLBF (PT Kalbe Farma Tbk), ASRI (PT Alam Sutera Realty Tbk), UNVR (PT Unilever Indonesia Tbk), ICBP (PT Indofood CBP Sukses Makmur Tbk), SMGR (PT Semen Indonesia Tbk), and only able to be used for six months. The optimal portfolio gives 0.242% returns for a week with 1.122 value of beta. Majority of the aggressive portfolio have higher return toward risk then portfolio moderate and conservative.

The Risk Analysis of Andalas University Hospital Construction Project

Construction project activities have various risks during their implementation. Every work item on the project has different levels of risk and can affect the project so that it will have an impact on increasing cost and time of project completion. PT. Adhi Karya Tbk is carrying out the project of Andalas University Hospital, where in its implementation there will be many possibilities of risks that will occur. Therefore, it is necessary to identify and analyze the variables of risks that may occur as well as proposing appropriate risk mitigation measures for minimize the potential risks. Risk identification and risk analysis were done using Risk Breakdown Structure (RBS) and Analytic Hierarchy Process (AHP) method respectively. Based on data compilation, variables of risk are grouped in 4 types, namely risk of engineering consist of 8 variables, risk of production consist of 5 variables, risk of construction consist of 9 variables and risk of financial consist of 2 variable, with total of risk are 24 variables. Risk analysis with AHP method is obtained 5 (five) risk priority based on the highest value on each risk type. The five priority risks were a risks of increasing of material prices (extreme), a risk of increasing of procurement costs (high), workplace accidents risk in the project area (medium), mistaken translating the DED to shop drawing (medium) and a quality of goods and services produced by vendors not meet the specifications in contract (medium). To reduce the possibility and impact the risks posed mitigation measures for the risk priority highest were proposed.

PEMBENTUKAN DAN PENGUJIAN PORTFOLIO SAHAM-SAHAM OPTIMAL: PENDEKATAN SINGLE INDEX MODEL

Buying stock is one of the way investors do to obtain profit from their money. Every investor should consider two important things, return and risk. To minimize the risk, one can diversify their investment by creating optimal portfolio, which consists of different stocks with optimal return and certain degree of risk. The aim of this research was to establish and determine the optimization of optimal portfolio composed by LQ45 stocks over the period of February 2011 to January 2015. The research was trying to create optimal portfolio from thirty-eight non-financial companies stocks listed in LQ45 using single index model. From the research, the optimal portfolio is composed of TLKM (PT Telkom Indonesia Tbk), BMTR (PT Global Mediacom Tbk), JSMR (PT Jasa Marga Tbk), SSIA (PT. Surya Semesta Internusa Tbk), AKRA (PT AKR Tbk), MNCN (PT Media Nusantara Citra Tbk), WIKA (PT Wijaya Karya Tbk), ASII (PT Astra International Tbk), KLBF (PT Kalbe Farma Tbk), ASRI (PT Alam Sutera Realty Tbk), UNVR (PT Unilever Indonesia Tbk), ICBP (PT Indofood CBP Sukses Makmur Tbk), SMGR (PT Semen Indonesia Tbk), and only able to be used for six months. The optimal portfolio gives 0.242% returns for a week with 1.122 value of beta. Majority of the aggressive portfolio have higher return toward risk then portfolio moderate and conservative.

ANALISIS KETERKAITAN PENGAKUAN PENDAPATAN DAN LABA PADA PERUSAHAAN KONSTRUKSI YANG TERDAFTAR DI BURSA EFEK INDONESIA

This study aimed to determine the effect of operating income recognition on the income statement. The data used were secondary data in form of the income statements of construction companies listed on the Indonesia Stock Exchange (IDX) from 2013 to 2016. The objects in this study were selected based on the highest profit value and were taken 3 companies as the sample. This study uses descriptive analysis as data analysis. The results showed that the three companies, namely PT Pembangunan Perumahan, PT Surya Semesta Internusa Tbk, and PT Waskita Karya Tbk, measured their income by using the percentage settlement method and each had a different level of income each year and were in accordance with the applicable accounting standars namely Standard Statement Financial Accounting (PSAK No. 34).

Accuracy Combination Test of Classical and Modern Technical Analysis: A Case Study in Stock of PT Wijaya Karya Tbk

The research aimed to measure the accuracy and combination of Classic and Modern Technical Analysis. PT Wijaya Karya Tbk (WIKA)’s stock in two periods is the sample of research. Technical analysis was used to predict stock prices by observing changes in historical share price. Practically, technical analysis is divided into Classic Technical and Modern. Research was conducted by library study and using a computer software. Microsft Excel was used for the simulation and Chart Nexus for analyzing Modern Technical Analysis. The research period started in January 1, 2013 until December 31, 2013 and January 1, 2014 until December 31, 2014. The Classic Technical Analysis used Support, Resistance, Trendline, and Flag Patern. Meanwhile for Modern Technical Analysis used Moving Average, Stochastic, Moving Average Convergence Divergence (MACD) indicator. The Classical Technical Analysis gave less result than Modern Technical Analysis. The classical give 14 investment decisions in two periods. The average return of Classical Technical is 15,50%. Meanwhile the Modern Technical Analysis gave 18 investment decisions in two periods. The average return of Modern Technical is 18,14%. Combining Classic Technical Analysis and Modern Technical Analysis gave 20 investment decisions with the average rate of return 20,41%.