APLIKASI K-MEANS DAN FUZY CLUSTERING DALAM PENGELOMPOKAN KECAMATAN DI KABUPATEN BANYUMAS

Clustering N objects into c clusters can be used to get information about data observation. Among the clustering methods are K-Means (KMC) and Fuzzy C-means (FCM) methods. In the K-means method, objects are members or not members of the cluster, while in the FCM method, objects are included in the cluster based on the degree of membership. This study discusses the implementation of KMC and FCM in the custering of sub-districts in Banyumas Regency based on total of population, the number of health workers and the number of health facilities and infrastructure. The results showed that the KMC and FCM methods produced the same cluster membership. Furthermore, the analysis of clustering based on the number of population, the number of health workers and the number of health facilities and infrastructure (scenario 1) and based on the number of health workers and the number of health facilities and infrastructure which have been corrected by population (scenario 2). The percentage of the variance ratio between clusters to the total variance in scenario 1 is 69% while in scenario 2 it is 85%. Clustering based on scenario 2 is better than scenario 1.

Adaptive market hypothesis: An empirical analysis of the Wine Market

We test the nature of weak form informational efficiency present in the wine market using daily return of LIV-EX 50 index from 1/1/2010 to 12/6/2020. First, we employ a number of statistical tests including variance ratio tests, tests for linear and non-linear dependence and Hurst coefficient. The tests are applied on the full dataset and on four non overlapping sub-samples of equal length. The variance ratio tests provide a mixed regarding informational efficiency. Evidence of non-linear dependence in the return series was found. The Hurst coefficient values confirm the presence of long run persistence in the wine market. Based on the mixed evidence, we test the possibility of adaptive nature of the wine market. We employ the newly proposed Adaptive Index (AI) to quantify the degree of information inefficiency in the wine market at any instance. Our results confirm that wine market is adaptive and periodically shifts between states of efficiency and inefficiency. The wine market is found to be relatively free from the Covid-19 induced shock and the safe haven property of wine is thus confirmed. Finally, impact of various macroeconomic and financial events on wine market efficiency is identified by using AI.

Study of Some Hydraulic Parameters of A solar-Powered Drip Irrigation System

An experiment was carried out in Al-Rifai District - Dhi Qar Governorate, to study the effect of the distance between drippers and their discharge on friction losses, coefficient of variation, and emission consistency of the drip irrigation system. Spiral drippers with a design discharge of 4 and 8 L.hr"1. While the emitters were installed at distances of 20, 40, 60 (cm). The actual discharge of the droplets was measured and the friction losses, emission consistency coefficient, and discharge variance ratio were calculated. The results showed that the distance between the emitters 60 cm gave the lowest percentage of friction losses, which amounted to 0.165, 0.204 (m) for drippers with design drainage of 4, 8 L.hr-1. The best values of the emission consistency coefficient and the variance ratio in the emitters discharge were 95.44 and 28.41% when using the 8L.hr-1 and the distance between the emitters is 60 cm, respectively.

Market Behavior in the Face of Political Violence: Evidence from Tsarist Russia

Even efficient financial markets may break down under periods of prolonged stress, especially when the ramification of an event is unclear. Political violence is such an event, sending immediate signals about possible impact on firm valuations but unclear information about the future viability of existing institutions. This paper examines the effect of political violence in 19th century Russia on its stock market; using a battery of unit root and variance ratio tests, the evidence is that Russian financial markets were mostly efficient in processing short-term information from political violence. However, when violence was at its peak between the assassination of the Tsar in 1881 and the 1905 revolution, large deviations from efficiency can be detected, as markets were unsure about the viability of the existing rules of the game.

An Empirical Investigation of the Random Walk Hypothesis in the Nigerian Stock Market

The Random Walk Hypothesis (RWH) states that stock prices move randomly in the stock market without following any regular or particular pattern and as such historical information contained in the past prices of stocks cannot be used to predict current or future stock prices. Hence, stock prices are unpredictable and that investors cannot usurp any available information in the market to manipulate the market and make abnormal profits. This study empirically examines the random walk hypothesis in the Nigerian stock market using the daily quotations of the Nigerian stock exchange from 2nd January, 1998 to 31st December, 2019. The study employs Augmented Dickey-Fuller unit root test, the random walk model, Ljung-Box Q-statistic test for serial dependence, runs test of randomness, and the robust variance ratio test as methods of analyses. The result of the study rejected the null hypotheses of a unit root and random walk in the stock returns. The null hypothesis of no serial correlation in the residuals of stock returns was also rejected indicating the presence of serial correlation/autocorrelation in the residual series. The result of the runs test rejected the null hypothesis of randomness in the Nigerian stock returns. The results of the variance ratio test under homoskedasticity and heteroskedasticity assumptions both strongly rejected the null hypothesis of a random walk for both joint tests and test of individual periods. Based on the results of the four tests applied in this study, it is concluded that the Nigerian daily stock returns under the period of investigation do not follow a random walk and hence the null hypothesis of a random walk is rejected. The results of the study further revealed that the Nigerian stock market is weak-form inefficient indicating that prices in the Nigerian stock market are predictable, dependable, consistently mispriced, inflated, liable to arbitraging and left unprotected to speculations and market manipulations. The study provided some policy recommendations

Testing the Efficiency of Globally Listed Private Equity Markets

This study is the first to investigate the efficient market hypothesis in its weak form and the random walk behaviour of globally listed private equity (LPE) markets represented by nine global, regional, and style indices based on weekly data covering the period from January 2004 to December 2020. Autocorrelation tests, variance ratio tests, and a non-parametric runs test are employed. The results of the autocorrelation tests and the variance ratio tests tend to correspond for all indices, and they reject the random walk hypothesis for the returns of all LPE indices under investigation. In contrast, the runs test for direct weak-form market efficiency cannot reject the null hypothesis of a random walk process for almost all LPE indices under investigation. Furthermore, there is no evidence that the market efficiency of globally listed private equity markets has improved after the global financial crisis. Due to the fact that the rapidly growing asset class of LPE as a form of private equity is still relatively unknown, the implications of the results of our paper are relevant for investors, policy makers, and academics alike. In addition, the results provide valuable insights to better understand the emerging asset class of LPE.

APAKAH SAHAM FARMASI DI BURSA EFEK INDONESIA MENGIKUTI HIPOTESIS RANDOM WALK SAAT PANDEMI COVID-19?

<p><em><span lang="EN-US">Berbeda dengan saham lain yang turun cukup tajam saat dimulainya pandemi Covid-19, pergerakan harga saham farmasi justru mengalami peningkatan. Kenaikan harga saham farmasi sejalan dengan ekspektasi investor terhadap peningkatan permintaan obat dan suplemen kesehatan yang berdampak pada kenaikan harga saham di pasar. Penelitian ini secara empiris bertujuan untuk menguji perilaku rantai jual beli di Bursa Efek Indonesia (BEI) yaitu PT Indo Farma Tbk (INAF), PT Kimia Farma Tbk (KAEF), PT Kalbe Farma Tbk (KLBF), PT Phapros Tbk (PEHA), PT Pyridam Farma Tbk (PYFA), dan PT Tempo Scan Pacific Tbk (TSPC). Secara khusus, penelitian ini menyelidiki apakah akan melaporkan apakah saham farmasi selama Pandemi Covid-19 mengikuti Random Walk Hypothesis (RWH) atau sebaliknya apakah pergerakan harga dapat diprediksi. Data yang digunakan dalam penelitian ini adalah harga penutupan saham harian dari tanggal 2 Januari 2020 sampai dengan 2 Februari 2021. Data dianalisis menggunakan uji Augmented Dickey-Fuller untuk adanya Uji Unit Root, uji Variance Ratio, dan Autoregressive Moving Average. (ARMA). Hasilnya, berdasarkan Uji Akar Unit, semua data stasioner di tingkat. Pengujian lebih lanjut menggunakan Variance Ratio, baik secara stand alone intersep maupun trend dan antar semua data juga tidak bergerak secara acak dan tidak mengikuti Hipotesis Random Walk. Terakhir, dengan menggunakan model ARMA, pergerakan log return saham farmasi di BEI dapat diprediksi.</span></em></p><p><em><span lang="EN-US"><em><span>In contrast to other stocks that fell quite sharply at the start of the Covid-19 pandemic, pharmaceutical stock price movements have increased. The increase in the price of pharmaceutical stocks is in line with investors' expectations of an increase in demand for medicines and health supplements, which will have an impact on the increase in stock prices in the market. This study empirically aims to examine the behavior of the chain buying and selling on the Indonesia Stock Exchange (IDX), namely PT Indo Farma Tbk (INAF), PT Kimia Farma Tbk (KAEF), PT Kalbe Farma Tbk (KLBF), PT Phapros Tbk (PEHA), PT Pyridam Farma Tbk (PYFA), and PT Tempo Scan Pacific Tbk (TSPC). Specifically, this study investigates whether to report whether pharmaceutical stocks during the Covid-19 Pandemic followed the Random Walk Hypothesis (RWH) or vice versa whether the price movements were predictable. The data used in this study are daily stock closing prices from January 2, 2020, to February 2, 2021. The data were analyzed using the Augmented Dickey-Fuller test for the existence of the Unit Root Test, Variance Ratio test, and Autoregressive Moving Average (ARMA). The result, based on the Unit Root Test, all data is stationary at the level. Further testing using the Variance Ratio, both by stand-alone intercept and trend and between all data also does not move randomly and does not follow the Random Walk Hypothesis. Finally, using the ARMA model, the log return movement of pharmaceutical stocks in IDX can be predicted.</span></em></span></em></p>

EFFICIENCY BASED ON MARKER ASSISTED SELECTION FOR F2 POPULATION WITH ONE LOCUS MODEL: A SIMULATION STUDY

Simulation study was done to evaluate QTL mapping and selection efficiency of molecular markers utilisation in the F2 population. The simulation study started with formulating genetic configuration which consists of chromosome maps and genetic models. Genetic model for diploid individuals is a model which consists two alleles for each locus. Genetic model that used is a mathematical model consists additive, dominance, and interactions with different effects at each locus, with maximum interaction occurs between two loci (digenic). QTL mapping was constructed by using single locus model, two loci model and multiple loci model. the effect of sample size, heritability, and marker density was observed. Three model was used to analyse QTL position, i.e. marker regression, interval mapping (IM) and composite interval mapping (CIM). Several parameters were specified in this study: genetic variability coefficient (GVC=15%), population mean (μ=10), epistasis and genetic variance ratio (f=0.1), dominance and additive variance ratio (r=0.25), the ratio of AA:AD:DD is 3:2:1 with additive and dominance gene action, and its interaction. The first and last marker were located at each edge of 150 cM chromosome for each chromosome. The interval distance between markers were equal. Haldane’s map function was used in this simulation. The simulation was performed by using the QTL Package on “R” software. With a heritability 0.2, the required sample size to indicate the interval markers associated with QTL were 50 for single locus model. The level of selection efficiency using molecular markers was higher than the phenotypic screening on. Efficiency level of selection based on molecular markers (Em) is a function of the distance between the markers to QTL (d) which follows “reciprocal quadratic” function. Efficiency level of selection based on phenotype (Ef) is a function of heritability favourable traits which follows “reciprocal quadratic” function.Keywords: efficiency, markers, QTL, simulation