Do Economic Attitudes Drive to Employee Productivity? Lesson from Indonesia

Hariyono HARIYONO 한국유통과학회 2021 The Journal of Asian Finance, Economics and Busine Vol.8 No.1

Productive human resources are important assets for companies in facing the global economic competition. The purpose of this study is to examine the effect of economic attitudes toward employees’ job satisfaction as well as understanding the impact of economic attitudes toward employee productive behavior at “Sentra Tenun Ikat” in East Java. The research method applied in this study is quantitative research with an explanatory design, which is intended to gain a better understanding of the relationship between variables. The population in this study amounted to 394 participants from SMEs and joint business groups. Meanwhile, the sample was 197 people and collected using a proportional random sampling technique. The variable measurement was carried out by a questionnaire distributed to respondents, which consisted of thirty-five closed questions. Each question item provides five alternative answers. Furthermore, it is calculated using Structural Equation Modeling (SEM) undergoing the LISREL 8.80 program. The findings indicated that there was a positive influence of economic attitudes on employees’ job satisfaction. Indeed, the positive value coefficient indicates that there is an effect that is directly proportional to economic attitudes toward employees’ productive behavior through employee performance satisfaction, namely, the better the economic attitude taken, the higher the productive behavior of employees.

Human Detection from Mobile Omnidirectional Camera Using Ego-Motion Compensated

Hariyono, J.,Hoang, V.-D.,Jo, K.-H. SPRINGER-VERLAG 2014 Lecture Notes in Computer Science Vol.8397 No.-

Motion Segmentation Using Optical Flow for Pedestrian Detection from Moving Vehicle

Hariyono, J.,Hoang, V.-D.,Jo, K.-H. SPRINGER-VERLAG 2014 Lecture Notes in Computer Science Vol.8733 No.-

Moving Object Localization Using Optical Flow for Pedestrian Detection from a Moving Vehicle

Hariyono, Joko,Hoang, Van-Dung,Jo, Kang-Hyun Hindawi Publishing Corporation 2014 The Scientific World Journal Vol.2014 No.-

<P>This paper presents a pedestrian detection method from a moving vehicle using optical flows and histogram of oriented gradients (HOG). A moving object is extracted from the relative motion by segmenting the region representing the same optical flows after compensating the egomotion of the camera. To obtain the optical flow, two consecutive images are divided into grid cells 14 × 14 pixels; then each cell is tracked in the current frame to find corresponding cell in the next frame. Using at least three corresponding cells, affine transformation is performed according to each corresponding cell in the consecutive images, so that conformed optical flows are extracted. The regions of moving object are detected as transformed objects, which are different from the previously registered background. Morphological process is applied to get the candidate human regions. In order to recognize the object, the HOG features are extracted on the candidate region and classified using linear support vector machine (SVM). The HOG feature vectors are used as input of linear SVM to classify the given input into pedestrian/nonpedestrian. The proposed method was tested in a moving vehicle and also confirmed through experiments using pedestrian dataset. It shows a significant improvement compared with original HOG using ETHZ pedestrian dataset.</P>

Detection of pedestrian crossing road: A study on pedestrian pose recognition

Hariyono, Joko,Jo, Kang-Hyun Elsevier BV 2017 Neurocomputing Vol. No.

<P><B>Abstract</B></P> <P>Detection of pedestrian crossing road is the objective of this work. The model incorporates the pedestrian pose recognition and lateral speed, motion direction and spatial layout of the environment. Pedestrian poses are recognized according to the spatial body language ratio. The center of mass of the body relative to its width and height is used to define the pedestrian pose. Motion trajectory is obtained by using point tracking on the centroid of detected human region, and then estimated velocity is determined. Spatial layout is determined by the distance of the pedestrian to the road lane boundary. These models will be then hierarchically separated according to their action (walking, starting, bending and stopping). In order to classify the pedestrian crossing road, a walking human model is proposed. A walking human is defined by ratio of the centroid location from the ground plane divided by the height of bounding box that should satisfy a constraint. The proposed algorithms are evaluated using publicly available datasets and our pedestrian walking dataset. The performance result shows that the correct pedestrian crossing road classification is 98.10%.</P>

A study on catalytic and non‑catalytic sites of H5N1 and H1N1 neuraminidase as the target for chalcone inhibitors

Hariyono Pandu,Kotta Jasvidianto Chriza,Adhipandito Christophorus Fideluno,Aprilianto Eko,Candaya Evan Julian,Wahab Habibah A.,Hariono Maywan 한국응용생명화학회 2021 Applied Biological Chemistry (Appl Biol Chem) Vol.64 No.5

The H1N1 pandemic in 2009 and the H5N1 outbreak in 2005 have shocked the world as millions of people were infected and hundreds of thousands died due to the infections by the influenza virus. Oseltamivir, the most common drug to block the viral life cycle by inhibiting neuraminidase (NA) enzyme, has been less effective in some resistant cases due to the virus mutation. Presently, the binding of 10 chalcone derivatives towards H5N1 and H1N1 NAs in the non-catalytic and catalytic sites was studied using molecular docking. The in silico study was also conducted for its drug-like likeness such as Lipinski Rule, mutagenicity, toxicity and pharmacokinetic profiles. The result demonstrates that two chalcones (1c and 2b) have the potential for future NA inhibitor development. Compound 1c inhibits H5N1 NA and H1N1 NA with IC50 of 27.63 μM and 28.11 μM, respectively, whereas compound 2b inhibits NAs with IC50 of 87.54 μM and 73.17 μM for H5N1 and H1N1, respectively. The in silico drug-like likeness prediction reveals that 1c is 62% better than 2b (58%) in meeting the criteria. The results suggested that 1c and 2b have potencies to be developed as non-competitive inhibitors of neuraminidase for the future development of anti-influenza drugs.

Association of selected gene polymorphisms with thermotolerance traits in cattle - A review

Hariyono, Dwi Nur Happy,Prihandini, Peni Wahyu Asian Australasian Association of Animal Productio 2022 Animal Bioscience Vol.35 No.11

Thermal stress due to extreme changes in the thermal environment is a critical issue in cattle production. Many previous findings have shown a decrease in feed intake, milk yield, growth rate, and reproductive efficiency of cattle when subjected to thermal stress. Therefore, selecting thermo-tolerant animals is the primary goal of the efficiency of breeding programs to reduce those adverse impacts. The recent advances in molecular genetics have provided significant breeding advantages that allow the identification of molecular markers in both beef and dairy cattle breeding, including marker-assisted selection (MAS) as a tool in selecting superior thermo-tolerant animals. Single-nucleotide polymorphisms (SNPs), which can be detected by DNA sequencing, are desirable DNA markers for MAS due to their abundance in the genome's coding and non-coding regions. Many SNPs in some genes (e.g., HSP70, HSP90, HSF1, EIF2AK4, HSBP1, HSPB8, HSPB7, MYO1A, and ATP1A1) in various breeds of cattle have been analyzed to play key roles in many cellular activities during thermal stress and protecting cells against stress, making them potential candidate genes for molecular markers of thermotolerance. This review highlights the associations of SNPs within these genes with thermotolerance traits (e.g., blood biochemistry and physiological responses) and suggests their potential use as MAS in thermotolerant cattle breeding.

Ego-Motion Compensated for Moving Object Detection in a Mobile Robot

Hariyono, J.,Kurnianggoro, L.,Wahyono,Hernandez, D.C.,Jo, K.-H. SPRINGER-VERLAG 2014 ICHIT 2012 Vol.8482 No.-

Modification of Cutoff Values for HE4, CA125, the Risk of Malignancy Index, and the Risk of Malignancy Algorithm for Ovarian Cancer Detection in Jakarta, Indonesia

Winarto, Hariyono,Laihad, Bismarck Joel,Nuranna, Laila Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.5

Background: CA125 and HE4 are used in calculating Risk of Malignancy Algorithm (ROMA); and Risk of Malignancy Index (RMI). However, studies showed that normal levels of CA125, and HE4 differ among ethnicities such as between Asians and Caucasians, thus affecting the accuracy of the RMI score and ROMA in predicting ovarian malignancy. This study aimed to determine whether new or modified cutoff values for Ca125, HE4, the RMI score, and ROMA resulted in a better prediction of malignancy compared with the previous or standard ones. Materials and Methods: Serum level of CA125 and HE4 from 128 patients with diagnosis of ovarian tumor that had been collected before surgery at Cipto Mangunkusumo General Hospital (CMH) in Jakarta from November 2010 until May 2011 were reviewed and analysed. The standard cutoff values of these biomarkers, RMI, and ROMA were modified by using logistic regression model. The modified cutoff values were compared to the standard cutoff values in terms of sensitivity, specificity, and accuracy. Results: The modified cutoff value of CA125, HE4, RMI score and ROMA were 165.2 U/mL, 103.4 pM, 368.7, 28/54. The sensitivity and specificity of the modified cutoff values CA125, HE 4, RMI score and ROMA in differentiating benign from malignant and borderline were 67% and 75,4%; 73.1% and 85.2%; 73.1% and 80.3%; and 77.6% and 86.9%. While the sensitivity and specificity of the standard cutoff value of CA125; HE4; RMI score; and ROMA were 91% and 24.6%; 83.6% and 65%; 80.6% and 65.6%; and 91.0% and 42.6%. The accuracy of modified cutoff values compared with standard cutoff values were: 71.2% vs 59.3%, 78.9% vs 75% vs, 76.5% vs 73.4%, and 82% vs 67.9%. Conclusions: The new or modified cutoff values of Ca125, HE4, RMI score and ROMA resulted in higher accuracy compared to the previous or standard ones, at the cost of reduced sensitivity.

Location Classification of Detected Pedestrian

Joko Hariyono,Van-Dung Hoang,Kang-Hyun Jo 제어로봇시스템학회 2014 제어로봇시스템학회 국제학술대회 논문집 Vol.2014 No.10

This paper proposes a method to detect pedestrians from a single camera mounted on the vehicle then classify the location of the pedestrian to give information for the driver assistance system. The system consists of three stages. First, moving objects are detected using optical flows method. A moving object is extracted from the relative motion by segmenting the region representing the same optical flows after compensating the ego-motion of the camera. The regions of moving object are detected as transformed objects which are different from the previously registered background. Second, histogram of oriented gradients (HOG) features descriptor and linear support vector machine (SVM) are used to recognize the pedestrian from detected moving objects. Third, a heuristic method according to the image formation in advance from its geometrical coordinates is proposed. It is used for classify the location of the detected pedestrian using the region properties of the image. The image is classified into two regions, the road region in front of vehicle and the pedestrian movement region. The proposed method is evaluated using sequential images in outdoor environment, and the performance results shown the best pedestrian detection rate is 99.3% at 0.09 false positive rate. The location classification evaluation shown correct detection rate is 92.40%.