Sevenpri Candra

KNOWLEDGE MANAGEMENT AND ENTERPRISE RESOURCE PLANNING IMPLEMENTATION: A CONCEPTUAL MODEL

The purpose of this research is examining the influence of organizational learning and knowledge management in enterprise resource planning implementation. This study is based on organizational learning, knowledge management and enterprise resource planning implementation. This research did not test all organizational factors and focus particularly on knowledge management capacity and absorptive capability. Enterprise resource planning implementation successful is a must. In today’s global and competitor in business, enterprise resource planning is becoming one of the main tools to achieve competitiveness in business. Enterprise resource planning is an infrastructure to create and maintain business to improve front-office and back-office efficiency and effectiveness. This study is significant to bring new thinking in determines the key antecedents to successful enterprise resource planning implementation based on knowledge management perspectives and it will helps to understand the key success factor in enterprise resource planning implementation.

From traditional learning into e-learning: Comparing students response to promote e-learning in college education

The purpose of this study was to measure student response by compared Management Department and Accounting Department, against a system of learning in e-learning. The samples are taken by non-probability sampling method that is purposive. Three hundred students (respondents) from these two departments of a private university are participated in this study, with a standard error of 1%. Based on a set of general questions concerning use and acceptance of e-learning the responses are categorized and evaluated. The results show good acceptance and relatively easy use of e-learning by responding students. For the idea of applying e-learning, the result of majoring in accounting (76%) said that the idea seems right e-Learning applied but for the Management students, only 32% of students who respond well.

Storyboarding for meetro: A smart navigation application system for commuter line in Jabodetabek

Transportation has been long part of people life, especially for the urban. The transportation need not only applied for the local, Jakarta as a capital city must be full of foreigner either for business purpose or others, and they are need a public transportation as well. Commuter Line Jabodetabek is the most preferable public transportation to avoid Jakartas traffic. The idea is to create a mobile application system which could easily help Commuter Line Jabodetabek user to get the information about timetable schedule, arrange the route and transit information and find how to reach the destination as well as how long to get there and how much does it cost, and visualize the route in easy-to-understand format. The application system is analyzed and designed with mobile application development approach and the application development with cloud computing provided by Application Craft, and the result of this study is prototype application design with cross-platform based.

The impact of e-Procurement practice in Indonesia government: A Preliminary Study (The case of Electronic Procurement Service at Bekasi District)

In digital economy, government of Indonesia uses the internet to deliver services and to communicate with citizens and organizations. One of applications are e-Procurement and LPSE is a unit to hold the service system of e-Procurement. Procurement of goods and services electronically in addition will increase transparency and accountability, improve market access and healthy competition, as well as improving the efficiency of the procurement process. Based on the background and specific objectives to be achieved, then the research will be viewed from e-Marketplace participation, Trust and its impact on the performance of existing procurement within the institution. Methods of data analysis used in this research is by using analysis of Structural Equation Modelling (SEM) by using the program Partial Least Square (PLS) to examine the relationship between variables. The population used in this study is an enterprise as well as other clients using the system LPSE Bekasi District. There are three part in this study population, namely the provision of a company, customer, and supplier of LPSE users amounted to 60 users. From data analysis, there are one hypothesis that rejected. The implication of this study are implementation of e-procurement and e-marketplace participation giving impact to procurement performance.

Improvement of E-learning quality by means of a recommendation system

Technology Enhanced Learning is one of the most dynamic areas of inquiry in education. One form of TELs, that is on-screen learning, has been well understood to hinder learning experience due to the reading spatial instability, difficulties in establishing mental map, and poor visual ergonomics. This work intends to study to which extend a learning a recommendation system improving on-screen learning experience. Participants were randomly divided into two groups: one group learning with the learning recommendation system and the other is without the system. Their understanding were assessed and a t-test was performed. The results indicated that the average score of learning with the recommendation system was significantly higher and the detrimental effects were mitigated.

Detecting online child grooming conversation

Massive proliferation of social media has opened possibilities for perpetrator to conduct the crime of online child grooming. Because the pervasiveness of the problem scale, it may only be tamed effectively and efficiently by using an automatic grooming conversation detection system. Previously, Pranoto, Gunawan, and Soewito [1] had developed a logistic model for the purpose and the model was able to achieve 95% detection accuracy. The current study intends to address the issue by using Support Vector Machine and fc-nearest neighbors classifiers. In addition, the study also proposes a low-computational cost classification method on the basis of the number of the existing grooming conversation characteristics. All proposed methods are evaluated using 150 conversation texts of which 105 texts are grooming and 45 texts are non-grooming. We identify that grooming conversations possess 17 features of grooming characteristics. The results suggest that the SVM and fc-NN are able to identify grooming conversations at 98.6% and 97.8% of the level of accuracy. Meanwhile, the proposed simple method has 96.8% accuracy. The empirical study also suggests that two among the seventeen characteristics are insignificant for the classification.

Relation between emotional state and speech signal

Automatic emotion recognition from human speech signal has many important practical applications. For the reason, a number of studies has been performed on the basis of English, German, Mandarin, Persian, and Danish languages. This work intends to develop automatic emotion recognition system on the basis of speech signal in Indonesia language. The study is limited to four emotional states, namely, happy, sad, angry, and fear. The speech data are collected from amateur actors and actresses, and are further quantified using Mel-Frequency Cepstral Coefficient to provide 48 emotion-related features. Finally, these features are used for emotion classification using Support Vector Machine method. The results suggest that the recognition can achieve about 86% of the level of accuracy.

Empirical relation between speech signals and heart rate

Heart disease is known to be one of the main cause of death worldwide. In the United States, the disease is the leading cause of death for people of most ethnicity. In Indonesia, the disease contributes 17% of the total mortality. It is also well-known that a regular or continuous monitoring the heart rate is important to minimize the fatality. At the current technological state, the monitoring method is expensive and often requires wearable sensor, which is inconvenient. This study intends to establish a relationship between the heart rate and speech signals empirically by using a regression and correlation analysis. The speech signals are analyzed through a frequency analysis using fast Fourier transformation. The results suggest that vowel ‘e’ speech signal has a strong correlation to the heart rate.

A study of comparison of feature extraction methods for handwriting recognition

Automatic handwriting recognition system is very important for various areas of application such as banking and logistics sectors. The performance of such system strongly depends on its feature extraction methods. So far, many extraction methods have independently been studied and proposed, and the three widely adopted methods are Geometric Moment Invariant (GMI), United Moment Invariant (UMI), and Zernike Moment Invariant (ZMI). This study is performed to understand the relative performance of the three methods. For this purpose, the methods, in conjunction with Support Vector Machine classifier with RBF, and PuK kernels, are used to recognize characters taken from Char75K dataset. In addition, the combined features of GMI-UMI, GMI-ZMI, UMI-ZMI, and GMI-UMI-ZMI are also studied. The numerical results suggest the following. Among the three extraction methods, GMI, UMI, and ZMI methods, the latter two methods tend to provide better results by about 7–8% than the GMI method. Generally, when the features are combined, the results improve rather significant, about 7–8% improvement. Only the pair of GMI and UMI combination provide small or negligible improvement. Using the RBF kernel, GMI features alone result in 63% accuracy, UMI features alone 70% accuracy, and GMI-UMI combination result in 72% accuracy. Combination of UMI-ZMI features improve the accuracy significantly than each method along. We also find that the combination of the three methods, GMI-UMI-ZMI, tend to increase the accuracy significantly. The accuracy reaches the level of 96% for the RBF kernel and 89% for the PuK kernel.

Improvement of production system efficiency and production capacity using line balancing method

This study discusses the research results conducted on an Indonesian plastic manufacturing company. The distribution of the workload in a production process needs to be calculated so that the company is able to achieve the target of production. This research was conducted to improve the efficiency of production systems and the production capacity of the company so that the company is able to meet production targets. The method used in this study is line balancing. Time study method is conducted to calculate cycle time and then forecasting method is utilized to determine production target and required cycle time. After that, 3 methods of line balancing: ranked positional weights, Moodie Young and new bidirectional is used. The result of the line balancing method shows that the best methods are Moodie Young and new bidirectional with the efficiency of 82.97%, much higher from the current state, which is only 48.89%. The number of workstation is also decreased from 9 to 7. The production also increased from 780.41 pieces per day to 1,030.07 pieces per day.