This research aims to analyze the influence of machiavellianism, competency and motivation toward audit quality. This study uses a quantitative approach by using questionnaires that was distributed to 50 respondents to gather primary data. Respondents for this research are auditors at Badan Pengawasan Keuangan dan Pembangunan (BPKP) – Central Java Chapter. Research data was analyzed by using multiple linear regression analysis. The results show that (1) machiavellianism has negative effect on audit quality, (2) competence has positive effect on audit quality and (3) motivation has no effect on audit quality.

Penelitian ini bertujuan untuk membuktikan bahwa terdapat pengaruh dari koneksi politik terhadap manajemen laba riil (real earnings management). Beberapa penelitian sebelumnya menemukan bahwa koneksi politik dianggap dapat memberikan pengaruh positif terhadap tingkat manajemen laba, namun beberapa penelitian lain menyatakan hal yang sebaliknya. Koneksi politik pada penelitian ini diukur menggunakan jumlah dewan direksi dan dewan komisaris terkoneksi politik untuk menunjukkan tinggi atau rendahnya pengaruh. Penelitian ini dilakukan di Indonesia dengan menggunakan sampel perusahaan manufatktur yang terdaftar di BEI. Sampel penelitian ini berjumlah 297 firm years. Hasil penelitian ini menunjukkan bahwa tidak mendukung hipotesis yang telah dikembangkan. Penelitian kali ini menunjukkan hasil bahwa penerapan dewan direksi terkoneksi politik dan dewan komisaris terkoneksi politik tidak berpengaruh terhadap praktik manajemen laba riil. Hal ini bisa dikarenakan jumlah dari dewan direksi dan dewan komisaris yang belum signifikan dalam sampel sehingga belum dapat menjadi prediktor dari praktik manajemen laba.

This study aims to examine accountability, transparency, and community participation in village financial management. The reason for choosing this research topic is because the results of this study are expected to provide benefits for village financial managers, village management, and village communities in increasing accountability, especially in accountability for design, preparation, implementation and accountability reports. This research was conducted in villages in North Bengkulu Regency using a sampling technique, namely purposive sampling in which the sample was adjusted to certain criteria. In this study using a quantitative approach. The data collection method in this study used primary data obtained from the results of distributing questionnaires to the head of finance, head of government, BPD, Kadun 1 and Kadun 2 in villages in North Bengkulu Regency with a sample of 45 respondents. Hypothesis testing using multiple regression analysis. The results of this study indicate that accountability has a positive effect on village financial management, transparency has a positive effect on village financial management, participation has a positive effect on village financial management.

This research was conducted on the grounds that group B students at Bakti Mulia Kindergarten Tlepokkulon had low cognitive abilities. The purpose of this study was to describe the effect of using number card media in improving students' cognitive abilities. This research uses classroom action research which is carried out in three cycles and each cycle through planning, implementing actions, observing, and reflecting. The subjects of this study were group B students of Bakti Mulia Kindergarten, Tlepokkulon Village, Grabag District, Purworejo Regency, which collected 15 children. The object of the research is to increase children's cognitive abilities in understanding the concept of numbers with number symbols using number cards as media. The results showed an increase in children's cognitive abilities through the connection of a collection of objects 1-10 with number cards through the demonstration method, namely students who developed according to expectations which previously reached 2 children (13%), in the cycle to 4 children (27%), cycle 2 became 7 children (46%) and cycle 3 became 13 children (86%).

Intrusion Detection Systems (IDS) are an efficient defense against network attacks as well as host attacks as they allow network/host administrators to detect any policy violations. However, traditional IDS are vulnerable and unreliable for new malicious and genuine attacks. In other case, it is also inefficient to analyze large amount of data such as possibility logs. Furthermore, for typical OS, there are a lot of false positives and false negatives. There are some techniques to increase the quality and result of IDS where data mining is one of technique that is important to mining the information that useful from a large amount of data which noisy and random. The purpose of this study is to combine three technique of data mining to reduce overhead and to improve efficiency in intrusion detection system (IDS). The combination of clustering (Hierarchical) and two categories (C5, CHAID) is proposed in this study. The designed IDS is evaluated against the KDD'99 standard Data set (Knowledge Discovery and Data Mining), which is used to evaluate the efficacy of intrusion detection systems. The suggested system can detect intrusions and categorize them into four categories: probe, DoS, U2R (User to Root), and R2L (Remote to Local). The good performance of IDS in case of accuracy and efficiency was the result of this study.

In conducting research, using descriptive methods, where the sources and types of data used are quantitative data and qualitative data. The research design used by the author is a primary data research design and a secondary data research design. The data collection technique used is a field research technique which includes interviews and observations, while a library research technique includes data collection techniques by studying, reviewing and understanding existing data sources. in several books related to the research.
In the presentation of the raw material inventory report still using manual recording using inventory cards and Microsoft Office Excel 2003 software, then the new information system will be used to create a system that includes making DFD, ERD, Normalization, context diagrams and physical design, namely output design and databases.
From the results of the study, it can be concluded that the existing system in CV. Adi Sejahtera Bandung there are several weaknesses, the system for recording transactions in and out of raw materials that is run manually is still not efficient, the occurrence of errors and the slow sales process is due to the slowness in receiving information on goods at this company. The author suggests using a computerized raw material inventory information system to help management control inventory transactions by improving the information structure in reports and making standardized reports to make work efficient and effective.

Human Computer Interaction (HCI), a growing research field in science and engineering, aims to provide a natural way for humans to use computers as tools. Humans prefer to interact with each other mainly through speech, but also through facial expressions and gestures, for certain parts of the speech and displays of emotions. The identity, age, gender, and emotional state of a person can be obtained from his face. The impression we receive from the expression reflected on the face affects our interpretation of the spoken word and even our attitude towards the speaker himself. Although emotion recognition is an easy task for humans, it still proves to be a difficult task for computers to recognize user`s emotional state. Advances in this area promise to arm our technological environment by means for more effective interactions with humans, and hopefully the impact of facial expressions on cognition will increase rapidly in the future. Will do. In recent years, the adoption of digital has increased rapidly, and the quality has improved significantly. Digital printing has resulted in fast delivery and needs-based costs. This article describes a sophisticated combination classifier approach, an empirical study of ensembles, stacking, and voting. These three approaches were tested on Nave Bayes (NB), Kernel Naive Bayes (kNB), Neural Network (NN), Auto MultiLayer Perceptron (Auto MLP), and Decision Tree (DT), respectively. The main contribution of this paper is the improvement of the classification accuracy of facial expression recognition tasks. In both persondependent and nonpersondependent experiments we showed that using a combination of these classifier combinations gave significantly better results than using individual classifiers. It has been observed from experiments that the overall voting technique by voting achieves the best classification accuracy.

Using different programming languages when software advancement is a familiar method in current software advancement. Nevertheless, using various languages that can hinder developer capacity is not widely known. This research simulated an unplanned controlled study examining the adoption of various languages in the situation of a directory programming task. Participants in this study were given programming tasks written in Java and one of three SQL-like embedded languages.  Simple “SQL” over authority, “Java” program only, and a more Java-like hybrid embedded language. Furthermore, to transcribe the responses to the online quest and the participators' “task” solutions, the participators' eye movements were also recorded with an eye tracker.
 “Eye Tracker” or in this study call as “Eye-Trc” is the methodology of the study of software development that has developed nowadays and grants more in-depth info about how developers accomplish programming tasks. This Eye-Trc method is used as a data collection method in this study. Eye-Trc data was get by thirty-one participators (university background and Industrial Background) for different programming tasks. To analyze the impact of inter-group inconstant and professional experience and in-group “task” variables on the dependent variable Time in completion, this study used a mixed model ANOVA. The outcome of this study indicates that an important impact on productivity was not found, this is different from the initial research because of the language used.
However, the same effect was found from the participators' expertise in programming activity indicating that more competent programmers were easy to full fill “polyglot programming tasks” more efficiently. In addition, it was raised that participators viewed the specimen code with the same proportion (time) for bringing “task” reckless of skills or language alternative provided. dominant-stage exploration management also remains mostly consistent over the experiences or language alternatives. Overall, it can be concluded that the programming stage of the linguist doesn’t have an important impact. The top-stage strategies that participators used came to be identical reckless of the language alternative presented to them. As a suggestion for future research, the impact of various characteristics of polyglot programming languages should be studied in depth for the conclusions reached to remain correct across various polyglot programming contexts.

This study is intended to assess the behavior of the variables of motivation, discipline, and leadership on the performance of ASN at the Wonogiri regional Secretariat through organizational culture or without organizational culture.From 140 ASN, be used 114 respondents as sample with Slovin formula were taken with a simple random sampling. The data was then analyzed using a path analysis system and equipped with statistical tests. Field findings show that: 1) Motivation has a significant influence on organizational culture in Wonogiri regional Secretariat; 2) Discipline has a significant influence on the culture of the organization in the Wonogiri regional Secretariat; 3) Leadership has an influence but not significant on the organizational culture in the Wonogiri regional Secretariat; 4) Motivation has a significant effect on the performance of ASN in the Wonogiri regional Secretariat; 5) Discipline has no significant effect on the performance of ASN in the Wonogiri regional Secretariat; 6) Leadership has an influence, although not insignificant, on the performance of ASN in the Wonogiri regional Secretariat; and 7) Organizational culture has a significant influence on the performance of ASN in the Wonogiri regional Secretariat

Credit Card (CC) scam In financial markets is a growing nuisance. CC scams increasing rapidly and causing large amounts of financial losses for organizations, governments, and public institutions, especially now that all payment methods for e-commerce shopping can be done much more easily through digital payment methods. For this reason, the purpose of this study is to detect scam CC transactions from a given dataset by performing a predictive investigation on the CC transaction dataset using machine learning techniques. The method used is a predictive model approach, namely logistic regression models (LR-M), random forests (RF), and XGBoost combined along particular resampling techniques that have been practiced to anticipate scams and the authenticity of CC transactions. Model performance was calculated grounded Re-call Curve (RC), precision, f1-score, PR, and ROC.
The experimental results show that the random forest in combination with the hybrid resampling approach of SMOTE and removal of Tomek Links works better than other models. The random forest model and XGBoost accomplished are preferred over the LR-M as long as their global  f1 score is without re-sampling. This demonstrates the strength of one technique that can provide greater achievement alike in the existence of class inequality dilemmas. Each approach, at the same time when used with Ran-Under, will give a great memory score but fails cursedly in the language of accuracy. Compared to the coordinate model sine re-sampling, the accuracy and RS are not repaired in cases where Tomek linker displacement was used. RF and xgboost perform quite well in terms of f1-S when Ran-Over is used. SMOTE increases the random forest draw score and xgboost but the precision score (PS) decreases slightly.
Completely, during a hybrid solution of Tomek delinker and SMOTE was practiced with random forest, it gave equitable attention and RS in the PR-AUC. XGboost failed to increase the PS even though the same re-sampling technique was used. For future research, a fee-delicate study method can be applied as long as fee misclassifications. So for future research, it is very necessary to consider this behavior change and it is also very important to develop predictive models. In addition to this, much larger data is needed so that detailed studies on handling non-stationary properties in CC scam detection can be carried out better.