cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Widhi Ariyo Bimo
Contact Email
moneter@uika-bogor.ac.id
Phone
+6288212632557
Journal Mail Official
moneter@uika-bogor.ac.id
Editorial Address
Jl. K.H. Sholeh Iskandar km 2 Bogor 16162 Jawa Barat, Indonesia Telp/Fax: 0251-8335335
Location
Kota bogor,
Jawa barat
INDONESIA
Moneter : Jurnal Keuangan dan Perbankan
Published by Universitas Ibn Khaldun Bogor
ISSN : 23022213     EISSN : 26155141     DOI : 10.32832/moneter
Core Subject : Economy, Science,
Computer Science & IT Economics, Econometrics & Finance
Moneter: Jurnal Keuangan dan Perbankan mempunyai fokus dalam kajian keuangan dan perbankan , dengan scope sebagai berikut: Dasar-dasar keuangan dan perbankan syariah dan konvensional Bisnis Teknologi Informasi
Arjuna Subject : Bisnis, Menejemen, dan Akutansi (semua kategori) - Bisnis, Menejemen, dan Akutansi (Lain-Lain)
Articles 151 Documents
 1   2   3   4   5 
The Influence Of Motivation And Work Environment On The Performance Of Outsourching Employees Annisa, Hanna; Tukirin, Tukirin
Moneter: Jurnal Keuangan dan Perbankan Vol. 11 No. 1 (2023): APRIL
Publisher : Universitas Ibn Khladun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (330.376 KB) | DOI: 10.32832/moneter.v11i1.53

Abstract

The purpose of this study was to determine the effect of motivation and work environment on outsourced employee performance. This study uses a survey method. The research variables are motivation and work environment as independent variables, and employee performance as the dependent variable. The research population is outsourced employees, the number of samples is determined by the Slovin formula. The sample selection was carried out by incidental samples. Data collection techniques with questionnaires, and measurement with a Likert scale. Processing techniques and data analysis include descriptive statistical analysis, and multiple linear regression analysis, determining the multiple linear regression model. Based on the results of descriptive statistical analysis, it can be interpreted that motivation (X1), work environment (X2), and employee performance variables (Y) are classified as good. Based on the results of multiple linear regression analysis, a multiple linear regression equation is obtained Ŷ= -0.016 +0.470 X1 + 0.341 X2. From the classical assumption test, the regression shows that the regression model is the Best Linear Unbiased Estimator (BLUE). The adjusted R-square value is 0.759, meaning that the ability to explain the independent variables, namely motivation and work environment on the employee performance variable (Y) is 75.9%, and the remaining 24.1% is explained by other variables not examined. Partially test the hypothesis that the motivational variable (XI) has a significance value of t = 0.000 <0.05, partially having a significant effect on employee performance (Y). Variable X2 has a significance value of t = 0.001 <0.05, which partially has a significant effect on employee performance (Y). Simultaneous hypothesis test results (F test), obtained a significance value of F of 0.000 <0.05, then the motivation variable (XI), work environment (X2) simultaneously has a significant effect on employee performance (Y).
DESIGN OF IOT AND ONION AGRICULTURE DATABASE USING BPR LIFE CYCLE Thifaal, Nisrina Salwa; Alzami, Farrikh; Steven, Alvin; Yusianto, Rindra; Saputra, Filmada Ocky; Sartika, Mila; Andono, Pulung Nurtantio; Wahyudi, Firman
Moneter: Jurnal Keuangan dan Perbankan Vol. 11 No. 1 (2023): APRIL
Publisher : Universitas Ibn Khladun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (632.824 KB) | DOI: 10.32832/moneter.v11i1.54

Abstract

One of the food commodities produced by the agricultural sector with high economic value is red onion. As the population of Indonesia increases, the need for red oniom has also increased. The level of red onion production from year to year is also increasing. Especially the central Java area as the largest red onion producing center in 2021. Therefore, the amount of red onion production needs to be maintained and increased by monitoring overall land conditions. Such as weather conditions, air, temperature, and humidity. A sensor to detect these factors is already available but there is no database to accommodate the data from the sensor. The purpose of this research is to produce a Business Process Model and Notation (BPMN) of red onion surveillance system on Internet of Things (IoT) based farmland. The stages carried out are by collecting data related to the research and analyzing business processes using the Business Process Reengineering Life Cycle (BPR) method. This method improves business processes to become more efficient and renewable. This research produces a database design to accommodate incoming data from Internet of Things sensors. Things (IoT) on red onion farming.
Implementation Of Extreme Gradient Boosting Algorithm For Predicting The Red Onion Prices Saputri, Pungky Nabella; Alzami, Farrikh; Saputra, Filmada Ocky; Andono, Pulung Nurtantio; Megantara, Rama Aria; Handoko, L Budi; Umam, Chaerul; Wahyudi, Firman
Moneter: Jurnal Keuangan dan Perbankan Vol. 11 No. 1 (2023): APRIL
Publisher : Universitas Ibn Khladun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (656.456 KB) | DOI: 10.32832/moneter.v11i1.55

Abstract

Red Onion or the Latin name Allium Cepa is included in the group of vegetable plants that are needed by the public for food needs. Red Onions are one of the seasonal crops so their availability can change in the market which causes price instability due to a lack of supply of production by several factors: 1) not yet it's harvest time, 2) crop attacked disease pests and fungi, and 3) weather factor. Therefore, a study is needed to predict red onion prices, so that it can be used as information for the government to stabilize red onion prices. The method used in this study is CRISP-DM and the Extreme Gradient Boosting algorithm to predict the price of red onions by taking data samples from Tegal and Pati Cities. The results of this study are that the Extreme Gradient Boosting algorithm is able to produce Tegal District Root Mean Square Error (RMSE) values of 5107.97% and Mean Absolute Percentage Error (MAPE) values of 0.17%. For prediction results with Pati Regency data samples, it produces a Root Mean Square Error (RMSE) value of 6049.74% and a Mean Absolute Percentage Error (MAPE) of 0.17%.
Comparison Of Arrival Classification Of Outpatient Patients Based On Appointment Using Adaboost And Random Undersampling Methods Widodo; Soeleman, Arief; Alzami, Farrikh; Muslich, Muslich; Krisnawati, Dyah Ika
Moneter: Jurnal Keuangan dan Perbankan Vol. 11 No. 1 (2023): APRIL
Publisher : Universitas Ibn Khladun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (866.876 KB) | DOI: 10.32832/moneter.v11i1.56

Abstract

Patients who choose to carry out examinations and treatment with an outpatient model without staying at hospitals and health service clinics are increasing for various reasons and the busyness of the patient in question. Clinics and hospitals are still able to survive and operate because they are still needed by patients who require both outpatient and inpatient services. Many clinics and hospitals in various countries still have not implemented an outpatient queue data processing system with an adequate system so there are many patients who have registered to be examined but do not come for various reasons which is a loss for the nurses and doctors on duty at the hospital. that day. This incident is certainly detrimental to clinics and hospitals because data processing is still manual, so it is impossible to predict how many patients will visit the clinic for check-ups. One solution that is still wide open for managing visiting patient data both for outpatient and inpatient treatment is to use big data. The method to be used in data mining is a Decision Tree classification with Adaboost and Random Undersampling. With the Decision Tree classification with Adaboost and Random Undersampling, good predictions will be produced so that they can help in making a decision.
VGG16 Deep Learning Architecture Using Imbalance Data Methods For The Detection Of Apple Leaf Diseases Sulistyowati, Tinuk; PURWANTO, Purwanto; Alzami, Farrikh; Pramunendar, Ricardus Anggi
Moneter: Jurnal Keuangan dan Perbankan Vol. 11 No. 1 (2023): APRIL
Publisher : Universitas Ibn Khladun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (692.215 KB) | DOI: 10.32832/moneter.v11i1.57

Abstract

Data in the real world, there are many conditions (situations) where the number of instances in one class is much less than the number of instances in other classes. This situation is a problem in unbalanced datasets (imbalance class). As a result, performance in classification will decrease in some data systems. In this study, it was identified that the apple leaf disease performance dataset used had a large enough data imbalance problem where the comparison between instances was 1:5, so an oversampling method was needed to solve the data imbalance problem. Methods that can be used include the Synthetic Minority Over Sampling Technique (SMOTE). In order to validate the effectiveness of the proposed model, two experimental scenarios were carried out: first, the VGG16 algorithm was directly applied to modeling without considering class imbalance by reducing the number of layers and kernels in each layer to achieve optimal results, second, over-sampling SMOTE to increase the number of balanced datasets. The results showed that using the confusion matrix the accuracy results for each method were obtained where VGG 16 scored 85.16%, VGG 16 with SMOTE scored 92.94%. The conclusion of this study is that SMOTE helps improve the accuracy of leaf disease detection in apples.
The Influence of Bank Soundness Level Indicators and Branch Office on Bank Deposit Growth ika, Ika Wulandari
Moneter: Jurnal Keuangan dan Perbankan Vol. 11 No. 1 (2023): APRIL
Publisher : Universitas Ibn Khladun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (394.835 KB) | DOI: 10.32832/moneter.v11i1.59

Abstract

This study aims to determine the effect of bank soundness rating indicator and branch offices on deposit growth. Assessment of bank health is proxied by using the ratio of NPL, LDR, IRR, GCG rating, ROA, NIM and CAR. Meanwhile, branch offices were obtained from the branch offices number of bank samples studied. Growth in deposits is proxied by changing on deposits in the year studied with the previous year. This type of research is quantitative research. The research population is banking companies listed on the Indonesia Stock Exchange with the sample of 33 companies in the 2018-2020 period. The sample companies were taken by purposive sampling method. Testing was carried out with multiple linear regression. Hypothesis testing was carried out using the t test. The results showed that NPL, IRR, GCG ratings, ROA, NIM, CAR and branch offices had no effect on deposit growth. Meanwhile, LDR had a negative effect on deposit growth.
The Function of National Culture in Moderating Digital Marketing's Influence on Consumer Purchase Interest (Case Study on Tokopedia Users in Denpasar City) rettobjaan, vitalia fina carla; Bagus Aristayudha, A.A. Ngurah
Moneter: Jurnal Keuangan dan Perbankan Vol. 11 No. 1 (2023): APRIL
Publisher : Universitas Ibn Khladun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32832/moneter.v11i1.139

Abstract

The purpose of this study is to ascertain how national culture influences the influence of digital marketing on customer purchasing interest. (Case Study of Tokopedia Users in Denpasar City). There are many elements that influence consumer buying interest, but some of them are rarely quantified, such as the impact of national culture on the use of digital marketing. This study uses a combination of methods. 106 respondents made up the study's quantitative sample, while 8 informants made up the study's qualitative sample. The smartPLS tool is used to assist in the data analysis for this investigation. The findings demonstrated that the impact of digital marketing had a favorable affect on consumer purchasing interest. The influence of national culture on consumer purchasing interest is beneficial.
THE INFLUENCE OF EASE OF USE, SHOPPING EXPERIENCE, AND SATISFACTION ON INTEREST TO REPURCHASE AT SHOPEE ONLINE STORES IN DENPASAR CITY richadinata, kadek riyan putra; Carla Rettobjaan, Vitalia Fina
Moneter: Jurnal Keuangan dan Perbankan Vol. 11 No. 1 (2023): APRIL
Publisher : Universitas Ibn Khladun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32832/moneter.v11i1.141

Abstract

Technological developments have penetrated the world of the trade industry known as E-commerce, one of the most popular E-commerce today is Shopee. Various conveniences and comforts provided by business activists who take advantage of marketplace containers in the world of trade. But no less important is how to maintain consumer interest or repurchasing power which is difficult. This is what will be examined in this study. This study aims to determine the effect of ease of use, shopping experience, and satisfaction on repurchase intention at the online shop Shopee. The design of this study is descriptive correlational with a cross sectional approach. The sample used in this study was 100 people who were taken using a non-probability sampling technique with a consecutive sampling approach. Data were collected using a questionnaire, then analyzed bivariately using the Spearman'rank test and multivariate analysis using logistic regression. The results of the bivariate analysis showed that there was an effect of ease of use, shopping experience and satisfaction on repurchase intention with p < 0.05. In the multivariate analysis, the results show that the consumer's shopping experience has the most influence on repurchase intention with AOR=36,591; 95%. Consumer repurchase intention is strongly influenced by many factors, one of which is the ease of use factor, shopping experience and satisfied response felt by consumers
Strategy Implementation of Green Ethics Concept in Human Resource Management Purnawati, Ni Luh Gede Putu Purnawati; Widnyani, Ni Made; Darmayanti, Ni Luh; Wahyuningsih, Luh Gde Nita Sri; Yudiastra, Putu Pande
Moneter: Jurnal Keuangan dan Perbankan Vol. 11 No. 1 (2023): APRIL
Publisher : Universitas Ibn Khladun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32832/moneter.v11i1.142

Abstract

The world is entering a transitional phase from the Industrial Revolution 4.0 to Society 5.0. One of the indicators of this transition is the emergence of various companies or organizations that make internal policies that are oriented towards increasing the value and welfare of their members. The strategy implemented is expected to stimulate the transition process to be faster and more measurable. Companies that want sustainability need to be consistent so that the policies implemented are in line with company goals. In this case, the policies designed are related to the development and management of human resources based on moral and ethical values (green ethics). This study aims to see what indicators are involved in implementing the policy and what steps should be taken by the Human Resource Development (HRD) team as the policy operator. The researcher uses a qualitative research method which is a description of the results of the literacy study to describe the research results more effectively. Based on the research results, green ethics policies have three key indicators as the main fundamentals, including green environment, green people, and green spirituality. The implementation of green ethics policies will be able to improve the quality of human resources which will indirectly help the company to remain sustainable.
Method for Managing Human Resources Better in Digital Marketing Surya Astitiani, Ni Luh Putu; widnyani, Ni made; Darmayanti, Ni Luh; Wahyuningsih, Luh Gde Nita Sri; Carla Rettobjaan, Vitalia Fina
Moneter: Jurnal Keuangan dan Perbankan Vol. 11 No. 1 (2023): APRIL
Publisher : Universitas Ibn Khladun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32832/moneter.v11i1.148

Abstract

Modern business trends are becoming more diverse as technology, particularly digital marketing, develops. The idea behind and use of digital marketing is an endeavor to increase sales of goods from a brand. Every human resource in the organization must be able to master this competency because it is the key to the growth of the business overall. Human resources must come up with plans to increase employee proficiency in digital marketing. The goal of the approach is to improve marketers' understanding of potential customers, their communication skills, and their capacity to identify the best marketing mix for each target market. The most effective digital marketers are those who have a clear understanding of how each campaign supports the goals of the offering. Digital marketers can use their free or paid media to produce broader campaigns depending on the objectives of their marketing plan. In order to increase the company's human resources' proficiency in digital marketing, this study focuses on the deployment of efficient training programs. A review of the literature using descriptive qualitative processing techniques was the research methodology used in this study.

Page 1 of 16 | Total Record : 151

 1   2   3   4   5 

Filter by Year

2023 2025


Reset
Filter By Issues
All Issue Vol. 13 No. 2 (2025): JULI Vol. 13 No. 1 (2025): APRIL Vol. 12 No. 3 (2024): OKTOBER Vol. 12 No. 2 (2024): JULI Vol. 12 No. 1 (2024): APRIL Vol. 11 No. 2 (2023): OKTOBER Vol. 11 No. 1 (2023): APRIL