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Analysis of the Influence of Technology, Information, and Communication Developments on Economic Growth in Java Island 2018 – 2022 Elang, Elang Mulya Maulana; Kusuma, Hendra
Jurnal Ilmu Ekonomi JIE Vol. 8 No. 04 (2024): Jurnal Ilmu Ekonomi
Publisher : Program Studi Ekonomi Pembangunan Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/jie.v8i04.35419

Abstract

This study aims to analyze the influence of the number of cellular phone users, internet users, e-commerce users, and labor force on economic growth in Java. This research is included in quantitative research. The data used in this study is panel data, which comes from a combination of cross-section data from 6 provinces on Java Island and data. In this study, the data analysis technique used is panel data regression analysis to determine the effect of technology, information, and communication variables on economic growth variables. Panel data is a combination of time series data and cross-section data. The results showed that the number of cellular phone users had a positive and significant effect on economic growth, while the number of Internet users and E-Commerce users had a significant negative effect on economic growth, while the labor force had a positive and insignificant effect on economic growth.
Perspective Transformation Automation In Identification Of Parking Lot Status With Blob Detection Mubin, Mohammad Nasrul; Kusuma, Hendra; Rivai, Muhammad
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 7, No 2 (2023): July
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v7i2.364

Abstract

Implementation of automation greatly facilitates the work of a system. This research automates the search for perspective transformation coordinates. In previous study, the process was done manually and was considered time-consuming and costly. The search for these coordinates is carried out with the help of red circles at several points in the parking area to be identified. There are two cases of images to be automated, namely the image of the parking area without obstacles and with obstacles. In the unobstructed images, the identification of transformation coordinates is carried out by identifying the coordinates of the auxiliary circle. Whereas in the images with obstructions, the identification of the transformation coordinates also involves the intersection equations of lines. The process of identifying the coordinates is done with the condition of the parking lot without a single vehicle. Once the coordinates are obtained, all coordinates are stored and will be used in the perspective transformation process in status parking slot identification stage. The identification stage is same with previous study. The proposed system 100% able to identify the transformation coordinates and carry out the perspective transformation process as expected. Of the 900 samples in each case, we acquire 100% recall, and most of the parking slot identification status being above 85% precision and accuracy. Compared to previous studies, the proposed system is more effective, with recall, precision, and accuracy values at 100%. The effectiveness of the proposed system is even more evident with average data automation time is 31.689 seconds.
Deep Neural Network for Visual Localization of Autonomous Car in ITS Campus Environment Dikairono, Rudy; Kusuma, Hendra; Prajna, Arnold
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 7, No 2 (2023): July
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v7i2.365

Abstract

Intelligent Car (I-Car) ITS is an autonomous car prototype where one of the main localization methods is obtained through reading GPS data. However the accuracy of GPS readings is influenced by the availability of the information from GPS satellites, in which it often depends on the conditions of the place at that time, such as weather or atmospheric conditions, signal blockage, and density of a land. In this paper we propose the solution to overcome the unavailability of GPS localization information based on the omnidirectional camera visual data through environmental recognition around the ITS campus using Deep Neural Network. The process of recognition is to take GPS coordinate data to be used as an output reference point when the omnidirectional camera takes images of the surrounding environment. Visual localization trials were carried out in the ITS environment with a total of 200 GPS coordinates, where each GPS coordinate represents one class so that there are 200 classes for classification. Each coordinate/class has 96 training images. This condition is achieved for a vehicle speed of 20 km/h, with an image acquisition speed of 30 fps from the omnidirectional camera. By using AlexNet architecture, the result of visual localization accuracy is 49-54%. The test results were obtained by using a learning rate parameter of 0.00001, data augmentation, and the Drop Out technique to prevent overfitting and improve accuracy stability.
Pengaruh Kualitas Pelayanan dan Harga terhadap Kepuasan Pelanggan Pada Produksi Roti “Banana” di Kediri Hanggondosari, Sri Utami; Riyanah, Riyanah; Kusuma, Hendra; Purwanti, Yuli
Jurnal Pendidikan Tambusai Vol. 9 No. 2 (2025): Agustus
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jptam.v9i2.27798

Abstract

Penelitian ini bertujuan untuk menganalisis dampak dari pengungkapan Corporate Social Responsibilty dan kualitas audit terhadap biaya utang. Ukuran perusahaan, return on assets, dan leverage dijadikan sebagai variabel kontrol dalam penelitian ini. Metode penelitian ini menggunakan data laporan keuangan perusahaan yang telah dipublikasikan di Bursa Efek Indonesia sebagai sampel yang akan diuji menggunakan regresi panel. Perangkat lunak yang digunakan adalah SPSS dan Eviews10. Hasil penelitian ini menunjukkan bahwa pengungkapan Corporate Social Responsibility tidak memiliki pengaruh terhadap biaya utang. Sedangkan kualitas audit berpengaruh secara signifikan negatif terhadap biaya utang. Hasil variabel kontrol menunjukkan bahwa return on assets berpengaruh secara signifikan negatif terhadap biaya utang, dan ukuran perusahaan serta leverage tidak berpengaruh secara signifikan terhadap biaya utang
PENGARUH STRATEGI PEMASARAN ONLINE TERHADAP MINAT BELI KONSUMEN (STUDI KASUS PADA TOKO BERHIJAB.CO) Aryanti, Pia; Pinandita, Candra Pramula; Kusuma, Hendra
JUMBA (Jurnal Manajemen, Bisnis, dan Akuntansi) Vol 4 No 1 (2025): JUMBA (Jurnal Manajemen, Bisnis, dan Akuntansi)
Publisher : Universitas Pawyatan Daha

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Adanya urgensi berkaitan dengan strategi pemasaran online dalam era digital untuk menarik minat beli konsumen melatarbelakangi dilaksanakannya penelitian ini, di mana Toko Berhijab.co, merupakan salah satu usaha yang memanfaatkan media sosial dan platform digital, memerlukan analisis lebih lanjut untuk mengukur efektivitas strategi tersebut dalam meningkatkan daya saing dan minat beli konsumen. Penelitian ini dilakukan untuk mengetahui apakah strategi pemasaran online yang dilakukan oleh Berhijab.Co berpengaruh terhadap minat beli konsumennya. Metode kuantitatif digunakan untuk melakukan penelitian ini, dimana data dikumpulkan menggunakan instrumen angket sejumlah 14 item dengan pengukuran skala likert 5 poin yang disebarkan secara daring melalui google form. Populasi yang diteliti adalah seluruh konsumen Berhijab.Co dengan sampel 70 responden yang dipilih menggunakan teknik Accidental Sampling. Analisis data menggunakan regresi linear sederhana berbantuan aplikasi IBM SPSS Statistics 26. Diperoleh bahwa strategi pemasaran online yang digunakan oleh Berhijab.Co berpengaruh positif dan signifikan terhadap minat beli konsumen dengan pengaruh 33,4%, sedangkan sisanya dipengaruhi oleh variabel lain yang tidak menjadi objek penelitian ini. Adapun, penelitian ini juga menunjukkan persamaan regresi, yaitu .
The impact of institutional quality, market openness, and government size on corruption across income levels Kusuma, Hendra; Iskandar, Deden
Jurnal Perspektif Pembiayaan dan Pembangunan Daerah Vol. 13 No. 1 (2025): Jurnal Perspektif Pembiayaan dan Pembangunan Daerah
Publisher : Program Magister Ilmu Ekonomi Pascasarjana Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/ppd.v13i1.41725

Abstract

Government openness in managing the economy can stimulate growth, but carries the risk of policy misuse. This study analyzes panel data from 139 countries between 2012 and 2023 to examine the relationship between economic openness and corruption, as measured by the Corruption Perceptions Index (CPI). The findings reveal that key factors such as government integrity and financial freedom significantly influence CPI scores across countries with varying income levels. Nations characterized by flexible business regulations, transparent governance, strong legal protection of property rights, and stable monetary policies tend to exhibit lower levels of public sector corruption. However, the analysis also shows that financial freedom in high-income countries and investment freedom in upper-middle-income countries are negatively associated with CPI scores. This suggests that excessive liberalization—particularly in investment—without adequate regulatory oversight can increase corruption risks, likely due to limited transparency in capital flows and foreign investment practices. In contrast, when properly managed, the recognition of property rights, government integrity, and investment freedom are instrumental in reducing corruption in many middle-income countries. The study highlights the importance of strengthening government integrity, particularly in delivering public services and regulating an open economy. By ensuring effective and efficient oversight, countries can enhance their CPI scores and reduce the potential for corruption.
Sustainable Banking Practices and Cost Efficiency: Evidence on Profitability from Islamic Commercial Banks in Indonesia Fathihani; Sulistiyowati, Rini; Kusuma, Hendra
Al-Kharaj: Journal of Islamic Economic and Business Vol. 7 No. 2 (2025): All articles in this issue include authors from 3 countries of origin (Indonesi
Publisher : LP2M IAIN Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24256/kharaj.v7i2.7359

Abstract

This study aims to examine the effect of green banking implementation and operational cost efficiency on the profitability of Islamic Commercial Banks in Indonesia during the period 2020–2024. The variables used in this study include green banking as an exogenous variable, operational efficiency (BOPO) as an independent variable, and return on assets (ROA) as a measure of profitability. This quantitative study employs secondary panel data sourced from the annual reports of Islamic Commercial Banks registered with the Financial Services Authority (OJK). The analysis uses a path model approach. The results reveal that green banking has a positive and significant effect on ROA while BOPO has a significant negative effect on ROA. Simultaneous testing found that the implementation of green banking as measured by GCR and BOPO had a positive and significant influence on ROA.These findings indicate that sustainable banking practices and cost efficiency play a critical role in enhancing the financial performance of Islamic banks in Indonesia.
Sustainable Banking Practices and Cost Efficiency: Evidence on Profitability from Islamic Commercial Banks in Indonesia Fathihani; Sulistiyowati, Rini; Kusuma, Hendra
Al-Kharaj: Journal of Islamic Economic and Business Vol. 7 No. 2 (2025): All articles in this issue include authors from 3 countries of origin (Indonesi
Publisher : LP2M IAIN Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24256/kharaj.v7i2.7359

Abstract

This study aims to examine the effect of green banking implementation and operational cost efficiency on the profitability of Islamic Commercial Banks in Indonesia during the period 2020–2024. The variables used in this study include green banking as an exogenous variable, operational efficiency (BOPO) as an independent variable, and return on assets (ROA) as a measure of profitability. This quantitative study employs secondary panel data sourced from the annual reports of Islamic Commercial Banks registered with the Financial Services Authority (OJK). The analysis uses a path model approach. The results reveal that green banking has a positive and significant effect on ROA while BOPO has a significant negative effect on ROA. Simultaneous testing found that the implementation of green banking as measured by GCR and BOPO had a positive and significant influence on ROA.These findings indicate that sustainable banking practices and cost efficiency play a critical role in enhancing the financial performance of Islamic banks in Indonesia.
SOSIALISASI BANK DIGITAL UNTUK KEGIATAN PRODUKTIF MANAJEMEN KEUANGAN DI GEREJA GBT KRISPASIH KEDIRI Hanggondosari, Sri Utami; Riyanah, Riyanah; Kusuma, Hendra; Mardijani, Prastiwi
Dharma Wiyata: Jurnal Pengabdian Kepada Masyarakat Vol 2 No 2 (2024): Dharma Wiyata
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Pawyatan Daha

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Abstract This community service aims to introduce digital banking and usage techniques for productive financial management activities at the GBT Krispasih Church in Kediri. The target is to increase knowledge and change the way participants view Digital Banking in practice. The activity was carried out on April 16 2024. After discussions with the Church Council management community, it was agreed that the activity would begin with an explanation of Digital Bank, its uses, as well as identification of positive and negative impacts through a direct question and answer process with participants. This activity ran smoothly and according to target. There were 29 participants who attended. There are some who are familiar with online transactions but don't have a business. The result of this community service is that participants admit that they have become clearer about Digital Banks and Conventional Banks, digital transactions, uses and techniques to avoid negative things and the characteristics of digital fraud. So it can be concluded that participants have increased their abilities regarding Digital Banking and its practical use for productive things.
Lung sound classification using YAMNet, neural network, and augmentation Arifin, Jaenal; Sardjono, Tri Arief; Kusuma, Hendra
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i5.pp4101-4112

Abstract

Globally, lung disease occupies a significant position as one of the main contributors to mortality rates. The characteristics of human respiratory sound signals can show a wide spectrum, ranging from normal patterns to indications of lung abnormalities. The proposed lung sound classification system is based on YAMNet as a pre-trained neural network model for medical audio recognition, which is then refined using artificial neural networks (ANN). This study presents the integration of multiple datasets and advanced pre-processing approaches. A total of 1,363 lung sound recordings from Kaggle, ICBHI, and Mendeley. This reflects the variety of clinical conditions, and differences in recording devices are combined. In order to increase the diversity of lung sound signal input, the pre-processing process is carried out through several stages, including adjusting the sampling frequency to 4 kHz, segmenting for 6 seconds, signal filtering with wavelet, min–max normalization, and data augmentation using window warping, jittering, cropping, and padding. A fold cross-validation scheme is employed to comprehensively evaluate the model's effectiveness. The evaluation results indicate that the model achieves an accuracy of 93.64%, a precision of 93.60%, a recall of 93.64%, and an F1-score of 93.52%, collectively reflecting outstanding classification performance. This work may incorporate deep learning technology into clinical practice, ultimately improving diagnosis accuracy and efficiency in the hospital setting.