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Jurnal Informatika Ekonomi Bisnis
Published by Universitas Putra Indonesia YPTK Padang
ISSN : 27148491     EISSN : -     DOI : https://doi.org/10.37034/infeb
Core Subject : Economy,
Economics, Econometrics & Finance
Jurnal Informatika Ekonomi Bisnis adalah Jurnal Nasional, yang didedikasikan untuk publikasi hasil penelitian yang berkualitas dalam bidang Informatika Ekonomi dan Bisnis, namun tak terbatas secara implisit. Jurnal Informatika Ekonomi Bisnis menerbitkan artikel secara berkala 4 (empat) kali setahun yaitu pada bulan Maret, Juni, September, dan Desember. Semua publikasi di jurnal ini bersifat terbuka yang memungkinkan artikel tersedia secara bebas online tanpa berlangganan. Jurnal Informatika Ekonomi Bisnis sebagai media kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis dalam bidang informatika ekonomi dan bisnis. Sebagai bagian dari semangat menyebarluaskan ilmu pengetahuan hasil dari penelitian dan pemikiran untuk pengabdian pada masyarakat luas, serta sebagai sumber referensi akademisi dalam bidang informatika ekonomi dan bisnis.
Arjuna Subject : Bisnis, Menejemen, dan Akutansi (semua kategori) - Bisnis, Menejemen, dan Akutansi (Lain-Lain)
Articles 616 Documents
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Analisis Efektivitas Metode Turun Lapangan dalam Menentukan Penerima Bansos terhadap Distribusi Bansos Rizti, Muthia; Kusmilawaty; Fahdhila, Tri Inda
Jurnal Informatika Ekonomi Bisnis Vol. 7, No. 3 (September 2025)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v7i3.1233

Abstract

This study aims to determine the effectiveness of the field method in determining recipients of social assistance, through the Integrated Referral Service System at the Tanjungbalai City Social Service. Based on the results of the study, it was found that the implementation of the SLRT program in Tanjungbalai City has been running quite well. This type of research is descriptive research with a qualitative approach. The specific results obtained are, the SLRT program in Tanjungbalai City shows progress in achieving target accuracy and timeliness, although there are still some errors in collecting recipients. Then, although the data used in this program is quite complete, there are some discrepancies between the existing data and conditions in the field, especially related to the changing economic status of recipients. Then, the SLRT program in Tanjungbalai City has successfully adapted well to field conditions, especially with geographical and accessibility limitations. Then, socialization regarding the SLRT program has been carried out quite well to the sub-district and village levels, although there are still some people who do not fully understand how this program works and its objectives. Overall, this study shows that the SLRT program in Tanjungbalai City can be said to be effective, but several aspects such as targeting accuracy, data updates, and socialization need to be improved to achieve more optimal results in poverty alleviation.
Pengaruh Product Quality dan Brand Experience terhadap Kepuasan Konsumen Refani, Irsya Dwi; Adityarini, Esthi; Irawan, Anggi
Jurnal Informatika Ekonomi Bisnis Vol. 7, No. 3 (September 2025)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v7i3.1216

Abstract

This research was grounded in the decline in sales experienced by the Innisfree brand in recent times. Multiple variables affect this phenomenon, such as product quality and brand experience. Therefore, this research aimed to examine the influence of product quality and brand experience on Innisfree consumer satisfaction. A quantitative approach was employed by distributing questionnaires and using multiple linear regression analysis on 101 respondents. The outcomes indicated that product quality and brand experience jointly influence consumer satisfaction, with a contribution of 69.9%. It is evident that product quality and brand experience are important factors in increasing consumer satisfaction, thereby helping the company address its declining sales.
Pengimplementasian Metode Simple Multi Attribute Rating Technique pada Sistem Pendukung Keputusan: Literatur Review Adha, Hafid Dwi; Zen, Lova Endriani; Hanim, Hafizah; Prasetyo, Haditya; Novi
Jurnal Informatika Ekonomi Bisnis Vol. 7, No. 3 (September 2025)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v7i3.1267

Abstract

The rapid development of technology today paves the way for the birth of various scientific inventions. Technology can assist decision-makers in determining a decision to be reached. One technology that can be utilized is a decision support system. Decision support systems can help reduce uncertainty and make the decision-making process more efficient. The Simple Multi-Attribute Rating Technique method is one of them, a method that can be applied to decision support systems. This study aims to be a literature review that can help researchers apply the Simple Multi-Attribute Rating Technique method in further research. This study presents 10 articles from national and international accredited journals that use the Simple Multi-Attribute Rating Technique method in their research. The Simple Multi-Attribute Rating Technique method can be used in various case studies, evaluation of student final assignment guidance, identification of employee performance, for selecting the best employees, determining sanctions, and selecting the best cafes in an area.
Model Prediksi Ketercapaian Learning Outcome Based Education Mahasiswa di Program Studi Teknik Informatika Menggunakan Algoritma Machine Learning Danny, Muhtajuddin; Fatchan, Muhamad
Jurnal Informatika Ekonomi Bisnis Vol. 7, No. 3 (September 2025)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v7i3.1259

Abstract

The Informatics Engineering Undergraduate Program, Faculty of Engineering, Pelita Bangsa University, implements Outcome Based Education (OBE) by emphasizing the achievement of student Learning Outcomes (LO) as an indicator of the quality of learning in higher education. LO achievement measurement has been mostly done manually through academic assessments, so it is less than optimal in predicting student performance comprehensively. This study aims to build a prediction model for student Learning Outcomes achievement using machine learning algorithms. Research data were obtained from academic results, attendance, lecture activities, and student skill indicators. The prediction model was developed by comparing the Support Vector Machine (SVM), Random Forest, Decision Tree, and Artificial Neural Network (ANN) algorithms, with performance evaluation using accuracy, precision, recall, and F1-score metrics. The results showed that the Random Forest algorithm provided the best performance with more stable accuracy compared to other algorithms. Furthermore, the distribution of Program Learning Outcomes (PLO) in the curriculum shows: PLO 1 (57 courses), PLO 2 (10 courses), PLO 3 (3 courses), PLO 4 (27 courses), PLO 5 (8 courses), PLO 6 (20 courses), PLO 7 (33 courses), PLO 8 (10 courses), PLO 9 (54 courses), and PLO 10 (57 courses). Based on student scores in 57 courses, the distribution of assessment categories is as follows: Very Good 38.1%, Good 46.3%, Fair 8.4%, and Fail 7.2%. Thus, the PLO achievement of the Informatics Engineering Undergraduate Study Program reached 84.4% in the Good and Very Good categories. This finding provides a significant contribution to efforts to monitor and plan strategies for improving the quality of OBE-based learning adaptively and data-driven.
Analisis Sentimen Ulasan Aplikasi Jamsostek dengan SVM, Random Forest, dan Logistic Regression Butsianto, Sufajar; Rifa'i, Anggi Muhammad
Jurnal Informatika Ekonomi Bisnis Vol. 7, No. 3 (September 2025)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v7i3.1266

Abstract

The digitalization of public services has encouraged the development of the Jamsostek Mobile (JMO) application by BPJS Ketenagakerjaan. This application is expected to provide convenience in accessing information, JHT claims, and other services. However, user reviews on the Google Play Store show diverse perceptions, ranging from satisfaction to technical complaints. This study aims to conduct sentiment analysis on user reviews of the JMO application by classifying opinions into positive, negative, and neutral sentiments. Data were collected through crawling from the Google Play Store and processed using text preprocessing stages, including data cleaning, case folding, stopword removal, tokenization, stemming, and Term Frequency–Inverse Document Frequency (TF-IDF) weighting. The classification process was then carried out using three machine learning algorithms, namely Support Vector Machine (SVM), Random Forest, and Logistic Regression. The results indicate that negative sentiment dominates with 46%, followed by positive sentiment at 40% and neutral at 14%. Most complaints are related to login difficulties, application errors, and technical bugs in claim features. In terms of algorithm performance, SVM with a linear kernel achieved the highest accuracy of 87.5% and an F1-score of 0.87, outperforming Random Forest (85.3%) and Logistic Regression (82.7%). Academically, this study reinforces the effectiveness of SVM in sentiment analysis using TF-IDF, while practically providing recommendations for BPJS Ketenagakerjaan to improve system stability, login speed, and reduce application bugs to enhance user satisfaction.
Pengaruh Pelatihan, Motivasi dan Disiplin terhadap Kinerja Pegawai dengan Kepuasan Kerja Sebagai Variabel Intervening Anantha, Anggun; Wiratha, Andre; Adif, Riandy Mardhika
Jurnal Informatika Ekonomi Bisnis Vol. 7, No. 3 (September 2025)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v7i3.1274

Abstract

The main problem in the research is that in 2024 the performance of BPBD Tanah Datar Regency employees will decrease from the previous year. The motivation given to Tanah Datar Regency BPBD employees has not been maximized so that interest in improving performance is difficult to achieve. The role of job satisfaction as a mediating factor in the relationship between training, motivation and work discipline on employee performance has not been analyzed in depth, so its impact on improving performance has not been properly measured. The aim of the research is to explain the influence of training, motivation and discipline on employee performance with job satisfaction as an intervening variable at BPBD Tanah Datar. The type of research used was quantitative research with a field approach with a sample size of 36 employees at BPBD Tanah Datar Regency. The data analysis technique used in this study was path analysis. The results showed that training had a significant effect on employee performance, motivation had no significant effect on employee performance, discipline had a significant effect on employee performance, training had a significant effect on job satisfaction, motivation had a significant effect on job satisfaction, and discipline had a significant effect on job satisfaction. Job satisfaction mediated the effect of training on employee performance at the Tanah Datar Regency Regional Disaster Management Agency (BPBD), while job satisfaction did not mediate the effect of motivation on employee performance at the Tanah Datar Regency Regional Disaster Management Agency (BPBD), and job satisfaction mediated the effect of discipline on employee performance at the Tanah Datar Regency Regional Disaster Management Agency (BPBD).
Perbandingan Metode Klasifikasi dalam Memprediksi Penyakit Ginjal Kronis Ermanto; Surojudin, Nurhadi
Jurnal Informatika Ekonomi Bisnis Vol. 7, No. 3 (September 2025)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v7i3.1263

Abstract

Chronic Kidney Disease (CKD) is a global health issue with an increasing prevalence that poses a significant economic burden on healthcare systems. Early detection of CKD is crucial to provide proper treatment before the disease progresses to end-stage renal failure. With technological advancements, machine learning methods have been widely utilized to support medical diagnosis with greater speed and accuracy. This study aims to compare the performance of two popular classification algorithms, Decision Tree C4.5 and Naïve Bayes, in predicting CKD using a public dataset from the UCI Machine Learning Repository consisting of 400 patient records with 24 clinical attributes. The research process involved systematic preprocessing steps, including handling missing values, transforming categorical data into numerical form, and selecting relevant attributes. Model evaluation was conducted using 10-Fold Cross Validation with performance metrics such as accuracy, precision, recall, Area Under the Curve (AUC), and statistical T-Test. The results show that Decision Tree C4.5 achieved an accuracy of 93.00%, precision of 84.27%, recall of 100%, and an AUC of 0.944, while Naïve Bayes obtained an accuracy of 93.50%, precision of 85.23%, recall of 100%, and an AUC of 0.948. Although the performance differences between both algorithms are relatively small and statistically insignificant, Naïve Bayes demonstrated slightly better results in terms of accuracy and AUC, while Decision Tree C4.5 offers advantages in interpretability through its classification rules. In conclusion, both algorithms are effective for early CKD diagnosis, and the choice may depend on practical needs, whether emphasizing interpretability or computational efficiency. This study contributes to the development of more accurate and efficient clinical decision support systems for improving healthcare services in CKD management.
Kepemimpinan Etis dan Dukungan Organisasi terhadap Perilaku Kewargaan Organisasional Mahasiswa Anggota UKM di Tanjungpinang Fani, Lastri Anggi; Randa, Fradya; Sufnirayanti
Jurnal Informatika Ekonomi Bisnis Vol. 7, No. 3 (September 2025)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v7i3.1269

Abstract

This study aims to analyze the influence of ethical leadership and perceived organizational support on organizational citizenship behavior (OCB) among students actively involved in Student Activity Units (UKM) in Tanjungpinang. The phenomenon of low voluntary participation among students in organizational activities highlights the need to examine factors that may enhance such extra-role behaviors. A quantitative approach with a survey design was employed, and data were collected through questionnaires distributed to 120 active UKM students. The data were analyzed using multiple linear regression. The findings indicate that ethical leadership does not have a significant effect on students’ OCB. In contrast, perceived organizational support was found to have a positive and significant effect on OCB. Furthermore, when tested simultaneously, ethical leadership and perceived organizational support significantly influence OCB, with 98 percent of the variance in students’ behavior explained by these two variables, while the remaining 2 percent is explained by other factors outside the research model. These results emphasize that perceived organizational support plays a dominant role in shaping students’ OCB, while ethical leadership still serves as a complementary factor that strengthens the overall model.
Design Kualitas Electronic Word of Mouth terhadap Kinerja Pemasaran Melalui Brand Image Selvi, Maria Jenia; Hiong, Lauw Sun
Jurnal Informatika Ekonomi Bisnis Vol. 7, No. 3 (September 2025)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v7i3.1270

Abstract

The ease of access to capital for MSMEs has led to their continued growth. It is known that food and beverage businesses in Pontianak are very diverse, and entrepreneurs can strive to build a positive image, for example by developing the appeal of their products, starting from unique packaging, guaranteed product quality, and marketing methods, both digitally and non-digitally. A good image plays an important role and can encourage existing customers to provide positive reviews. A strategy that entrepreneurs can implement in marketing is to utilize electronic word of mouth, with this information about products conveyed through a good brand image by customers will ultimately increase sales and profits. The study used a quantitative method and a causal approach, namely examining the cause-and-effect relationship between the variables EWOM (x), brand image (z) and marketing performance (y). Data were collected through a questionnaire based on a numeric rating scale, namely a value of 1 to 10. The research population was MSMEs in the food and beverage sector in Pontianak. The sample determined was 147 respondents with a purposive sampling technique, and the data were analyzed using analysis of moment structures (AMOS). The results of the study indicate that electronic word of mouth (EWOM) influences brand image, marketing performance, brand image, and marketing performance through brand image.
Managerial Competence, GHRM dan Green Accounting terhadap Keberlanjutan Ekowisata Satria, Mohd Rhana; Sari, Rizki Yuli
Jurnal Informatika Ekonomi Bisnis Vol. 7, No. 3 (September 2025)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v7i3.1264

Abstract

This study aims to analyze the effect of managerial competence, green human resource management (GHRM), and green accounting on ecotourism sustainability in Community-Based Tourism Groups (Pokdarwis) in the coastal tourism areas of Bintan. The research employed a quantitative approach with a survey method to several Pokdarwis in Bintan. Data were analyzed through validity and reliability tests, as well as multiple linear regression analysis. The findings reveal that managerial competence and green accounting particularly in recording and managing conservation costs have a significant positive effect on ecotourism sustainability, while GHRM shows a significant negative effect. Simultaneously, the three variables contribute 93.5% to ecotourism sustainability. These results highlight the importance of strengthening managerial competence and optimizing the recording of conservation costs through green accounting, as well as evaluating GHRM practices to make them more effective in supporting ecotourism sustainability.

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