Article Per Year (5 Year)
p-Index From 2021 - 2026
2.679
P-Index
This Author published in this journals
All Journal Techno.Com: Jurnal Teknologi Informasi QALAMUNA: Jurnal Pendidikan, Sosial, dan Agama Syntax Literate: Jurnal Ilmiah Indonesia Jurnal Riset Informatika Jurnal Mantik Jurnal Informatika Ekonomi Bisnis Daengku: Journal of Humanities and Social Sciences Innovation Jurnal Ekonomi Jurnal Terapan Ilmu Manajemen dan Bisnis (JTIMB) Klabat Accounting Review Jurnal Informatika Ekonomi Bisnis Klabat Journal of Management JER Jurnal Ekonomi, Manajemen, Akuntansi
Tonny Irianto Soewignyo
Dosen Fakultas Ekonomi Dan Bisnis Universitas Klabat
Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences Other

Published : 17 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 17 Documents
Search

 1   2 
The Influence of Work Motivation and Work Discipline on Employee Performance Manado Independent School Soewignyo, Tonny; Paat, Silvia Friska; Kainde, Llly Linne; Mandagi, Deske Wenske; Petir, Abraham Leslie; Rantung, Rinny Cherryl
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/syntax-literate.v9i11.52375

Abstract

This research aims to investigate the influence of motivation and discipline on employee performance at Manado Independent School. Utilize quantitative research methods to determine whether motivation and discipline have an impact on employee performance. Primary data sources were used for this study. The data analysis method employed was multiple linear regression analysis conducted using SPSS 26 software. Data collection was carried out by distributing questionnaires to 100 respondents. Overall, the results of the multiple linear regression analysis and hypothesis testing suggest that motivation and discipline have a positive and significant influence when considered simultaneously, with a p-value of 0.000 < 0.05. The coefficient value is 1.87, and the adjusted R-squared value is 76.31%. Consequently, it can be concluded from this study that, partially, the variable of work motivation does not have a significant influence on employee performance, whereas the variable of work discipline has a significant impact on employee performance productivity. Therefore, efforts should be made to enhance work motivation to positively impact employee performance.
Exploring City Brand Gestalt Driver: The Case of Bitung City Mandagi, Deske W.; Darvel Civlie Walone; Tonny Irianto Soewignyo
Jurnal Ekonomi Vol. 13 No. 02 (2024): Jurnal Ekonomi, Edition April - June 2024
Publisher : SEAN Institute

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

Abstract

As urban landscapes evolve rapidly and competition among cities intensifies for economic growth and global recognition, the imperative to understand the dynamics of City Brand Gestalt (CBG) has heightened. This study aims to delve into the architecture of CBG by assessing the impact of its four dimensions (namely Story, Sensescape, Servicescape, and Stakeholder) on shaping Bitung City's overall brand gestalt. This research holds significance in formulating development strategies for CBG aimed at improving the economy of Bitung City, particularly in the tourism sector. A quantitative descriptive and causal research design was adopted by distributed and collected 250 self-administered online questionnaires from Bitung City visitors between January and May 2023. Structural Equation Modeling using SmartPLS was employed to determine the significant influence of each dimension on brand gestalt. The results confirmed the significant role of the 4S dimensions namely, story, sensescape, servicescape, and stakeholder in shaping the overall city brand gestalt.  In summary, this research underscores significant implications for city marketers and policymakers, emphasizing the necessity of crafting an appealing and positive brand narrative to enhance the image of a city. This, in turn, can bolster the city's economy, particularly in terms of tourism and other sectors.
Peran Social Commerce dalam Meningkatkan Kepercayaan Konsumen dan Niat Beli Soewignyo , Tonny Irianto; Soewignyo, Fanny; Ambalao, Shapely
Jurnal Economic Resource Vol. 8 No. 2 (2025): September - February
Publisher : Fakultas Ekonomi & Bisnis Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57178/jer.v8i2.2000

Abstract

Penelitian ini mengkaji peran social commerce dalam membangun kepercayaan dan meningkatkan niat beli konsumen melalui pendekatan Systematic Literature Review (SLR) berdasarkan pedoman PRISMA. Dari 815 artikel awal, tujuh studi utama dianalisis secara mendalam. Hasil penelitian menunjukkan bahwa interaksi sosial, ulasan konsumen (OCR/e-WOM), dan konten buatan pengguna menjadi faktor kunci pembentuk trust. Live streaming commerce memperkuat kepercayaan melalui demonstrasi produk real-time dan kualitas informasi yang tinggi, sedangkan influencer berperan signifikan dalam membentuk kredibilitas dan keputusan pembelian. Sistem reputasi digital seperti rating dan review juga terbukti mengurangi ketidakpastian konsumen. Temuan ini dirangkum dalam kerangka Stimulus–Organism–Response (S-O-R), yang menunjukkan bahwa stimulus sosial mempengaruhi respon kognitif-emosional konsumen dan berujung pada niat serta keputusan pembelian. Studi ini menekankan pentingnya strategi interaksi digital dan kredibilitas influencer dalam meningkatkan performa social commerce.
Evaluasi Kinerja Algoritma Apriori dan FP-Growth untuk Association Rule Mining pada Data Transaksi Ritel Soewignyo, Fanny; Soewignyo, Tonny Irianto; Mokodaser, Wilsen Grivin; Silitonga, Argha Orion
Techno.Com Vol. 24 No. 4 (2025): November 2025
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v24i4.14952

Abstract

Ledakan data transaksi ritel yang terekam melalui sistem Point of Sale (POS) dan platform daring menuntut metode analisis yang efektif untuk menggali pola pembelian konsumen. Association Rule Mining merupakan pendekatan populer untuk menemukan keterkaitan antarproduk, dengan algoritma Apriori dan FP-Growth sebagai dua metode yang paling banyak digunakan. Penelitian ini bertujuan memberikan gambaran empiris mengenai efektivitas kedua algoritma tersebut pada data transaksi ritel yang nyata. Metode yang digunakan meliputi tahapan data understanding untuk mengenali struktur data, data cleaning untuk menghapus nilai kosong dan menyeragamkan format, serta data transformation menggunakan TransactionEncoder untuk mengubah data mentah menjadi format biner (one-hot encoded). Selanjutnya algoritma Apriori dan FP-Growth dijalankan dengan parameter yang sama untuk menghasilkan frequent itemsets dan aturan asosiasi. Evaluasi kinerja dilakukan dengan mengukur waktu pemrosesan, jumlah aturan yang dihasilkan, serta nilai support, confidence, dan lift tertinggi. Hasil penelitian menunjukkan bahwa kedua algoritma menghasilkan jumlah aturan yang sama (63 aturan) dengan support tertinggi 0,06, confidence tertinggi 0,51, dan lift tertinggi 3,29, tetapi waktu pemrosesan berbeda signifikan (Apriori 0,39 detik, FP-Growth 6,95 detik). Kesimpulannya, association rule mining efektif mengungkap pola pembelian konsumen, dan algoritma Apriori lebih efisien untuk dataset kecil hingga menengah, sedangkan FP-Growth lebih sesuai untuk dataset yang jauh lebih besar. Keywords - Association Rules, Apriori, FP-Growth, Frequent Itemset, Transaksi Ritel.
FORECASTING HEALTH INSURANCE PAYER INCOME: A COMPARATIVE ANALYSIS OF DECISION TREE AND SVR ALGORITHMS Wilsen Grivin Mokodaser; Tonny Irianto Soewignyo; George Morris William Tangka; Fanny Soewignyo
Jurnal Riset Informatika Vol. 7 No. 3 (2025): Juni 2025
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2466.493 KB) | DOI: 10.34288/jri.v7i3.369

Abstract

An insurance company is a type of non-bank financial institution that protects clients from risks and collects premiums over a certain period, these facts provide an overview of the insurance business and highlight its role in the economy, this study evaluated the performance difference between the Decision Tree Regressor and Support Vector Regression (SVR) in predicting insurance payer income. The Decision Tree model demonstrated strong predictive accuracy, achieving a Mean Absolute Error (MAE) of approximately 57 million and an R-squared (R²) value of 0.896, meaning it could explain around 89.6% of the variance in the data. Additionally, the model maintained high consistency, as evidenced by 5-fold cross-validation scores ranging from 0.908 to 0.967, indicating strong generalization and low risk of overfitting. In contrast, the SVR model significantly underperformed. It recorded a much higher MAE of over 237 million and a large Mean Squared Error (MSE), reflecting substantial deviations from the actual values. Its R² score of -0.299 suggests that SVR performed worse than a naive mean predictor, failing to identify meaningful patterns. This poor performance was consistent across all cross-validation folds, which also produced negative R² scores. The SVR model’s inadequacy is likely due to the large scale of the income data and the lack of proper preprocessing, such as normalization, or parameter tuning. Overall, these findings clearly demonstrate that the Decision Tree Regressor is a more suitable, accurate, and stable model for predicting insurance payer income.
PRODUCT SALES PREDICTION USING XGBOOST WITH FEATURE IMPORTANCE ANALYSIS FOR ADVERTISING MEDIA EVALUATION Wilsen Grivin Mokodaser; Tonny Irianto Soewignyo; Fanny Soewignyo
Jurnal Riset Informatika Vol. 8 No. 3 (2026): Juni 2026
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v8i3.537

Abstract

Product sales prediction plays a crucial role in supporting data-driven marketing strategies and optimizing advertising expenditures. Although previous studies have demonstrated the effectiveness of machine learning techniques for sales forecasting, most of them primarily focus on prediction accuracy and provide limited insights into the contribution of individual advertising channels to sales performance. This limitation reduces the interpretability and practical value of predictive models for business decision-making. Therefore, this study proposes a product sales prediction framework using Linear Regression as a baseline model and XGBoost Regression combined with Feature Importance Analysis for advertising media evaluation. The novelty of this study lies in integrating predictive modeling and interpretable analysis within a single framework, enabling both accurate sales prediction and the identification of influential advertising factors. Hyperparameter optimization and five-fold cross validation were employed to improve model reliability and robustness. Experimental results show that Linear Regression outperformed XGBoost, achieving an R² score close to 1.0, while XGBoost achieved an R² score of 0.953 with a mean cross-validation R² score of 0.950, indicating stable predictive performance. Feature Importance Analysis revealed that Affiliate Marketing was the most influential factor, followed by Billboards and Social Media. These findings contribute to marketing analytics by providing interpretable insights that support advertising budget optimization and more effective data-driven business decision-making.
Analisis Pengaruh Pemasaran Media Sosial Terhadap Kesadaran Merek Dan Loyalitas Merek: Peran Mediasi Brand Gestalt Risca Rioline Mokalu; Tonny Irianto Soewignyo
EKOMA : Jurnal Ekonomi, Manajemen, Akuntansi Vol. 4 No. 3: Maret 2025
Publisher : CV. Ulil Albab Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56799/ekoma.v4i3.6422

Abstract

Penelitian ini dilakukan dengan tujuan untuk mengetahui sejauh mana dan seberapa efektif penggunaan media sosial dalam memasarkan produk AKR Land Kawanua Emerald City. Serta strategi pemasaran ini dapat memperkuat brand dari proyek Kawanua Emerald City sehingga dapat lepas dari bayang-bayang proyek sister saat mengenalkannya kepada konsumen. Desain penelitian yang dipilih adalah pendekatan penelitian kualitatif studi kasus, yang bertujuan untuk memahami dan menjelaskan pengaruh Social Media Marketing. Dalam penelitian studi kasus ini, informan penelitian adalah tim Sales & Marketing Kawanua Emerald City yang menjadi sumber data primer dan untuk data sekunder akan menggunakan data perusahaan mulai dari laporan penggunaan tools media sosial dalam pemasaran dan penerapan strategi lainnya. Berdasarkan pengujian hipotesis yang telah dilakukan, dapat disimpulkan dengan beberapa hasil yaitu variabel Social Media Marketing tidak memiliki pengaruh terhadap brand gestalt, namun variabel Social Media Marketing memiliki pengaruh terhadap brand awareness dan brand loyalty. Selanjutnya variabel brand gestalt tidak memiliki pengaruh terhadap brand awareness, namun memiliki pengaruh terhadap brand loyalty pada karyawan PT AKR Land Kawanua Emerald City Manado. Terakhir, hasil penelitian menemukan bahwa kesadaran merek tidak berpengaruh terhadap loyalitas merek pada karyawan PT AKR Land Kawanua Emerald City Manado.
Co-Authors Agung Sukma Adiguna Siddik Darvel Civlie Walone Daysi Fikka Kelejan Deske W. Mandagi dos Santos, Joni Maria Fanny Soewignyo George Morris William Tangka Jeannifer Papilaya Jeiner Maruru Joy Budiman David Sondakh Kainde, Llly Linne Mokalu, Risca Rioline Nikoku Joshua Sepang Paat, Silvia Friska Petir, Abraham Leslie Rantung, Rinny Cherryl Risca Rioline Mokalu Risca Rioline Mokalu Ronny Hansje Walean Saputri Victoria Lolaroh Septiani Septiani Shapely Ambalao Siddik, Agung Sukma Adiguna Silitonga, Argha Orion Wilsen Grivin Mokodaser