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Pengaruh Budaya Organisasi, Gaya Kepemimpinan, dan Pelatihan Terhadap Kinerja Karyawan Dengan Kepuasan Kerja Sebagai Pemoderasi
Full text linkThis study investigates the impact of organizational culture, leadership style, and training on employee performance, with job satisfaction acting as a moderating variable. Utilizing the Structural Equation Modeling (SEM) approach and Smart PLS software, the study analyzes the relationships between variables. A saturated sampling method was employed, involving all 157 employees of Buddhi College School as respondents. The findings confirm the proposed hypothesis, indicating that organizational culture, leadership style, training, and job satisfaction positively and significantly influence employee performance. However, job satisfaction moderates the relationship between organizational culture and employee performance negatively and significantly. Conversely, job satisfaction positively and significantly moderates the effects of leadership style and training on employee performance. These findings suggest that organizations aiming to enhance employee performance should focus on strengthening organizational culture, leadership effectiveness, training programs, and job satisfaction
Pengaruh Customer Online Reviews, Flash Sale dan Tagline Gratis Ongkir terhadap Pembelian Impulsif pada Aplikasi Tik Tok
Full text linkImpulsive buying is an act of purchasing done suddenly without any consideration, which can lead to regret. The aim of this study is to demonstrate how flash deals, customer online reviews, and the phrase "free shipping" affect impulsive purchases made by Rembang Regency TikTok users. Customers in Rembang Regency who are between the ages of 18 and 40 who have used the Tik Tok app to make purchases online make up the research population. Purposive sampling was the method of sampling that was employed. Using SPSS 24, the data analysis method included multiple linear regression analysis. The study's findings demonstrate that while flash sales have a significant positive impact on impulsive purchasing, customer online reviews and the tagline "free shipping" have a positive but negligible effect. Only 57.5% of impulsive purchases can be explained by the three independent factors in this study, according to the determination test results; the remaining 42.5% can be explained by variables not included in this study
Pengaruh Kinerja Keuangan Terhadap Nilai Perusahaan Dengan Corporate Social Responsibility (CSR) Sebagai Variabel Moderasi
Full text linkThis study aims to examine the effect of financial performance on company value with Corporate Social Responsibility as a moderating variable in banking sector companies listed on the Indonesia Stock Exchange in 2021-2023. The research method used is quantitative with an associative approach, the population in this study was 47 banking companies listed on the Indonesia Stock Exchange in 2021-2023, the sample collection technique used purposive sampling with the results of 29 companies. The data source used is secondary data in the form of annual financial reports of banking companies in 2021-2023. Data collection uses documentation techniques. The data analysis technique uses descriptive analysis techniques using the Smart PLS.4 application. The results of the study show that there is an influence between ROI on PBV, while LDR and DER have no effect on PBV. This is also the same as the results that CSR cannot moderate the relationship between financial performance proxied by ROI and LDR except for DER on company value proxied by PBV in banking companies listed on the IDX in 2021-2023
Analisis Prediksi Harga Saham PT. BCA Dengan Menggunakan Metode ARIMA
Full text linkPenelitian ini bertujuan untuk memprediksi harga saham PT. BCA yang mengalami fluktuasi dalam beberapa tahun terakhir. Metode yang digunakan adalah Autoregressive Integrated Moving Average (ARIMA), dengan data sekunder berupa data time series harian penutupan dari tanggal 12 April 2021 hingga 11 April 2025 yang berjumlah 964 data time series. Data tersebut diperoleh melalui pencarian histori harga saham PT. BCA yang tersedia di situs resmi www.investing.com. Pengolahan data dilakukan menggunakan software ekonometrika, yaitu E-views 12. Hasil analisis menunjukkan bahwa model terbaik untuk peramalan adalah ARIMA (1,1,1), dengan nilai MAPE <10%, yang menunjukkan tingkat akurasi yang tinggi. Berdasarkan model tersebut, prediksi harga saham BCA pada tahun 2026 diproyeksikan mengalami tren kenaikan hingga akhir tahun. Penelitian ini memberikan kontribusi dalam mendukung pengambilan keputusan investasi dengan pendekatan peramalan teknikal berbasis data historis. Hasil ini juga memperkuat keandalan model ARIMA dalam konteks peramalan harga saham harian jangka menengah, khususnya bagi saham-saham dengan pola pergerakan harga yang relatif stabil seperti BCA
Pengaruh Struktur Aset, Sales Growth, dan Ukuran Perusahaan Terhadap Kebijakan Hutang
Full text linkPentingnya memahami faktor-faktor penentu kebijakan hutang dalam konteks sektor manufaktur di negara berkembang. Kehadiran dana yang cukup untuk mendukung operasinal bisnis suatu organisasi merupakan salah satu komponen kuncinya. Oleh karena itu, kebijakan hutang dapat menjadi sumber modal yang tepat untuk memperkuat keuangan suatu bisnis, sehingga tujuan dari riset ini yaitu menganalisis secara empiris terkait kebijakan utangnya terhadap struktur aktiva, pertumbuhan penjualan, kemudian skala perusahaan di perusahaan manufaktur yang tercatat di BEI periode 2021–2023. Riset ini menerapkan regresi linier berganda dengan teknik purposive sampling pada 276 data dari 92 entitas. Hasil uji t menunjukkan struktur aktiva tidak berpengaruh signifikan (t = 1,667; p = 0,95), begitu pula pertumbuhan penjualan (t = 0,668; p = 0,504). Sebaliknya, ukuran perusahaan berkorelasi positif terhadap kebijakan utang (t = 4,536; p = 0,000). Uji F mengindikasikan ketiga variabel independen secara simultan memengaruhi kebijakan utang (p = 0,000 < 0,05). Implikasi riset ini, aset tetap sebaiknya tidak dijadikan agunan bila dana internal mencukupi, kemudian fluktuasi penjualan tahunan turut memengaruhi kemampuan pelunasan utang. Analisis mengungkapkan bahwa kebijakan hutang hanya dipengaruhi oleh ukuran perusahaan (p = 0,000) dengan R2 = 6,8%. Temuan ini dapat membantu manajer keuangan mempertimbangkan ukuran perusahaan dalam merancang struktur pembiayaan
Demand Prediction and Apparel Production Management Using AI-Based Decision Tree
Full text linkThe apparel industry faces significant challenges in demand forecasting due to market volatility, rapid changes in fashion trends, and diverse consumer behavior, especially within e-commerce environments. Traditional forecasting methods such as linear regression and time series models often fall short in addressing the complex dynamics of the modern fashion market. This study presents a novel integration of demand forecasting and size recommendation into a unified AI-based system utilizing the Decision Tree algorithm. The system is designed to predict product demand while also providing personalized clothing size recommendations based on user attributes such as body measurements, style preferences, and seasonal trends. The system was developed using a structured data processing and predictive modeling approach, incorporating user profiles and trend sentiment derived from social media. The evaluation results show that the system achieved an accuracy rate of 87.5% in demand forecasting and 84% user satisfaction for size recommendations. It demonstrated better adaptability and performance compared to traditional methods such as ARIMA. A functional prototype was implemented, allowing users to interactively input data and receive real-time predictions. This study confirms the potential of Decision Tree-based AI models to enhance the shopping experience, reduce product return rates, and optimize inventory management. Future improvements may involve integrating real-time data and advanced technologies such as 3D body scanning to further increase prediction accuracy and personalization in digital fashion retail.The apparel industry faces significant challenges in demand forecasting due to market volatility, rapid changes in fashion trends, and diverse consumer behavior, especially within e-commerce environments. Traditional forecasting methods such as linear regression and time series models often fall short in addressing the complex dynamics of the modern fashion market. This study presents a novel integration of demand forecasting and size recommendation into a unified AI-based system utilizing the Decision Tree algorithm. The system is designed to predict product demand while also providing personalized clothing size recommendations based on user attributes such as body measurements, style preferences, and seasonal trends. The system was developed using a structured data processing and predictive modeling approach, incorporating user profiles and trend sentiment derived from social media. The evaluation results show that the system achieved an accuracy rate of 87.5% in demand forecasting and 84% user satisfaction for size recommendations. It demonstrated better adaptability and performance compared to traditional methods such as ARIMA. A functional prototype was implemented, allowing users to interactively input data and receive real-time predictions. This study confirms the potential of Decision Tree-based AI models to enhance the shopping experience, reduce product return rates, and optimize inventory management. Future improvements may involve integrating real-time data and advanced technologies such as 3D body scanning to further increase prediction accuracy and personalization in digital fashion retail
Optimasi Ongkir dan Rute Pengiriman Menggunakan Haversine Formula dan Algoritma Kruskal
Full text linkOptimasi ongkos kirim (ongkir) dan rute pengiriman menjadi tantangan utama bagi usaha mikro, kecil, dan menengah (UMKM), terutama dalam meningkatkan efisiensi logistik. Toko Keripik Aldafa menghadapi permasalahan dalam menentukan ongkir secara akurat serta memilih rute pengiriman yang optimal karena masih menggunakan metode manual. Ketidakakuratan dalam estimasi biaya dan rute yang kurang efisien menyebabkan peningkatan waktu tempuh serta tingginya biaya operasional. Oleh karena itu, penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem berbasis web yang dapat membantu mengoptimalkan ongkir dan rute pengiriman dengan memanfaatkan Haversine Formula untuk perhitungan jarak geografis serta Algoritma Kruskal untuk menentukan jalur pengiriman terpendek. Metode yang digunakan dalam penelitian ini meliputi penerapan Haversine Formula untuk menghitung jarak berdasarkan koordinat lintang dan bujur, serta Algoritma Kruskal dalam membangun Minimum Spanning Tree (MST) guna menemukan jalur distribusi yang paling optimal. Pengujian dilakukan dengan membandingkan hasil perhitungan manual dan sistem berbasis web. Hasil penelitian menunjukkan bahwa sistem yang dikembangkan mampu meningkatkan akurasi estimasi ongkir dan mengoptimalkan rute pengiriman. Dibandingkan dengan metode manual, sistem ini berhasil mengurangi biaya logistik rata-rata sebesar 18,5% serta menghemat waktu tempuh hingga 22,3%. Selain itu, perbedaan hasil perhitungan manual (8.15 km) dan sistem (8.12 km) menunjukkan tingkat akurasi yang tinggi dengan selisih yang kecil. Dengan implementasi sistem ini, UMKM seperti Toko Keripik Aldafa dapat mengurangi ketidakefisienan dalam proses logistik dan meningkatkan daya saing di era digital. Penelitian ini juga membuka peluang pengembangan lebih lanjut, seperti penggunaan data real-time dan integrasi dengan sistem pemetaan lainnya untuk meningkatkan akurasi dan efisiensi distribusi barang.Optimasi ongkos kirim (ongkir) dan rute pengiriman menjadi tantangan utama bagi usaha mikro, kecil, dan menengah (UMKM), terutama dalam meningkatkan efisiensi logistik. Toko Keripik Aldafa menghadapi permasalahan dalam menentukan ongkir secara akurat serta memilih rute pengiriman yang optimal karena masih menggunakan metode manual. Ketidakakuratan dalam estimasi biaya dan rute yang kurang efisien menyebabkan peningkatan waktu tempuh serta tingginya biaya operasional. Oleh karena itu, penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem berbasis web yang dapat membantu mengoptimalkan ongkir dan rute pengiriman dengan memanfaatkan Haversine Formula untuk perhitungan jarak geografis serta Algoritma Kruskal untuk menentukan jalur pengiriman terpendek. Metode yang digunakan dalam penelitian ini meliputi penerapan Haversine Formula untuk menghitung jarak berdasarkan koordinat lintang dan bujur, serta Algoritma Kruskal dalam membangun Minimum Spanning Tree (MST) guna menemukan jalur distribusi yang paling optimal. Pengujian dilakukan dengan membandingkan hasil perhitungan manual dan sistem berbasis web. Hasil penelitian menunjukkan bahwa sistem yang dikembangkan mampu meningkatkan akurasi estimasi ongkir dan mengoptimalkan rute pengiriman. Dibandingkan dengan metode manual, sistem ini berhasil mengurangi biaya logistik rata-rata sebesar 18,5% serta menghemat waktu tempuh hingga 22,3%. Selain itu, perbedaan hasil perhitungan manual (8.15 km) dan sistem (8.12 km) menunjukkan tingkat akurasi yang tinggi dengan selisih yang kecil. Dengan implementasi sistem ini, UMKM seperti Toko Keripik Aldafa dapat mengurangi ketidakefisienan dalam proses logistik dan meningkatkan daya saing di era digital. Penelitian ini juga membuka peluang pengembangan lebih lanjut, seperti penggunaan data real-time dan integrasi dengan sistem pemetaan lainnya untuk meningkatkan akurasi dan efisiensi distribusi barang
Development of The Software as Services (SaaS) Business Model in The Satusehat Integrated Electronic Medical Record System
Full text linkDigital transformation in the healthcare sector represents a key strategy to enhance operational efficiency and improve the quality of medical services. This study presents the development of a Software as a Service (SaaS)-based Electronic Medical Record (EMR) information system, integrated with SatuSehat, a national health data platform managed by the Ministry of Health of the Republic of Indonesia. The system is designed to improve the accuracy of clinical data recording and expedite access to patient information for healthcare professionals. The development process adopted the Agile methodology, characterized by iterative and incremental stages including requirements analysis, system design, implementation, testing, and evaluation. Agile was selected for its ability to accommodate dynamic user needs and regulatory requirements through continuous feedback loops and adaptive planning. Compliance with national health regulations and data security standards, including Minister of Health Regulation No. 24 of 2022 concerning EMR implementation, guided the entire process. Evaluation of the system demonstrates enhanced efficiency in medical administrative workflows, improved accuracy of patient records, and accelerated clinical decision-making processes. The integration with SatuSehat enables interoperability at a national level, thereby supporting real-time health data exchange and long-term health monitoring systems. From a societal standpoint, the system improves data accessibility for healthcare personnel and elevates the overall quality of care delivered to patients. Economically, the SaaS-based approach reduces operational costs, promotes efficient budgeting, and contributes to the broader digital transformation of healthcare services, particularly in strengthening primary care infrastructure
Simple Additive Weighting Method for Internet Service Provider Vendor Selection Decision Support System
Full text linkThe increasing demand for high-speed, stable, and reliable internet services at IKPIA Perbanas—driven by educational, research, and administrative needs—has posed challenges in selecting the most suitable Internet Service Provider (ISP). With numerous vendors offering diverse bandwidth packages and pricing, a structured and objective decision-making method is essential. This study proposes the development of a web-based Decision Support System (DSS) using the Simple Additive Weighting (SAW) method to assist in the selection of the most appropriate ISP. The research adopts a quantitative approach, utilizing both primary and secondary data. Primary data were collected through a questionnaire distributed via Google Forms to five experts comprising the tender selection team. Secondary data were obtained through observation and interviews. Seven key criteria were identified: bandwidth, benefit, experience, service level agreement (SLA), support, hardware, and security. Each criterion was weighted and evaluated using the SAW method. The resulting system calculated normalized performance ratings and preference values for each vendor. The analysis showed that PT. B achieved the highest preference value (0.97), followed by PT. E (0.93), indicating PT. B as the most suitable vendor. The developed system successfully supports transparent, criteria-based ISP selection, enhancing the efficiency and objectivity of the procurement process at IKPIA Perbanas
Measuring User Satisfaction of iPusnas Through the End-User Computing Satisfaction Model
Full text linkiPusnas serves as Indonesia’s national digital library platform, offering free access to electronic books for the general public. This research aims to evaluate user satisfaction with the iPusnas application by employing the End-User Computing Satifactions (EUCS) model, which comprises five main constructs: content, acuracy, format, ease of use, and timelines, along with two additional dimensions—system speed and system reliability. The study involved 450 participants selected through purposive sampling. Data analysis was conducted using the Partial Least Squares Structural Equations Modeling (PLS-SEM) technique with the assistance of SmartPLS 4 software. The findings indicate that six variables—content, ease of use, format, accuracy, system speed, and system reliability—have a statistically significant and positive impact on user satisfaction. This suggests that a higher level of perceived quality in these six areas corresponds to greater satisfaction among users. On the other hand, timeliness was found to have a significant yet negative influence. These results suggest that delays in delivering content or in system responsiveness remain key issues that negatively affect user experience. Accordingly, this study recommends enhancing system performance, particularly in terms of timeliness to improve user satisfaction and the overall experience. Strengthening these areas is also anticipated to contribute to increased user engagement and further the national objective of expanding digital literacy and equitable knowledge access across the country