Abstract:The rapid development of globalization compels companies to enhance the quality of their products and services to compete in the market. The primary goal of companies is to maximize corporate value, which reflects the well-being…
ll-being of shareholders and attracts investors’ interest. Corporate value is often gauged by the stock price in the capital market, making it crucial for companies to plan sound financial strategies. This research focuses on the banking sector listed on the Indonesia Stock Exchange (IDX) from 2021 to 2023, evaluating the influence of investment policy, dividend policy, and profitability on corporate value. The study employs a descriptive quantitative method using secondary data from the companies’ financial reports. Multiple linear regression analysis is used to assess the relationships between these variables. The results indicate that investment policy and profitability have a positive but not significant effect on corporate value, while dividend policy has a significant positive impact. Corporate value is also affected by stock price fluctuations, which are often inconsistent. These findings affirm that dividend policy is a crucial factor in enhancing corporate value, while investment policy and profitability, although important, do not have a significant impact within the study period. Overall, these independent variables collectively have a significant influence on corporate value in the banking sector on the IDX. This research provides insights for company management in formulating effective strategies to increase corporate value.
Abstract:Livestock agribusiness is an integral part of agricultural development as a subsector that fulfills society's animal protein needs. This research was carried out at the Goatday Farm located in Seyegan District, Sleman Regency…
gency on June 22 - August 20, 2023. This research aims to analyze the upstream-to-downstream agribusiness system of the Goatday farm, analyze the strategies that Goatday has implemented, and analyze the strategies that Goatday can implement in the future. The data sources in this research were obtained from key informants and follow-up informants. The key informant in this research is Mr. Muhammad Farid Akrom the owner of the Goatday farm, while further informants are Mr. Ahmad Fauzi and Mr. Hendri the person in charge of the Goatday farm, and Mr. Hermawan the partner of the Goatday breeder. The analysis used is descriptive analysis, Business Model Canvas (BMC), and SWOT analysis. The result of this research was that Goatday has implemented an agribusiness system on its farms that is integrated. Goatday has also implemented partnerships and has a well-systemized farm. Based on the SWOT analysis, the strategy that Goatday can implement in the future is to create an education-based farm and provide more training to staff and partners regarding efficient maintenance management.
Abstract:This study investigates how audit fees impact audit quality. The purpose of this study is to determine the relationship between the effect of audit fees on audit quality in companies listed on the Indonesia Stock Exchange…
e which are categorized as LQ45. This study was conducted using the verification method. Researchers involved 225 LQ45 companies listed on the Indonesia Stock Exchange from 2016 to 2020. The data used comes from secondary data collected through the documentation method. In analyzing the data, this study uses panel data regression statistical testing with a random effect model. The findings of this study are that audit fees are positive to audit quality based on the calculation of panel data regression analysis conducted through the Eviews 9 program.
Abstract:This research was conducted in the Food and Beverage sector companies listed on the Indonesia Stock Exchange during the period 2017-2021 with the title "Analysis of Activity, Liquidity, and Solvency on Profitability in Food…
ood and Beverage Companies Listed on the Indonesia Stock Exchange (IDX) Period 2017-2021." The data used in this study is quantitative data from secondary sources. The sample was selected using purposive sampling based on specific criteria, with 27 companies selected as samples, making a total of 135 companies studied from the period 2017-2021. The research technique used was multiple linear regression analysis.Partially, the findings of this research state that: 1) Activity has a positive and significant effect on profitability, indicated by a significant value of 0.052 ≤ 0.05 and a t-value of 1.963 > 1.65648. 2) Liquidity has a positive and significant effect on profitability, with a significant value of 0.044 ≤ 0.05 and a t-value of 2.038 > 1.65648. 3) Solvency has a positive and significant effect on profitability, with a significant value of 0.000 ≤ 0.05 and a t-value of 18.944 > 1.65648. 4) Simultaneously, activity, liquidity, and solvency have a positive and significant effect on profitability, as indicated by a significant value of 0.000 < 0.05 and an F-value of 147.949 > 3.07. The determination test shows that 76.7% of the variations in activity, liquidity, and solvency affect profitability, while 23.3% (100% - 76.7%) is influenced by other factors beyond the independent variables studied in food and beverage companies listed on the IDX from 2017 to 2021.
Abstract:Abstract: The development of information and communication technology has increased public demand for digital services, particularly data packages as the primary means of internet access. This high demand requires data package…
ackage retailers to manage inventory optimally to ensure product availability meets customer needs. At CMC Cell, the determination of data package stock is still based on intuition without systematic data analysis, resulting in stock accumulation for certain products and stock shortages for others when demand increases. This study aims to design and implement a web-based Decision Support System (DSS) using the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) method to determine the optimal stock of data packages. The MOORA method is applied to rank data package alternatives based on several criteria, including data package demand, sales history, remaining stock, selling price, and validity period. Sales data are analyzed using the calculation stages of the MOORA method. The results show that the Telkomsel V 3 GB data package achieves the highest preference value of 0.1498 and is therefore recommended as the top-priority data package, with an optimal stock quantity of 200 units. With the implementation of this system, the recommendations for determining data package stock become more measurable, objective, and data-driven.
Keywords: MOORA; PHP; decision support system; optimal stock; stock priority
Abstrak: Perkembangan teknologi informasi dan komunikasi telah meningkatkan kebutuhan masyarakat terhadap layanan digital, khususnya paket data sebagai sarana utama akses internet. Tingginya permintaan tersebut menuntut pelaku usaha penjualan paket data untuk mampu mengelola stok secara optimal agar ketersediaan produk sesuai dengan kebutuhan pelanggan. Pada Toko CMC Cell, penentuan stok paket data masih dilakukan berdasarkan intuisi tanpa analisis data yang sistematis, sehingga sering terjadi penumpukan stok pada beberapa produk dan kekosongan stok pada produk lain saat permintaan meningkat. Penelitian ini bertujuan untuk merancang dan mengimplementasikan Sistem Pendukung Keputusan (SPK) berbasis web menggunakan metode Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) dalam menentukan stok optimal paket data. Metode MOORA digunakan untuk melakukan perangkingan alternatif paket data berdasarkan beberapa kriteria, yaitu permintaan paket data, riwayat penjualan, jumlah stok tersisa, harga jual, dan masa aktif. Data penjualan paket data dianalisis menggunakan tahapan perhitungan metode MOORA. Hasil penelitian menunjukkan bahwa paket data Telkomsel V 3 GB memperoleh nilai preferensi tertinggi sebesar 0,1498 sehingga direkomendasikan sebagai paket data dengan prioritas stok tertinggi, dengan jumlah stok optimal sebanyak 200 pcs. Dengan adanya sistem ini, rekomendasi penentuan stok paket data yang dihasilkan menjadi lebih terukur, objektif, dan berbasis data.
Kata kunci: MOORA; PHP; sistem pendukung keputusan; stok optimal; prioritas stok
Abstract:Abstract: This study is motivated by the underutilization of transaction data at Toko F3I Kisaran in supporting decision-making related to inventory and pricing strategies. Currently, decisions are made conventionally based…
sed on experience, which may lead to overstock or stockout conditions. This research aims to develop a sales prediction model by applying Data Mining techniques using the Multiple Linear Regression method to analyze the influence of stock and price variables on sales. The research methodology includes historical data collection, regression analysis, web-based system design using PHP and MySQL, and system testing through the Black Box method. The results indicate that the developed model is capable of generating measurable and systematic sales estimations based on stock and price variables. The implementation of this system can assist store management in planning inventory levels and pricing strategies more efficiently, thereby improving operational effectiveness and business competitiveness.
Keywords: data mining; multiple linear regression; PHP; sales prediction; web-based system
Abstrak: Penelitian ini dilatarbelakangi oleh belum optimalnya pemanfaatan data transaksi penjualan pada Toko F3I Kisaran dalam mendukung pengambilan keputusan terkait persediaan dan penetapan harga. Selama ini, keputusan masih dilakukan secara konvensional berdasarkan pengalaman, sehingga berpotensi menimbulkan overstock maupun stockout. Penelitian ini bertujuan untuk membangun model prediksi penjualan dengan menerapkan teknik Data Mining menggunakan metode Regresi Linier Berganda guna menganalisis pengaruh variabel stok dan harga terhadap penjualan. Metodologi penelitian meliputi pengumpulan data historis, analisis perhitungan regresi, perancangan sistem berbasis web menggunakan PHP dan MySQL, serta pengujian sistem dengan metode Black Box. Hasil penelitian menunjukkan bahwa model yang dibangun mampu menghasilkan estimasi penjualan berdasarkan variabel stok dan harga secara lebih terukur dan sistematis. Implementasi sistem ini dapat membantu manajemen toko dalam merencanakan jumlah persediaan dan strategi harga secara lebih efisien, sehingga meningkatkan efektivitas pengelolaan bisnis dan daya saing perusahaan.
Kata kunci: data mining; prediksi penjualan; regresi linier berganda; sistem berbasis web; PHP
Abstract:Abstract: Inventory managemet plays a strategic role in supporting the operational sustainability of retail businesses. Errors in determining the quantity of goods procured can lead to inventory buildup or stockouts, which…
ch impacts increased storage costs and reduced customer service levels. Attar Jaya store still uses a manual inventory management system, so the restocking recording and decision-making processes are not yet supported by an integrated and data-driven system. This condition has the potential to cause inefficiency in inventory management. This research aims to apply the concept of Electronic Supply Chain Management (E-SCM) integrated with the Economic Order Quantity (EOQ) method to determine the optimal order quantity of goods. The EOQ method is used to calculate the most economical order quantity by considering ordering and storage costs, while E-SCM plays a role in integrating inventory management processes digitally. The research methods include observation, interviews, and literature studies, with system design using the Unified Modelign Language (UML). The system was developed using the PHP programming language and the MwSQL database. The research result are expected to help Toko Attar Jaya improve the accuracy of resctocking decision-making, minimize the risk of overstocking and understocking, and increase the efficiency of inventory mangement.
Keywords: MySQL; PHP; e-supply chain management; economic order quantity; restock items
Abstrak: Manajemen persediaan memiliki peran strategis dalam mendukung keberlangsungan operasional usaha ritel. Kesalahan dalam menentukan jumah pengadaan barang dapat menyebabkan terjadinya penumpukan persediaan maupun kekurangan stok yang berdampak pada meningkatnya biaya penyimpanan seerta menurunnya tingkat pelayanan kepada pelanggan. Toko Attar Jaya masih menerapkan sistem pengelolaan persediaan secara manual, sehingga proses pencatatan dan pengambilan keputusan restok belum didukung oleh sistem yang terintegrasi dan berbasis data. Kondisi tersebut berpotensi menimbulkan ketidakefisienan dalam pengelolaan stok barang. Penelitian ini bertujuan untuk menerapkan konsep Electronic Supply Chain Management (E-SCM) yang terintegrasi dengan metode Economic Order Quantity (EOQ) dalam menentukan jumlah pemesanan barang yang optimal. Metode EOQ digunakan untuk menghitung jumlah pemesanan yang paling ekonomis dengan mempertimbangkan biaya pemesanan dan biaya penyimpanan, sedangkan E-SCM berperan dalam mengintegrasikan proses pengelolaan persediaan secara digital. Metode penelitian meliputi observasi, wawancara, dan studi literatur, dengan perancangan sistem menggunakan Unified Modeling Languge (UML). Sistem dikembangkan mengguanakan bahasa pemrograman PHP dan basis data MySQL. Hasil penelitian diharapkan mampu membantu pihak Toko Attar Jaya dalam meningkatkan akurasi pengambilan keputusan restok, meminimalkan risiko kelebihan dan kekurangan persediaan, serta meningkatkan efisiensi pengelolaan persediaan.
Kata kunci: MySQL; PHP; e-supply chain management; economic order quantity; restok barang
Abstract:Abstract: In a competitive digital era, business owners such as Alya Collection face challenges in determining the right fashion products to offer to consumers. Relying on intuition without data support often results in…
inaccurate and potentially detrimental decisions. This study aims to assist the sales decision-making process by applying a data mining method using the K-Means Clustering algorithm. This method was used to group sales data from February 2024 to January 2025 into three categories: best-selling, least-selling, and non-selling products. The study was conducted using a quantitative approach, through sales data collection and direct interviews with store owners. The system was built using the PHP programming language and MySQL database, and designed with tools such as UML, DFD, and ERD. The results of this clustering system are expected to provide strategic information useful for Alya Collection in planning stock, promotions, and product development, thereby increasing sales effectively and efficiently.
Keywords: data mining; k-means; sales; alya collection; information system
Abstrak: Dalam era digital yang kompetitif, pemilik usaha seperti Alya Collection menghadapi tantangan dalam menentukan produk fashion yang tepat untuk ditawarkan kepada konsumen. Ketergantungan pada intuisi tanpa dukungan data seringkali mengakibatkan keputusan yang kurang akurat dan berisiko merugikan. Penelitian ini bertujuan untuk membantu proses pengambilan keputusan penjualan dengan menerapkan metode data mining menggunakan algoritma K-Means Clustering. Metode ini digunakan untuk mengelompokkan data penjualan dari Februari 2024 hingga Januari 2025 ke dalam tiga kategori: produk terlaris, kurang laris, dan tidak laris. Penelitian dilakukan dengan pendekatan kuantitatif, melalui pengumpulan data penjualan serta wawancara langsung dengan pemilik toko. Sistem yang dibangun menggunakan bahasa pemrograman PHP dan database MySQL, serta dirancang dengan alat bantu seperti UML, DFD, dan ERD. Hasil dari sistem klasterisasi ini diharapkan dapat memberikan informasi strategis yang berguna bagi Alya Collection dalam merencanakan stok, promosi, serta pengembangan produk, sehingga mampu meningkatkan penjualan secara efektif dan efisien.
Kata kunci: data mining; k-means clustering; penjualan; alya collection; sistem informasi
Abstract:Abstract: Motorcycle sales are one of the key indicators of growth in Indonesia’s automotive industry. CV. Honda Karya Utama, as an authorized Honda motorcycle dealer, faces challenges due to unstable monthly sales fluctuations.…
ctuations. This uncertainty complicates stock planning, marketing strategy formulation, and may lead to potential losses caused by overstocking or understocking. To address these issues, this study aims to analyze the relationship between time and sales volume and to develop a predictive model that can assist management in making more effective business decisions.
The research was conducted using a quantitative method and a machine learning approach by applying a linear regression algorithm, implemented through the Python programming language and a MySQL database. The dataset used consists of monthly sales data over one year, analyzed to predict future sales trends. The results show that the linear regression algorithm can predict sales trends with a good level of accuracy, achieving evaluation values of MAPE 1.72%, MSE 1.76%, and RMSE 0.57. The developed model assists management in formulating marketing strategies, optimizing inventory planning, and minimizing financial risks. Therefore, linear regression can serve as an effective analytical tool to support strategic business decision-making at CV. Honda Karya Utama.
Keywords: motorcycle sales; linear regression; prediction; sales analysis
Abstrak: Penjualan sepeda motor merupakan salah satu indikator penting dalam pertumbuhan industri otomotif di Indonesia. CV. Honda Karya Utama sebagai dealer resmi sepeda motor Honda menghadapi tantangan berupa fluktuasi penjualan yang tidak stabil setiap bulannya. Ketidakpastian ini menyebabkan kesulitan dalam perencanaan stok, penentuan strategi pemasaran, serta berpotensi menimbulkan kerugian akibat kelebihan atau kekurangan persediaan. Untuk mengatasi permasalahan tersebut, penelitian ini bertujuan untuk menganalisis hubungan antara waktu dan jumlah penjualan serta membangun model prediksi yang dapat membantu manajemen dalam pengambilan keputusan bisnis yang lebih efektif. Penelitian dilakukan dengan metode kuantitatif dan pendekatan machine learning menggunakan algoritma regresi linier, dengan implementasi berbasis bahasa pemrograman Python dan basis data MySQL. Data yang digunakan berupa data penjualan bulanan selama satu tahun, yang kemudian dianalisis untuk memprediksi tren penjualan pada periode berikutnya. Hasil penelitian menunjukkan bahwa regresi linier mampu memprediksi tren penjualan dengan tingkat akurasi yang baik, dengan nilai evaluasi MAPE sebesar 1,72%, MSE 1,76%, dan RMSE 0,57. Model ini membantu manajemen dalam menyusun strategi pemasaran, mengoptimalkan perencanaan stok, serta meminimalkan risiko kerugian. Dengan demikian, regresi linier dapat menjadi alat bantu yang efektif dalam mendukung keputusan bisnis di CV. Honda Karya Utama.
Kata kunci: penjualan sepeda motor; regresi linier; prediksi; analisis penjualan
Abstract:Abstract: The rapid advancement of information technology requires companies to enhance efficiency in supply chain management. RO Aquatub, a business engaged in manufacturing bathtubs, often faces issues such as delays in…
n raw material procurement, manual stock recording, and the absence of an integrated system with suppliers. These problems impact the overall production process efficiency. This study aims to develop a web-based Supply Chain Management (SCM) system to optimize the raw material inventory management at RO Aquatub. The system development follows the waterfall model, consisting of requirement analysis, system design, implementation, and testing phases. The system is designed to serve three main entities: admin, supplier, and manager, with key features including stock management, material purchase requests, live chat, and transaction reports. The results of system testing using the black box method indicate that all features function as intended. The system improves stock management efficiency, speeds up communication with suppliers, and supports decision-making by providing accurate and real-time data. With this system, RO Aquatub can manage its production operations more effectively and more controlled manner.
Keywords: Supply Chain Management; Raw Material Inventory; Information System, RO Aquatub; Web-Based System
Abstrak: Perkembangan teknologi informasi yang pesat menuntut perusahaan untuk meningkatkan efisiensi dalam pengelolaan rantai pasok. RO Aquatub merupakan usaha yang bergerak di bidang pembuatan bathub, namun dalam praktiknya sering mengalami kendala seperti keterlambatan pengadaan bahan baku, pencatatan stok yang masih manual, serta tidak adanya sistem terintegrasi dengan supplier. Permasalahan tersebut berdampak pada kurang optimalnya proses produksi. Penelitian ini bertujuan untuk mengembangkan sistem manajemen rantai pasok (Supply Chain Management) berbasis web guna mengoptimalkan pengelolaan persediaan bahan baku pada RO Aquatub. Metode pengembangan sistem menggunakan pendekatan waterfall, dengan tahapan analisis kebutuhan, perancangan, implementasi, dan pengujian sistem. Sistem dirancang untuk memfasilitasi tiga entitas utama yaitu admin, supplier, dan pimpinan, dengan fitur utama seperti manajemen stok, pengajuan pembelian bahan, live chat, serta laporan transaksi. Hasil pengujian menggunakan metode black box menunjukkan bahwa seluruh fitur sistem berjalan sesuai fungsinya. Sistem ini mampu meningkatkan efisiensi pengelolaan stok, mempercepat proses komunikasi dengan supplier, serta membantu pimpinan dalam pengambilan keputusan berbasis data yang akurat dan real-time. Dengan adanya sistem ini, pihak RO Aquatub dapat menjalankan operasional produksi secara lebih efektif dan terkontrol.
Kata kunci: Supply Chain Management; Persediaan Bahan Baku; Sistem Informasi; RO Aquatub; Web