Abstract:This study explores how incorporating artificial intelligence improves institutional resilience and overcomes the rigidity of conventional, data-based methods to alter financial risk management. To find patterns in AI applications,…
applications, resilience theory, and integration pathways, a qualitative systematic literature review was carried out utilizing theme synthesis in accordance with PRISMA peer-reviewed protocols. Findings show that AI techniques, machine learning for tail-risk detection, deep learning for high-frequency forecasting, and explainable AI for transparent decisions, yield up to 28% reductions in forecasting errors and halve recovery times during crises. The hybrid CNN Transformer architectures and transformer-based NLP models significantly enhance predictive accuracy and forward-looking insights. The study suggests financial institutions adopt integrated AI frameworks, invest in data quality and human–AI collaboration, and implement principle-based governance to balance innovation with fairness and stability. Limitations include reliance on published literature and limited representation of emerging AI models, warranting future longitudinal and context-specific empirical research.
Abstract:The rapid growth of the hotel industry requires hotels to improve operational planning, one of which is by forecasting room reservations. Inaccurate forecasting may cause an imbalance between room availability and customer…
er demand. This study aims to compare the Weighted Moving Average and Single Exponential Smoothing algorithms in forecasting room reservations at Raz Hotel and Convention Medan using historical data from January 2025 to May 2026. The research method consisted of data collection, forecasting using both algorithms, and accuracy evaluation through Mean Absolute Deviation, Mean Squared Error, and Mean Absolute Percentage Error. The results indicate that the Single Exponential Smoothing algorithm achieved a Mean Absolute Percentage Error of 15.24%, which is lower than the 15.63% obtained by the Weighted Moving Average algorithm. Furthermore, the Single Exponential Smoothing algorithm predicted 835.90 room reservations for June 2026. Therefore, it can be concluded that the Single Exponential Smoothing algorithm provides better forecasting accuracy and is more suitable for predicting room reservations at Raz Hotel and Convention Medan.
Abstract:Sales forecasting is a crucial component of operational strategy and inventory management in the culinary industry, particularly for businesses dealing with raw materials that have short shelf lives. The Sate Padang Hapis…
s business faces the challenge of unpredictable monthly fluctuations in consumer demand, which often lead to supply imbalances, overproduction, or lost profit opportunities due to stockouts. This study aims to implement and analyze the accuracy of the Single Moving Average (SMA) quantitative forecasting method in predicting Sate Padang Hapis sales volumes for June 2026. Model performance was evaluated by assessing mathematical accuracy across two time-interval variations: 3-month and 5-month moving averages. Projection error rates were rigorously measured using Mean Absolute Deviation (MAD), Mean Squared Error (MSE), and Mean Absolute Percentage Error (MAPE) parameters. The analysis reveals that the Single Moving Average model with a 5-month interval yields projections closest to actual data, achieving the lowest error rates (MAD: 28.00; MSE: 1,304.00; MAPE: 2.28%). Implementing this forecasting model provides management with an objective basis for decision-making, enabling the effective and efficient optimization of raw material logistics and supply management.
Abstract:Improper rice stock management in wholesale businesses can lead to shortages or overstock that negatively impact operational efficiency. This study aims to forecast rice stock needs at Warung Grosir Giran using the Weighted…
ted Moving Average method with a weighting of 1:2:3, based on historical data from January 2025 to June 2026. A quantitative approach with time series forecasting technique was applied. Accuracy was evaluated using Mean Absolute Deviation, Mean Squared Error, and Mean Absolute Percentage Error. The results show that the forecasted rice stock requirement for July 2026 is 1,456.67 kg. The accuracy evaluation yielded a Mean Absolute Deviation of 78.22, Mean Squared Error of 9,288.15, and Mean Absolute Percentage Error of 5.71%, which is classified as highly accurate. In conclusion, the Weighted Moving Average method is suitable as a decision-support tool for rice stock management at Warung Grosir Giran.
Abstract:Angga Colection adalah sebuah usaha yang bergerak di bidang penjualan fashion, terletak di Jalan Besar Sei Silau Timur, Kabupaten Asahan. Produk fashion yang ditawarkan meliputi baju, celana, tas, sepatu, aksesoris, dan…
gamis. Namun, saat ini Angga Colection menghadapi kesulitan dalam memprediksi permintaan produk fashion karena masih mengandalkan perkiraan dari bagian penjualan. Untuk mengatasi masalah ini, penelitian ini bertujuan untuk menerapkan metode single moving average pada sistem peramalan penjualan produk fashion di Angga Colection. Metode ini melibatkan pengambilan sekelompok nilai pengamatan, mencari nilai rata-rata, dan menggunakan hasilnya sebagai ramalan untuk periode yang akan datang. Penelitian ini menggunakan metode penelitian kuantitatif dan hasilnya menunjukkan bahwa menerapkan metode single moving average pada sistem peramalan penjualan produk fashion di Angga Colection dapat memudahkan proses peramalan dan meningkatkan akurasi prediksi. Dengan demikian, Angga Colection dapat membuat keputusan yang lebih tepat dan efektif dalam menghadapi permintaan produk fashion.
Abstract:Abstract: Palm oil is a key commodity that requires accurate production planning to support budget and operational efficiency. PT Buana Sawit Indah, a company managing palm oil plantations, faces challenges in forecasting…
g future production, necessitating a computerized forecasting system. This study aims to develop a forecasting system using the Single Exponential Smoothing (SES) and Single Moving Average (SMA) methods to predict palm oil production. The results indicate that both methods are effective; however, SMA with a Moving Average (MA) of 5 provides the best forecasting results, with a MAD of 165,941.64, an MSE of 65,823,372,491.27, and an MAPE of 15.66%, categorized as "good" forecasting. Meanwhile, the SES method with α = 0.9 yields the lowest error compared to other alpha values, with a MAD of 154,586.25, an MSE of 33,192,818,696.83, and an MAPE of 16.91%, also classified as "good" forecasting. Based on these findings, the SMA method with MA 5 is recommended as it produces lower forecasting errors than the SES method. Therefore, this forecasting system can assist the company in planning palm oil production more accurately and efficiently, supporting better decision-making in the future.
Keywords: palm oil; forecasting; production; single exponential smoothing; single moving average
Abstrak: Kelapa sawit merupakan komoditas utama yang memerlukan perencanaan produksi yang akurat untuk mendukung efisiensi anggaran dan operasional. PT Buana Sawit Indah, salah satu perusahaan yang mengelola perkebunan kelapa sawit, sedang menghadapi kesulitan dalam memperkirakan hasil produksi di masa mendatang, sehingga diperlukan sistem peramalan berbasis komputer. Penelitian ini bertujuan mengembangkan sistem peramalan menggunakan metode Single Exponential Smoothing (SES) dan Single Moving Average (SMA) untuk memprediksi produksi kelapa sawit. Hasil penelitian menunjukkan bahwa kedua metode cukup efektif, namun SMA dengan Moving Average (MA) 5 memberikan hasil peramalan terbaik dengan nilai MAD sebesar 165.941,64, MSE sebesar 65.823.372.491,27, dan MAPE sebesar 15,66%, yang dikategorikan sebagai peramalan “bagus.†Sementara itu, metode SES dengan α = 0,9 menunjukkan nilai kesalahan lebih rendah dibanding nilai alpha lain, dengan MAD sebesar 154.586,25, MSE sebesar 33.192.818.696,83, dan MAPE sebesar 16,91%, yang juga termasuk kategori peramalan “bagus.†Berdasarkan hasil tersebut, metode SMA dengan MA 5 lebih direkomendasikan karena menghasilkan tingkat kesalahan yang lebih rendah dibandingkan metode SES. Dengan demikian, sistem peramalan ini dapat membantu perusahaan dalam merencanakan produksi kelapa sawit secara lebih akurat dan efisien untuk mendukung pengambilan keputusan yang lebih baik di masa mendatang.
Kata kunci: kelapa sawit; peramalan; produksi; single exponential smoothing; single moving average
Abstract:Abstract: Roemah Donat Lezat carries out many sales transactions every day because the prices are affordable and the flavors and toppings are increasingly varied, this affects the supply of raw materials at Roemah Donat…
Lezat In managing raw material inventory, you must ensure sufficient inventory for sales, minimizing the time and costs required. So far, the owner of Roemah Donat Lezat does not have a method for anticipating how much supply of basic ingredients there is and only predicts without clear and precise calculations, therefore, sometimes Roemah Donat Lezat takes too little stock even though customer needs at the time the trend is increasing, causing no fulfilling customer requests and sometimes taking too much stock even though customer demand is decreasing resulting in losses, therefore Roemah Donat Lezat always finds it difficult and confused to estimate stock supplies for the following month To overcome the problems above, the author provides a solution using method comparison forecasting calculations, because it can provide a deeper and more detailed understanding of the advantages, weaknesses and relative performance of the two methods used to achieve a goal or solve a problem The method used is Single Exponential Smoothing, which is forecasting used for the short term or usually only for the next month Single Moving Average is a technique for calculating the average of a number from the latest actual values, updated as new values available for use in forecasting in subsequent periods.
Keywords: single exponential smoothing-single moving average; forecasting; roemah donat lezat; raw materials; inventory
Abstrak: Roemah Donat Lezat setiap harinya banyak melakukan transaksi penjualan karena harga terjangkau dan semakin bervariasi rasa dan topping, hal ini mempengaruhi persediaan bahan baku jika ada di Roemah Donat Lezat Dalam pengelolaan persediaan bahan baku harus memastikan persediaan jika cukup dalam penjualan, meminimalkan waktu dan biaya jika dibutuhkan.Selama ini pemilik Roemah Donat Lezat tidak memiliki metode dalam mengantisipasi seberapa banyak persediaan bahan-bahan pokok dan hanya memprediksi tanpa adanya perhitungan jika jelas dan tepat maka dari itu, terkadang Roemah Donat Lezat terlalu sedikit mengambil stok padahal kebutuhan pelanggan waktu trend itu sedang meningkat menyebabkan tidak terpenuhinya permintaan pelanggan dan kadang-kadang juga cenderung mengambil terlalu banyak stok meskipun permintaan Pelanggan sedang mengalami penurunan sehingga mengalami kerugian, Sehingga Roemah Donat Lezat selalu menghadapi kesulitan dan kebingungan dalam memperkirakan persediaan stok di bulan berikutnya. Solusi dari permasalahan tersebut yaitu dengan memanfaatkan perhitungan peramalan komparasi metode, kita dapat memperoleh pemahaman yang lebih mendalam dan rinci mengenai kelebihan, kekurangan, serta kinerja relatif dari dua metode yang digunakan untuk mencapai suatu tujuan atau menyelesaikan masalah. Metode yang dibandingkan adalah Single Exponential Smoothing dan Single Moving Average.
Kata kunci: single exponential smoothing-single moving average; peramalan; roemah donat lezat; bahan baku; persediaan
Abstract:Abstract: Bismillah Ponsel in Kisaran Kota faces challenges in managing internet voucher stock due to inefficient manual recording and limited active period. To overcome this problem, the application of the Single Moving…
Average (SMA) forecasting method is proposed to predict stock needs based on historical data. Thus, business owners can manage stock more optimally, avoid shortages or excess inventory, and improve business efficiency and finances. The results of the application of the SMA method show the prediction of voucher stock needs for April and May with fairly good Mean Absolute Percentage Error (MAPE) accuracy. For IM3 vouchers, the stock predictions for each month are 244 and 244.5 (MAPE 8.21%). Axis vouchers as many as 798 (MAPE 5.02%), XL as many as 713 and 724.5 (MAPE 5.02%), Telkomsel as many as 942 and 951 (MAPE 3.23%), Tri as many as 490 and 491 (MAPE 7.94%), and Smartfren as many as 656 and 664 (MAPE 5.38%). With quite high accuracy, the SMA method has proven to be able to predict sales quickly and accurately, help provide stock according to needs, and increase the operational efficiency of Bismillah Ponsel.
Keywords: inventory; management; sales; forecasting; single moving average (SMA).
Abstrak: Bismillah Ponsel di Kisaran Kota menghadapi tantangan dalam pengelolaan stok voucher internet akibat pencatatan manual yang tidak efisien dan masa aktif terbatas. Untuk mengatasi masalah ini, diusulkan penerapan metode peramalan Single Moving Average (SMA) guna memprediksi kebutuhan stok berdasarkan data historis. Dengan demikian, pemilik usaha dapat mengelola stok lebih optimal, menghindari kekurangan atau kelebihan persediaan, serta meningkatkan efisiensi dan keuangan bisnis.Hasil penerapan metode SMA menunjukkan prediksi kebutuhan stok voucher untuk April dan Mei dengan akurasi Mean Absolute Percentage Error (MAPE) yang cukup baik. Untuk voucher IM3, prediksi stok masing-masing bulan adalah 244 dan 244,5 (MAPE 8,21%). Voucher Axis sebanyak 798 (MAPE 5,02%), XL sebanyak 713 dan 724,5 (MAPE 5,02%), Telkomsel sebanyak 942 dan 951 (MAPE 3,23%), Tri sebanyak 490 dan 491 (MAPE 7,94%), serta Smartfren sebanyak 656 dan 664 (MAPE 5,38%). Dengan akurasi yang cukup tinggi, metode SMA terbukti mampu meramalkan penjualan secara cepat dan akurat, membantu penyediaan stok sesuai kebutuhan, serta meningkatkan efisiensi operasional Bismillah Ponsel.
Kata Kunci: manajemen; persediaan; peramalan; penjualan; single moving average (SMA
Abstract:Abstract: Fitri Keramik Shop sells various types of ceramics. In this research, the researcher created a system that can make it easier to predict demand for ceramics in the following month based on the categories in Fitri…
ri Keramik by explaining the correct method for forecasting, one of the methods that can be used is Double Exponential Smoothing (DES) which is a forecasting method using uses a number of new actual demand data to generate forecast values for future demand by finding the average value as a forecast for the future period. The results of predicting demand for ceramics using an alpha value of 0.3 and having the lowest error rate are May 2023, Terraso: 176; Mosaic : 169; Standard Ceramic Floor: 163; Squared : 117.
Keywords: Analysis, Double Exponential Smoothing, Predicting Demand.
Abstrak: Toko Fitri Keramik melakukan penjualan berbagai jenis keramik. Pada penelitian ini, peneliti membuat sistem yang dapat memudahkan dalam meramalkan permintaan keramik pada bulan berikutnya berdasarkan kategori yang ada pada Fitri Keramik dengan memaparkan metode yang tepat dalam peramalan, salah satu metode yang dapat digunakan yaitu Double Exponential Smoothing (DES) yang merupakan metode peramalan dengan menggunakan sejumlah data aktual permintaan yang baru untuk membangkitkan nilai ramalan untuk permintaan dimasa yang akan datang dengan mencari nilai rata-rata tersebut sebagai ramalan untuk periode yang akan datang. Hasilnya dari memprediksi permintaan keramik dengan menggunakan nilai alpa 0,3 dan memiliki nilai tingkat error terendah yaitu Mei 2023, Teraso : 176; Mozaik : 169; Keramik Lantai Standart: 163; Kuadrat : 117.
Kata kunci: Analisis, Double Exponential Smoothing, Memprediksi Permintaan.
Abstract:Abstract: Top Fresh Chicken is one of the UKM that produces food made from chicken. The problem faced by Top Fresh Chicken is the excess supply of raw materials which results in high inventory holding costs and hampered…
capital allocation. In this study, historical data on stock of chicken raw materials will be used to test forecasting using the SES and WMA methods. The SES method is a simple forecasting method and relies on exponential smoothing to forecast the value of raw material inventories in the future. Meanwhile, the WMA method uses certain weights to calculate moving averages from historical data, where the highest weight is given to the most recent data. In the method comparison process, several evaluation factors will be used, including the level of accuracy, level of stability, and ease of implementation. By comparing the performance of the two methods, this study aims to determine the most accurate and appropriate method for forecasting chicken raw material stocks. The results of this study are expected to provide clear recommendations regarding the most suitable forecasting method used by Top Fresh Chicken. By using accurate and effective forecasting methods, companies can optimize the use of resources, reduce inventory costs, increase production efficiency, and avoid excess or shortage of raw material inventories.
Keywords: comparison of methods; single exponential smoothing; weighted moving average; raw materials; top fresh chicken.
Abstrak: Top Fresh Chicken merupakan salah satu UKM yang memproduksi makanan yang berbahan baku ayam. Permasalahan yang dihadapi oleh Top Fresh Chicken adalah kelebihan persediaan bahan baku yang mengakibatkan biaya simpan persediaan yang tinggi dan alokasi modal yang terhambat.Dalam penelitian ini, data historis persediaan bahan baku ayam akan digunakan untuk menguji peramalan menggunakan metode SES dan WMA. Metode SES merupakan metode peramalan yang sederhana dan mengandalkan eksponensial smoothing untuk meramalkan nilai persediaan bahan baku di masa depan. Sedangkan metode WMA menggunakan bobot tertentu untuk menghitung rata-rata bergerak dari data historis, di mana bobot tertinggi diberikan pada data terbaru.Dalam proses komparasi metode, beberapa faktor evaluasi akan digunakan, termasuk tingkat akurasi, tingkat kestabilan, dan kemudahan implementasi. Dengan membandingkan kinerja kedua metode, penelitian ini bertujuan untuk menentukan metode yang paling akurat dan tepat untuk meramalkan persediaan bahan baku ayam.Hasil dari penelitian ini diharapkan dapat memberikan rekomendasi yang jelas tentang metode peramalan yang paling cocok digunakan oleh Top Fresh Chicken. Dengan menggunakan metode peramalan yang akurat dan efektif, perusahaan dapat mengoptimalkan penggunaan sumber daya, mengurangi biaya persediaan, meningkatkan efisiensi produksi, dan menghindari terjadinya kelebihan atau kekurangan persediaan bahan baku.
Kata kunci : komparasi metode; single exponential smoothing; weighted moving average; bahan baku; top fresh chicken.