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Recent Submissions

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PENERAPAN DIAGRAM KONTROL DEMERIT PADA PEGENDALIAN KUALITAS PRODUK CACAT ROTTE BAKERY
(Elfitra, 2023-12) Dharma, Pandu Satria; Bustami
This study discusses the application of demerit control charts to quality control of Rotte Bakery defective products which consists of three types of bread, namely Fit O Mini, Cokelat Spesial, and Fit O Vanilla. The purpose of this study is to see the quality control of defective products during the production process through visualization in the form of a demerit control chart. The demerit control chart begins by determining the weight for each type of bread, then calculating the demerit value for each subgroup, followed by determining the centerline, upper center line, and lower center line, and ends by visualizing the number of defective products using the demerit control chart. The results showed that the quality of the Fit O Mini, Chocolate Special, and Fit O Vanilla products was still under control. This can be seen in the degree of membership in each subgroup which is still present in the upper and lower limit intervals of the demerit diagram.
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PENERAPAN METODE DEKOMPOSISI UNTUK PERAMALAN HARGA SAHAM PT BANK CENTRAL ASIA TBK
(Elfitra, 2023-12) Tampubolon, Omar Farrakhan; Bustami
Singular Spectrum Analysis (SSA) is a non-parametric time series analysis technique used for forecasting. The advantage of this method is that it does not require the assumption of stationarity, thus making SSA a good time series data analysis technique to describe trends and other components that have a simple structure. The data used for forecasting using the Riau Province Interest Rate in the period January 2013 to January 2023. The analysis carried out is in the form of a matrix to find the Eigen value and Eigen Vector. The right SSA model in this case is obtained by window length 37 and number of groups 3 with MAPE 4.569288%. The accuracy of this SSA method is considered very good for forecasting such as the Interest Rate data in Riau Province.
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MODEL HYBRID SINGULAR SPECTRUM ANALYSIS DAN NEURAL NETWORK UNTUK PERAMALAN KENAIKAN NILAI INFLASI DI INDONESIA
(Elfitra, 2023-12) Dwifattah, Muhammad Rizki; Bustami
Current economic developments cause increasing inflation rates in a country. One of the statistical methods used to determine the increase in inflation values is forecasting using a non-parametric time series model. This research was carried out using Singular Spectrum Analysis and Neural Network as a non-parametric forecasting method with monthly data on inflation values in Indonesia from January 2003 - December 2022. This analysis was carried out by forming a square matrix from the research data so that eigenvalues and eigenvectors were obtained in each matrix. as many as 50. In the calculations, the forecast results obtained for the next 5 month period show insignificant increases and decreases. Based on the accuracy results, an error was obtained using MAPE with forecasting results for the inflation value of 9%, which can be said to be in the very good category.
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PENERAPAN ALGORITMA FP-GROWTH UNTUK MENGANALISA POLA PEMBELIAN KONSUMEN PADA TOKO PAGARUYUNG DIESEL
(Elfitra, 2023-12) Anjheli, Maena; Sukamto
Pagaruyung Diesel store in Duri City has experienced Growth in both customers and product variety. The issue at hand is an imbalance in product inventory. Therefore, decisions need to be made based on the highest sales to efficiently manage inventory and enhance customer service. In this regard, transaction sales data is utilized to identify customer purchasing behavior. Data mining technology serves as a valuable tool in inventory information identification at Pagaruyung Diesel store. This technology employs pattern matching strategies and algorithms to uncover relationships within the data. One of the approaches used is the FP-Growth Algorithm, which allows the identification of common Item sets within the data. In this study, the FP-Growth Algorithm is applied to analyze purchasing patterns. The aim of this research is to implement the FP-Growth Algorithm method to analyze purchasing patterns at Pagaruyung Diesel store. The results are expected to assist in inventory management and decision-making. The research findings indicate that by using sales data for automotive spare parts from January to June 2022, the FP-Growth Algorithm method produces 5 association Rules with a Minimum Support of 1% and a Minimum Confidence of 50%. These results demonstrate that the FP-Growth Algorithm can be effectively applied to analyze purchasing patterns at Pagaruyung Diesel store.
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SINTESIS KOMPOSIT MnOx/ABU CANGKANG KELAPA SAWIT DENGAN VARIASI WAKTU KALSINASI DAN UJI AKTIVITAS KATALITIK UNTUK DEGRADASI METILEN BIRU
(Elfitra, 2023-12) Ambarita, Lidia Sartika Br; Awaluddin, Amir
The chemical industry is growing rapidly along with the increase in world population. The waste produced by this industry is the main cause of environmental pollution. One of the dyes that is difficult to degrade which has an aromatic compound group is methylene blue dye. One method that can be used to degrade methylene blue using a catalyst is the Fenton-like method. This research aims to synthesize the MnOx/ACKS composite using a one-step sol gel method, the synthesis is carried out by reacting KMnO4, glucose, and ACKS. The MnOx/ACKS composite was characterized using X-Ray Diffaraction (XRD). The XRD characterization results show that the MnO2 type in the MnOx/ACKS 1 Hour composite contains a mixed phase of cryptomelane, manganosite, birnessite and hausmanite. Degradation of methylene blue at a concentration of 5 mL H2O2, 25 mg composite, and 12.5 ppm methylene blue, was able to degrade methylene blue by 77.71% within 120 minutes.