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SINTESIS KOMPOSIT MnOx/ABU CANGKANG KELAPA SAWIT UNTUK DEGRADASI METILEN BIRU: VARIASI SUHU KALSINASI
(Elfitra, 2024-12) Sibarani, Panji Haratua; Awaluddin, Amir
Manganese oxide is an important compound in nature for the transformation of various
compounds into simpler compounds. Synthesis of manganese oxide can be carried out
using the sol-gel method. The aim of this research is to examine the effect of calcination
temperature on the characteristics and catalytic activity of MnOx/ACKS composites.
The synthesis of the MnOx/ACKS composite was carried out by mixing KMnO4,
glucose and activated ACKS. The MnOx/ACKS composite was characterized using XRay
Diffraction (XRD). The XRD characterization results show that the MnOx/ACKS
composite consists of a quartz phase and a mixed phase of manganese oxide such as
managanosite, cryptomelane, hausmanite and binnerssite. Degradation of methylene
blue at a concentration of 12.5 ppm, a volume of 5 mL of H2O2 and a composite mass of
25 mg was able to degrade methylene blue by 86.67% within 120 minutes.
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.
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.
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.
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.