Coffee Aroma Research Articles

Rapid classification of coffee origin by combining mass spectrometry analysis of coffee aroma with deep learning

Mislabeling the geographical origin of coffee is a prevalent form of fraud. In this study, a rapid, nondestructive, and high-throughput method combining mass spectrometry (MS) analysis and intelligence algorithms to classify coffee origin was developed. Specifically, volatile compounds in coffee aroma were detected using self-aspiration corona discharge ionization mass spectrometry (SACDI–MS), and the acquired MS data were processed using a customized deep learning algorithm to perform origin authentication automatically. To facilitate high-throughput analysis, an air curtain sampling device was designed and coupled with SACDI–MS to prevent volatile mixing and signal overlap. An accuracy of 99.78% was achieved in the classification of coffee samples from six origins at a throughput of 1 s per sample. The proposed approach may be effective in preventing coffee fraud owing to its straightforward operation, rapidity, and high accuracy and thus benefit consumers.

Design of a Web-Based Coffeeshop Ordering Information System

Coffee is a drink that is brewed from coffee beans that have been roasted and ground into coffee grounds. In addition to the distinctive taste and aroma of coffee, it also contains caffeine which can help reduce the risk of developing cancer, diabetes, heart disease and various other diseases. Therefore, information related to coffee is created, apart from this application provides information about coffee, it also carries out the buying and selling process. The needs provided are several types of local coffee in the territory of Indonesia. Making this system using the PHP programming language. The system that is made has several features, namely the starting location of the delivery of goods in the medan, the process of sending goods or orders is directly selected by the customer. The delivery services used are JNE, JTE and the Post Office. For goods purchase transactions, customers can choose the payment method available on the application, namely via transfer or using the OVO application that is already listed on the application.

Analisis Cita Rasa Kopi di Tilik Kopi Kota Padang

This research was motivated by customer reviews regarding the taste of coffee in Padang City Coffee. This research is classified as qualitative research with the method used being descriptive. The variables used in this research are coffee and taste. The research sample was 5 people, data was collected by distributing observations and interviews. The results of this research show that the aroma of the product presented is good with the criteria of a typical coffee aroma without the presence of the aroma of other ingredients such as chemicals. The acidity of the product presented is quite good with the typical criteria for coffee acid which has a pH of 4.85 to 5.10. The level of balance of taste of the product served is good because the coffee served has a taste that is formed due to the right mixture of ingredients. The level of viscosity of the product served is good by paying attention to the amount of ground coffee that will be processed with the water used using a dose of 1:2 with water. The bitter taste of the product served is very good because the bitterness produced is just right due to correct coffee processing, without any other causes such as bad coffee powder. The sweet taste of the product served is quite good according to consumer tastes. From all the aspects considered in this research, in general, espresso is better than Americano because espresso is the basis for making Americano itself.

Development of A Resistive Sensor Array Based on Graphene and Conducting Polymer Composites for Coffee Aroma Classification

This work aims to create a resistive sensor array for categorizing coffee from various plantations. A mixture of graphene oxide and a conductive polymer is used to create the sensor array. Eight types of sensors were made by dripping various mixtures of graphene oxide, polypyrrole, polyaniline, and poly acetate materials on the interdigitated electrode. Coffee fragrance gas was used for the sensor array test. The surface of the sensor array receives the scent gas created by the brewing of coffee grinds. Each sensor’s response profile is recorded. Each coffee sample has a distinct sensor response profile for simple separation with a distinct pattern. PCA analysis was used to examine sensor responses in order to find classification patterns of coffee samples from diverse plantations that were separated by brewing category. Sensor response data underwent PCA analysis, yielding scores of 54.74% PC1 and 26.17% PC2. These findings suggest that graphene-based and conducting polymer sensor array have a good potential for quick differentiation of different coffee varieties.

EKSPERIMEN PEMBUATAN KUE SEMPRONG SUBSTITUSI SANTAN DENGAN KOPI ESPRESSO SEBAGAI ALTERNATIF VARIAN RASA

The new taste presented by the addition of espresso coffee in making semprong cakes can also be an alternative for the community to enjoy semprong cakes. This research is an experimental study of making semprong cakes with the addition of espresso coffee levels of 30, 60 and 90. Experiments were carried out on 15 trained panelists and 20 untrained panelists. Based on the results of the hedonic quality test, the results obtained were that as many as 20 people, starting from 20 combined panelists, 10 trained panelists, and 10 untrained panelists stated that the coconut milk substitute semprong cake experiment with espresso coffee had significant differences in the color aspect. aroma, texture, and taste. Based on the results of the hedonic test, it was found that as many as 15 people including 15 combined panelists, 5 trained panelists, and 10 untrained panelists stated that they preferred color, aroma, texture, and taste in the sample. A which has a dark brown color, coffee aroma, very crunchy texture, and a sweet and slightly bitter taste.

Pengaruh Lama Perendaman dengan Sari Labu Siam (Sechium edule) Terhadap Penurunan Kafein Biji Kopi Arabika (Coffea arabica) Kintamani


 
 
 The process of decaffeination involves reducing the caffeine content in coffee and other substances containing caffeine using various methods, such as immersing them in siamese pumpkin extract. Siamese pumpkin extract contains protease enzymes that aid in the decaffeination process. This research aims to investigate the impact of soaking time with siamese pumpkin extract on decreasing the caffeine content of Kintamani arabica coffee beans and to determine the appropriate soaking duration for reducing the caffeine content of Kintamani arabica coffee. In this study, a Completely Randomized Design was employed with five levels of soaking time treatments, namely 0 hours, 12 hours, 24 hours, 36 hours, and 48 hours, which were repeated three times, resulting in 15 experimental units. The parameters observed included water content, protein content, caffeine content, and sensory evaluation, including aroma, taste, and overall acceptance. The data were analyzed using analysis of variance (ANOVA), and if there was a significant effect of the treatment, Duncan's multiple range test was applied. The duration of soaking Arabica Kintamani coffee beans with siamese pumpkin extract had a significant influence on the water content, protein content, caffeine content, and sensory attributes of the coffee. The optimal soaking time for producing decaffeinated coffee was found to be 24 hours, resulting in a caffeine content of 0.3% and a water content of 2.72%, with a protein content of 22.14%. The sensory evaluation revealed that the coffee had a light coffee aroma and a light bitter taste, which was preferred overall.
 
 

Sensory description of beverages of intervarietal hybrids of Conilon and Robusta: Natural and fermented coffees

AbstractThis study describes the sensory profile of beverages of Coffea canephora hybrids (clones BRS 2314 and BRS 2357) in natural (N) and fermented (F) versions. Flash Profile and Temporal Dominance of Sensations were performed; physicochemical characteristics were evaluated. Increase in total titratable acidity and reduction in pH was observed with fermentation. BRS 2314 beverages had higher contents of 5‐caffeoylquinic acid and caffeine. Natural coffees were described as having brown/coffee color, coffee aroma and flavor, roasted aroma and flavor, sweet aroma, and sour taste, and presenting dominance of coffee and tobacco flavors, and bitter and sour tastes. Fermented coffees were described as full‐bodied and having non‐characteristic, fermented and herbal aromas, astringent sensation, bitter taste and bitter aftertaste, and residual flavors, with the dominance of chocolate, fermented and roasted flavors, and bitter taste. BRS 2357 beverages were characterized by bitter taste and bitter aftertaste. BRS 2314N beverage presented attributes considered positive for quality.Practical ApplicationsThe results are relevant for the coffee production chain and consumers. Intervarietal hybrids of Conilon and Robusta are grown in an area characterized by family farming and with great prospects for sustainable production (in the Rondônia/BR state, Western Amazon) and are developed to express the best characteristics of both botanical varieties, as the high potential of Robusta coffees for fine cup beverages. The hybrid clones were successfully evaluated by experts, but the results do not necessarily correspond to the consumers' insights into coffee brew quality. In addition, fermentation allows to produce beverages with different nuances. The joint use of quick methodologies for static (Flash Profile) and temporal (Temporal Dominance of Sensations) sensory descriptions provided a closer representation of the consumers' perception of those products. This information brings new market perspectives for high‐yield Coffea canephora coffees that are now going through a moment of breaking paradigms regarding quality.

An AI-powered e-nose system using a density-based clustering method for identifying adulteration in specialty coffees

Coffee is a valuable commodity with diverse varieties and unique specifications, particularly in Indonesia, a coffee-producing country. Ensured classification and quality of coffee throughout the supply chain are crucial for industry stakeholders, particularly in terms of flavor and aroma. This study focuses on the authenticity of coffee, particularly specialized coffee beans from microclimates that may be impacted by climate change. Advanced technologies, such as electronic nose (E-Nose) systems paired with machine learning techniques, play a significant role in achieving accurate and efficient authentication. Furthermore, the research addresses adulteration issues, such as blending different types of coffee beans, which can discourage farmers from participating in coffee cultivation. In this study, we develop an authentication method leveraging the olfactory characteristics of coffee aroma, emphasizing the unique interplay between microclimate conditions and flavor profiles. The clustering method of density-based spatial clustering of applications with noise (DBSCAN) technique is used to authenticate tropical climate specialty coffee and recognize adulterated specialty coffee beans. In our case study, adulteration in Arabica and Luwak specialty coffees was successfully detected using the DBSCAN technique combined with dimensionality reduction methods. This work has demonstrated a novel method for identifying specialty coffee authenticity and adulteration using the E-Nose system paired with machine learning techniques.

A Study of the Physical Characteristics and Defects of Green Coffee Beans That Influence the Sensory Notes Using Machine Learning Models

This paper presents a detailed analysis of the relation between physical characteristics and defects of green coffee beans and the sensory profile that influence the sensory notes of fragrance, aroma, flavor, and aftertaste of coffee. Machine learning models were used to identify the variables of importance and identify the ways in which these variables affect the sensory note of coffee, to determine which algorithm and its hyperparameters have greater precision in determining the sensory values of coffee such as floral, fruity, herbal, nutty, caramel, chocolate, spicy, resinous, pyrolytic, earthy, fermented, and phenolic. The result indicates the relationship and importance that exist between the physical variables, defects, and size of the green coffee bean, with respect to their respective sensory notes. The data of the proposed system demonstrate that by combining the scores of several experts, a precision can be achieved analogously to that obtained by cupping experts; therefore, the possibility of errors induced by human concerns such as fatigue or subjectivity is reduced.

THE CHEMICAL CHARACTERISTICS OF ARABICA AND ROBUSTA GREEN COFFEE BEANS FROM GEOPARK RINJANI, INDONESIA

Green coffee beans are also called unroasted coffee beans. The chemical composition of green coffee beans plays a vital role in determining the final product’s aroma. The main objective of this research was to characterize the chemical properties of Arabica and Robusta green coffee beans grown in different regions of Geopark Rinjani, Lombok Island, Indonesia. The water, ash, protein, carbohydrate, total solids, and caffeine contents, total acidity, and pH were determined. Data were analyzed by analysis of variance. The results revealed significant differences in the moisture contents of Arabica beans from Sembalun, Sajang, and Sapit and Robusta beans from Rempek, Selelos, and Genggelang. Additionally, the ash contents of Arabica Sajang and Arabica Sapit showed notable differences compared to other samples. However, the total fat contents of Arabica Sajang, Arabica Sapit, Robusta Rempek, and Robusta Genggelang did not exhibit significant variations. On the other hand, significant differences were observed in the protein contents of all samples, particularly between Arabica Sembalun and Arabica Sapit, compared to Arabica Sajang, Robusta Rempek, Robusta Genggelang, and Robusta Selelos. Robusta coffee beans appeared to have a slightly lower pH than Arabica beans. The latter exhibited consistent acidity in the range of 0.20–0.21, whereas the former showed higher acidity levels (0.23–0.25). Arabica beans had a lower caffeine content, averaging 1.09%, whereas Robusta beans exhibited an average caffeine content of 2.09%. This research provides valuable insights into the chemical composition of green coffee beans from different species and locations within Geopark Rinjani, contributing to a better understanding of the factors influencing the aroma and quality of coffee.

Modeling of Coffee Fruit: An Approach to Simulate the Effects of Compression

The flavor, aroma, and color of coffee can be changed due to mechanical damage, reducing its quality. To measure the mechanical behavior of the fruit, compression tests can be performed at different stages of ripeness. In this study, we analyzed the deformation, strain energy, and von Mises stress of coffee fruits at mature, semi-mature, and immature stages under compression forces. Compression in three directions (x, y, and z) was simulated on coffee fruit models using the finite element method. A compression support was applied in the opposite direction to the force application axis. Numerical simulations of the compression process allowed us to verify that the more mature the fruit, greater the associated mean deformation (2.20 mm mm−1, 0.78 mm mm−1, and 0.88 mm mm−1), the lower the mean strain energy (0.07 mJ, 0.21 mJ, and 0.34 mJ), and the lower the mean equivalent von Mises stress (0.25 MPa, 1.03 MPa, and 1.25 MPa), corresponding to ripe, semi-ripe, and immature fruits, respectively. These analyses not only save time and professional resources but also offer insights into how strain energy and von Mises stress affect fruits at different maturation stages. This information can guide machine adjustments to reduce coffee harvesting damages.

Pengaruh Barista Terhadap Produk Coffee Shop di Kota Majalengka Provinsi Jawa Barat

The product is the main attribute of the coffee shop business, so it must be optimized so that consumers who have bought it can make a repurchase. However, optimal coffee shop products can only be created by dedicated baristas. This study aimed to analyze the influence of baristas on coffee shop products in Majalengka City and the indicators that consumers are most concerned about in these two variables. The research was conducted in April-May 2023 using a quantitative research design and survey method. The research population is consumers of Coffe Shop Marina in Majalengka City, and the number of samples is set at 120 respondents—data analysis using the Structural Equation Model instrument. The results of the study concluded that the barista had a real and positive effect on the product, and the indicator that consumers paid the most attention to in the barista variable was "speed (0.76)", while in the product variable was "the aroma of good coffee (0.79)". For this reason, it is recommended for Coffee Shop Marina business actors, in particular, to improve the quality of the barista's speed in making optimal coffee drinks and always strive to provide fresh and quality coffee bean raw materials so that the aroma is maintained so that they can achieve consumer satisfaction.

A Consumer Assessment of Fermented Green Coffee Beans with Common Beer/Wine Yeast Strains for Novel Flavor Properties

Fermentation is a critical step in the production of coffee when following standard wet processing, one of the most common methods used to remove the mucilage layer from coffee cherries. During this step, the de-pulped coffee cherries undergo fermentation with native yeast that modifies the flavor profile of the resultant coffee. This study aimed to ferment green coffee beans using commercial yeast strains from beer and wine prized for their ability to produce specific flavors, and subsequently evaluate the aroma and flavor of the coffee using coffee consumers. Four Saccharomyces cerevisiae strains were used: Belgian Ale, Sourvisiae, 71 B, and Tropical IPA, along with one non-Saccharomyces, Toluraspora delbrueckii (Biodiva), and a non-inoculated control sample. The green coffee beans underwent a controlled wet fermentation for 72 h, followed by roasting, grinding, and brewing. Results showed that flavor profiles varied broadly by yeast strain, suggesting that producing novel flavors in coffee through fermentation is feasible and that these flavors survive the roasting process; however, higher liking scores were still reported for the control sample compared to the fermented samples. Biodiva, a strain used in wine to produce esters and fruity flavors, resulted in coffee with highly fruity notes, and all strains were rated more floral than the control, while the sample fermented with Sourvisiae yeast used in the brewing of sour ales resulted in coffee that was both perceived as more sour and had the lowest pH, likely due to the degree of lactic acid this strain is engineered to produce. Further, there were significant color differences between the samples. In conclusion, fermenting green coffee beans with brewing and winemaking yeast strains strongly impacted the flavor and aroma of the resultant coffee; however, evaluating larger panels of strains or optimizing strain performance may yield flavor profiles more suitable for coffee.

Identification of Coffee Types Using an Electronic Nose with the Backpropagation Artificial Neural Network

Coffee is one of the famous plants’ commodities in the world. There are some coffee powders such as Arabica dan Robusta. This study aimed to identify two various coffee powders, Arabica and Robusta based on the blended aroma profiles, employing the backpropagation Artificial Neural Network (ANN). Four taste sensors were employed, namely TGS 2602, 2610, 2611, and 2620, to capture the diverse coffee aroma. These detectors were combined with the aroma sensors having transducers integrated with signal amplifiers or processors, which featured a load of 10 KΩ resistance. Three aroma types were investigated, namely Arabica coffee, Robusta coffee, and without coffee beans. The neural network architecture consisted of four inputs from all sensors, with one hidden layer housing eight neurons. Two neuron outputs were employed for classification, with 70 samples used for training ANN for each type. During the training phase, the developed neural network showed an impressive accuracy rate of 91.90%. TGS 2602 and 2611 sensors showed the most significant differences among the three aroma types. When analyzing ground Robusta coffee, TGS 2602 and 2611 sensors recorded 2.967 volts and 1.263 volts, with a gas concentration of 17.92 ppm and 2441.8 ppm. Similarly, the sensors for ground Arabica coffee displayed 3.384 volts and 1.582 volts with a gas concentration of 20.445 ppm and 3058.5 ppm in both TGS 2602 and 2611, respectively. The implemented ANN with aroma sensor as input successfully identify the coffee powders.

Using Hierarchical Agglomerative Clustering in E-Nose for Coffee Aroma Profiling: Identification, Quantification, and Disease Detection

Using Hierarchical Agglomerative Clustering in E-Nose for Coffee Aroma Profiling: Identification, Quantification, and Disease Detection

Effect of continuous instant pressure drop treatment on the rheological properties and volatile flavor compounds of whole highland barley flour

Continuous instant pressure drop (CIPD) treatment effectively reduces microbial contamination in whole highland barley flour (WHBF). Base on it, this study further investigated its effects on flour properties (especially rheological properties) and volatile compounds (VOCs) profile of WHBF, and compared it with that of ultraviolet-C (UV-C), ozone and hot air (HA) treatments. The results showed that the damaged starch content (6.0%) of CIPD-treated WHBF was increased, leading to a rough surface and partial aggregation of starch particle, thereby increasing the particle size (18.06 μm of D10, 261.46 μm of D50 and 534.44 μm of D90). Besides, CIPD treatment exerted a positive influence on the structure and rheological properties of WHBF, including an elevation in pasting temperature and viscosity. Notably, CIPD-treated WHBF exhibited higher storage modulus and loss modulus compared to the other three groups of sterilization treatments, contributing to the formulation of a better-defined and stable gel strength (tan δ = 0.38). UV-C and ozone, as cold sterilization techniques, also induced alterations in specific characteristics of WHBF. UV-C treatment led to changes in WHBF's crystallinity, while ozone treatment caused modifications in the secondary protein structure of WHBF. A total of 68 VOCs were identified in raw WHBF (including 3 acids, 19 alcohols, 25 aldehydes, 1 alkene, 8 esters, 2 ethers, 3 furans, and 7 ketones). The maximum flavor-contributing VOC in CIPD-treated WHBF remained dimethyl sulfide monomer (cabbage aroma), consistent with the raw WHBF. Conversely, in HA-treated WHBF, the maximum flavor-contributing VOC shifted to 2-furanmethanethiol monomer (roasted coffee aroma), altering the initial flavor presentation. These findings will provide strong support for the application of CIPD technology in the powdery foods industry.

Analisis komponen bioaktif dan atribut sensori seduhan kopi Arabika Kalosi Enrekang dengan pengolahan pascapanen berbeda [Analysis of bioactive compounds and sensory attributes of Kalosi-Enrekang Arabica coffee prepared different postharvest processing

Postharvest processing affects the chemical components and sensory attributes of coffee beans. This study aimed to evaluate the effect of postharvest processing on caffeoylquinic acids and alkaloids (bioactive compounds) and sensory attributes (aroma and taste) of brewed coffee. Coffee beans of Kalosi-Enrekang were processed using three postharvest processing methods (honey, natural, and full-washed), roasted at a medium degree, and brewed with tubruk brewing techniques. Bioactive compounds were analyzed using UPLC-PDA and sensory attributes were analyzed using the Quantitative Descriptive Analysis method. The data were analyzed using single-factor ANOVA and Principal Component Analysis. The research showed that postharvest processing did not affect the bioactive compound of brewed coffee. Postharvest processing affected the aroma and taste attributes of brewed coffee. Natural processing had dominant attributes of fruity, spicy, sweet, and caramelized. Honey processing had dominant attributes of nutty and roasted, while full-washed processing did not have dominant attributes. The result also showed that caffeoylquinic acids and alkaloids did not affect coffee brewed's aroma and taste attributes.

Effects of adding cocoa fermentation medium on cigar leaves in agricultural fermentation stage.

Background and Objective: With the development of the world economy and the integration of cultures, the Chinese cigar market has shown a significant upward trend. However, high-quality cigar leaves are mostly produced in Dominica, Cuba, Nicaragua and other places. In contrast, Chinese cigar leaves have problems such as insufficient aroma, which has become one of the main factors restricting the development of Chinese cigars. Adding medium to ferment is a traditional method in the cigar industry. At present, it mostly relies on manual experience, and lacks systematic and scientific research. At the same time, the addition of medium fermentation is mainly concentrated in the industrial fermentation process, and has not yet begun to be applied in the agricultural fermentation process. In this study, the medium was added to the agricultural fermentation process for the first time to explore the possibility of the application. The effects of adding cocoa medium to ferment on the chemical composition, sensory quality and surface microbial diversity of eggplant core cigar leaves were investigated.wrapper. Method: With Dexue 7' as the experimental material, the changes of main chemical components of wrapper fermented with water and cocoa medium were determined, and microbial community structure on the surface and relative abundance of cigar leaves at different turning periods were analyzed, and the functional genes were predicted. The results of the study were as follows: 1) The results of sensory evaluation showed that the addition of cocoa medium could highlight the aroma of bean, cocoa and coffee, improve the sweetness and fluency and the combustibility of cigar leaves. 2) The addition of cocoa medium increased the contents of proline and malic acid which were positively correlated with sensory quality, and decreased the contents of citric acid, linoleic acid, basic amino acids and aromatic amino acids which were negatively correlated with sensory quality. 3) The addition of cocoa medium increased the total amount of aroma components in cigar leaves, especially carotenoid degradation products, and changed the structural composition of some aroma substances in wrappercigar leaves. 4) The similarity of species composition between the water-added group and the cocoa-added group was higher, but the dominant microorganisms were more concentrated. Staphylococcus and Arthrobacter maintained a high relative abundance throughout the fermentation process, which may be the key microorganisms in the agricultural fermentation stage. 5) The addition of cocoa medium increased the expression abundance of related functional genes in cigar leaves, accelerated the fermentation process of cigar leaves, and bacteria played a major role in the fermentation process. Conclusion: Adding cocoa medium in the agricultural fermentation stage, the changes of bacterial community and dominant flora on the surface of cigar leaves are the main factors affecting their internal chemical components, and the addition of media has a positive effect on tobacco fermentation.

Uji Parameter Spesifik dan Non Spesifik p ada Kopi Robusta ( Coffea canephora )

Robusta coffee is the most widely cultivated type of coffee in Indonesia. Caffeine in coffee determines the taste and aroma of coffee. Extract standardization determines the quality of the extract. Therefore, this study aims to standardize the extract including organoleptic extract, calculating the yield weight, moisture content and ash content, as well as testing the caffeine content of Robusta coffee using the gravimetic method. The solvent used was ethyl acetate 99% with refluks extraction method. The results showed that the yield weight was 9,712%, the moisture content was 4,83% and the as content was 0,43%. The water content and ash content values meet the standards set by Farmakope Herbal Indonesia. Meanwhile, the value of caffeine levels shows 7,91 ± 0,01 %

Cosmetic Serum Loaded Arabica Coffee (Coffea arabica) Extract: Formulation and Antioxidant Study

Arabica coffee (Coffea arabica) is a natural antioxidant that can be used in the prevention of skin aging. This study was conducted to determine the comparison of variations in the composition of HPMC, CMC-Na, and Carbomer in the optimum formula of arabica coffee serum, then to determine the physical properties of the preparation, as well as the IC50 value ofarabica coffee extract and arabica coffee serum in the DPPH test. Arabica coffee extract was obtained by maceration method using 70% ethanol. Determination of the optimum formula of arabica coffee serum using the Simplex Lattice Design method. The optimum formula of arabica coffee serum was evaluated for physical properties including organoleptic test, homogeneity test, pH test, spreadability test, and adhesion test. The antioxidant activity of arabica coffee extract and the optimum formula of arabica coffee serum was tested using the DPPH method. Data analysis used SPSS One sample T-test statistics. The results showed that the composition variation of HPMC, CMC-Na, and Carbomer in the optimum formula of arabica coffee serum using the Simplex Lattice Design method was 0.1%:0.8%:0.1%. The resulting predicted values are a pH value of 4.88 and a spreadability value of 7.95 cm. The optimum formula of arabica coffee serum has the physical properties of the preparation, namely brown color, coffee aroma, light texture, a cool sensation when applied to the skin, homogeneous, has a spreadability of 7.93 cm, stickiness of 1 second, and pH value of 4.9. The IC50 value of arabica coffee extract and the optimum formula of arabica coffee serum are 8.13 ppm and 250 ppm. The results of the SPSS One sample T-test statistical analysis showed that there was no significant difference between the prediction response and the results of the optimum formula evaluation.