Indonesia has the largest medicinal plant species in the world and these plants are used as Jamu medicines. Jamu medicines are popular traditional medicines from Indonesia and we need to systemize the formulation of Jamu and develop basic scientific principles of Jamu to meet the requirement of Indonesian Healthcare System. We propose a new approach to predict the relation between plant and disease using network analysis and supervised clustering. At the preliminary step, we assigned 3138 Jamu formulas to 116 diseases of International Classification of Diseases (ver. 10) which belong to 18 classes of disease from National Center for Biotechnology Information. The correlation measures between Jamu pairs were determined based on their ingredient similarity. Networks are constructed and analyzed by selecting highly correlated Jamu pairs. Clusters were then generated by using the network clustering algorithm DPClusO. By using matching score of a cluster, the dominant disease and high frequency plant associated to the cluster are determined. The plant to disease relations predicted by our method were evaluated in the context of previously published results and were found to produce around 90% successful predictions.
Abstract. Andrianto D, Husnawati, Hermita S, Haryanti S. 2020. Classification of betel leaves (Piper betle) from 15 ethnics in eastern Indonesia based on phytochemicals fingerprint analysis. Biodiversitas 21: 252-257. Betel (Piper betle Linn), also called Golden Heart of Nature, is often used as traditional medicine. Nonetheless, betel plants originated from different places contains different phytochemicals profile, resulting in different utilization across ethnics. The research aimed to classify betel leaves from eastern Indonesia origins based on phytochemical profiles. In this study, the phytochemical profiles of 69 betel leave samples from 15 ethnics in eastern Indonesia were obtained using High-Performance Liquid Chromatography (HPLC) fingerprint analysis. This data was then used to classify the betel leaves samples using Principal Component Analysis (PCA). The results of the analysis show that the betel leaves from Eastern Indonesia can be divided into three clusters. Cluster 1 consisted of betel leaves originated from two ethnics, namely Komoro and Greri, from Papua, while Cluster 2 consisted of those originated of two ethnics, namely Sumber Baba and Demta, both were also from Papua. Cluster 3 consisted of betel leaves originated 11 ethnics, namely Asilulu (Maluku), Balesang (Central Sulawesi), Bungku (Central Sulawesi), Mulong Kuni (Central Sulawesi), Saluan (Central Sulawesi), Tialo (Central Sulawesi), Tolage (Central Sulawesi), Gebe (North Maluku), Makian (North Maluku), Mey Brat (West Papua) and Waigeo (West Papua). The location of P. betle plantation in this research accounts for clusterization of samples, Papua island give the highest biodiversity because we can find all the three cluster in Papua island.
This study aims to analyze the marketing strategy of BNI Credit Cards in the face of global competition at PT. Bank Negara Indonesia (Persero) Tbk Banda Aceh Branch Office. This study uses a qualitative approach with a descriptive type where the type of data used is secondary data sourced from various reports and documentation from PT. Bank Negara Indonesia (Persero) Tbk Banda Aceh Branch Office. The results of this study indicate that in marketing BNI Banda Aceh Branch credit cards a strategy that can be used is a marketing strategy that differentiates the market (Differentiated marketing), which is to determine the target market segmentation in accordance with the target types of credit card products that are in accordance with the segmentation. The Banda Aceh BNI branch also uses a concentrated marketing strategy such as the marketing of BNI-Unsyiah affinity Credit Cards which is focused on alumni of Syiah Kuala University throughout Indonesia. Besides that, another strategy used by the Banda Aceh BNI branch in marketing BNI Credit Cards is by issuing pre aproval credit cards, where certain customers in accordance with applicable regulations are directly proposed to issue credit cards on behalf of these customers, if the customer agrees for card issuance, the card can be activated immediately. Furthermore, BNI provides the convenience of non-cash transactions through the YAP (Your All Payment) application as a payment tool for (cashless) and without showing the debit card or credit card (Cardless) through a smartphone. This YAP application is an advantage owned by BNI and the first in Indonesia.
The technology used in the printing industry is currently growing rapidly. Generally, the digital printing industry uses raw materials in the form of paper production. The use of paper material with large volumes is clear badly in need of purchasing large quantities of paper stock as well. The purchase of paper stocks with a constant amount at the beginning of each month for various types of paper causes a buildup or lack of material stock standard on certain types of paper. During this time the purchase and ordering of raw materials only based on the estimates or predictions of the owner. In this paper proposed forecasting will be carried out in the digital printing industry by applying the ARIMA model for each type of raw material paper with the Palembang F18 digital printing case study. The ARIMA modeling applied will produce different parameters for each materials paper type so as to produce forecasting with the Akaike Information Criterion (AIC) value averages 13.0294%.
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