Judul: Customer Segmentation of PLN UPJ East Bogor Region Using Fuzzy C-Means
Abstrak: Electricity is a very crucial source of energy nowadays. This is proven by the increase of PLN customers every month. The increasing number of customers and the use of electricity should be followed by increasing the quality of service. PLN can make a better decision to increase its service by knowing its customer’s segmentations. The data of electricity usage is periodically kept by PLN and can be used for customer segmentation analysis. Customer segmentation can be conducted using clustering method such as Fuzzy C-Means algorithm. After the segmentation has been done, the characteristics of electricity usage of each segment can be identified, and the distribution of each segment can be visualized on a map to make it easier to see the distribution of each segment from its spatial aspects. The clustering process in this research is used four clusters, which represent the usage level, which are low class, medium class, high class, and very high class. As the result of the research, we found out that the low class users are the majoring, whereas the high class has the least users. Areas that have users from all segments are Babakan, Bantarjati, Baranang Siang, and Kedung Halang.
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Judul: Karakterisasi Pelanggan PLN Menggunakan Algoritma Fuzzy C Mean
Abstrak: Based on the technology point of view, CRM is a system tool in analyzing customers’ behavior based on customer histories data. One of the important tasks of CRM is identifying PLN customers’ behavior based on their behavior in using electricity. Customer identification is done by segmenting customers. In this research, the customer that will be segmented are home, business and industrial customer. The variable that used as a attribute in segmentation process are the duration of subscribing, total payment, discipline in paying and total electric usage. The system that developed in this research provided many choice of variable combination to be segmented. The goal is to provide many choice for PLN in segmenting customer. The method used for segmenting customer is fuzzy c-mean algorithm. To measure the segmentation accuration, the result of the clustering is validated by the Xie and Beni index method. The result of the research showed that business and home customer are more accurate if they are clustered into 3 clusters, while the industrial customer in some variable combination are more accurate if they are clustered into 3 clusters and the some variable combination are more accurate if they are clustered into 4 clusters. The result of customers’ character segmentation can be used as supporting data in making PLN’s business decision which is related to CRM.
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Judul: Aktivitas antitoksik katekin-α-glukosida hasil reaksi transfer enzimatik
Abstrak: Katekin mcrupakan salah satu senyawa (unman polifenol yang dikenal memiliki aktivitas biomedisin. Akan tetapi hingga saat ini scnyaw3 katckin belum dimanfaatkan secara optimum karena mcmiliki kelamtan yang rendah di dalam air dan tidnk stabil. Kestabiian dan kelarutannya dapat ditingkalkan dengan cara mcngubah senyawa tcrscbut mcnjadi senyawa dalam bentuk glikosida mclalui reaksi transgiikosilasi. baik secara kimin. enzimatik. maupun mcnggunakan kullur suspcnsi sel. Sintesis senyawa po1ifcnol glukosida mclalui transfer enzimatik menjadi pilihan karena memiliki berbagai kelebihan baik dari segi biaya maupun metode. Katekin-α-glukosida tersebut memiliki potcnsi linggi untuk diuji dan dimanfaatkan. salah satunya sebagai senyawa antitoksik yang akhir-akhir ini mulai menarik perhatian ilmuwan.
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