The purpose of this study was to examine the theoretical basis in an effort to build the competitiveness of the banking services industry, particularly in terms of customer satisfaction and loyalty. This type of research uses explanatory research. The sampling method used a non-probability sampling, used purposive sampling technique that has become a customer for two years, used questionnaires to 100 respondents in Bandung bank customers.Measurement validity uses confirmatory factor analysis, while test reliability is calculated by Cronbach Alpha method. Analysis to test the hypothesis uses the path analysis. The findings illustrate a clear pattern of the dimensions of customer relationship marketing, satisfaction effect built, and several important findings including empirical verification mediating role overall customer satisfaction in the formation of loyalty attributes.
Abstract. Modification planning of business transformation involving technological utilization required a system of transition and migrat ion planning process. Planning of system migration activity is the most important. The migration process is including complex elements such as business re-engineering, transition scheme mapping, data transformation, application development, individual involvement by computer and trial interaction. TOGA F ADM is the framework and method of enterprise architecture imp lementation. TOGAF ADM provides a manual refer to the architecture and migration planning. The planning includes an implementation solution, in this case, IT solution, but when the solution becomes an IT operational planning, TOGAF could not handle it. This paper presents a new model framework detail transitions process of integration between TOGAF and ITIL. We evaluated our models in field study inside a private university.
Indonesian people have electronic citizen card called e-KTP. e-KTP is NFC based technology embedded inside Indonesian citizenship identity card. e-KTP technology has never been used until now since it was launch officially by the government. This research proposes an independent framework for bridging the gap between Indonesia regulation for e-KTP and commercial use in the many commercial or organization sector. The Framework proposes interoperability framework using novel combination component, there are e-KTP reader, Middleware and Web Service. KAFA (e-KTP Middleware and Framework) implementing Internet of Things (IoT) concept to make it as open standard and independent. The framework use federation mode or decentralized data for interoperability, to make sure not breaking the law of privacy. Extended development of AES-CBC cipher algorithm was used to encrypt the data on the transport between middleware and web service.
The development of technology today has been growing rapidly and has an impact on the behavior patterns of people who feel it. The Ministry of Communication and Information (KOMINFO) released a data that of 265 million people of Indonesia, there are around 54% have used internet technology or about 143 million people. In one survey IDN Research Institute said that there are three Social Media that are widely used in Indonesia, namely Facebook, Instagram and Twitter. This study focuses on extracting data in the form of text produced from social media twitter that responds to the account of the RI presidential candidates in the 2019 elections. Sentiment analysis is obtained through tweet classification using sentiment analysis tools such as NRC Lexicon and Bing Lexicon so that information is obtained in the form of positive polarity and negative polarity from community tweets towards the Presidential candidates in the 2019 elections. Using March data before the 2019 election, for candidate 01 Joko Widodo, the NRC Lexicon analysis gave a value of 249 and bing lexicon of 267 with an average value of 0.11, while for candidate 02 Prabowo Subianto the NRC Lexicon analysis gave a value of 195 and bing lexicon of 204 with an average value of 0.085. Using april data after the 2019 election. Candidate 01 Joko Widodo still received a lot of responses from netizens but the sentiment value shifted more negatively compared to candidate 02 Prabowo Subianto. For candidate 01 Joko Widodo the NRC Lexicon analysis gave a value of 17 and bing lexicon of -273 with an average value of -0,246, while for candidate 02 Prabowo Subianto the NRC Lexicon analysis gave a value of 238 and bing lexicon of -73 with an average value of -0.02430939.
PT. Telekomunikasi Indonesia adalah salah satu perusahaan yang mengedepankanpelanggan akan tetapi belum ada informasi tentang karakteristik pelanggan. Pada penelitian ini dilakukan analisa karakteristik pelanggan sebagai dasar penetapan segmentasi pelanggan dan customer profiling pelanggan produk digital service add on Indihome menggunakan Algoritma K-Means. Penentuan jumlah cluster terbaik dilakukan menggunakan metode Elbow dan diperoleh nilai K = 3, sehingga data pelanggan dikelompokkan kedalam tiga segmen. Pengolahan data pelanggan dibagi menjadi 3 simulasi dengan persentase data train dan data test 80% - 20%, 70% - 30% dan 50% - 50%. Data yang digunakan berjumlah 1392 record sebagai populasi imanadata tersebut akan digunakan untuk mencari karakteristik setiap data tersebut. Evaluasi cluster dilakukan menggunakan metode Silhouette Index, Davies Bouldin Index dan Calinski Harabasz Index. Hasil dari penelitian menunjukan bahwa simulasi ketiga merupakan simulasi terbaik berdasarka evaluasi cluster dengan presentasi data train 50% dan data test 50% dimana customer profiling dilihat dengan menganalisis anggota masing-masing cluster dari simulasi ketiga dimana cluster 0 memiliki anggota 396 pelanggan dengan kategori pelanggan yang memberikan keuntungan terbesar bagi perusahaan, cluster 1 memiliki anggota 286 pelanggan dengan kategori pelanggan yang tanpa disadari memiliki potensi besar dalam memberikan keuntungan bagi perusahaan, dan cluster 2 memiliki anggota 14 pelanggan dengan kategori pelanggan yang memberikan keuntungan lebih sedikit daripada biaya untuk memberikan pelayanan.
Saat ini banyak perusahaan swasta yang bergerak di bidang jasa pengiriman yang mengakibatkan banyaknya pesaing bagi Kantor Pos Cimahi dan dapat mengakibatkan penurunan jumlah pelanggan yang menggunakan jasa Kantor Pos Cimahi. Oleh karena itu, diperlukan suatu sistem untuk membantu Kantor Pos Cimahi dalam mengidentifikasi calon pelanggan, sehingga dapat diketahui calon pelanggan mana yang dapat memperoleh perlakuan khusus, sehingga pelanggan tersebut dapat terus menggunakan jasa Kantor Pos Cimahi. Sistem yang dibangun menggunakan bahasa pemrograman PHP dan metode Algoritma C 5.0 yang merupakan salah satu algoritma pohon keputusan yang dapat membantu untuk menentukan pelanggan potensial. Penelitian menggunakan data transaksi periode bulan januari – oktober 2020 dimana atribut yang digunakan yaitu bulan, nama perusahaan, jenis kiriman yang digunakan, jumlah transaksi selama sebulan, dan total uang. Hasil penelitian menunjukan bahwa algoritma C 5.0 mampu melakukan menentukan data pelanggan potensial dengan akurasi sebesar 96%.
In general, the college admission process is done through registration, file selection, examinations, an announcement of the results of students who pass, and ends with re-registration. In this case, a problem was found where there is a significant decrease in the number of student who register with those who re-register .Things like this can reduce the balance between new students and students who meet the requirements, to make a decrease in the quality of higher education and affect accreditation. Based on these problems, a classification method was developed to look for patterns of students who would enter institutions and what factors influence students to re-register. To improve the accuracy of the decision tree algorithm the author use adaptive boosting (adaboost) in finding factors that make prospective students continue to the re-registration process. From the results of the study, the AdaBoost-based decision tree algorithm shows that the level of accuracy has an increase of 20%. The presentation of results is as follows, 61.4% (decision tree); 91.35% (decision tree + AdaBoost).
e-KTP is an Indonesian Identity Card based on Near Field Communicator technology. This technology was embedded in every e-KTP card for every Indonesian citizen. Until this research, e-KTP technology never to be utilized by any stack-holder neither government agencies nor nongovernment organization or company. e-KTP Technology inside the card never been used and go with conventional with manual copy it with photocopy machine or take a photograph with it. This research was proposing an open standard to utilized e-KTP Technology. The open standard will bring e-KTP technology used as is and used broadly in many government agencies or much commercial company. This research was proposing decentralized network model especially for storing e-KTP data without breaking privacy law. Besides providing high specs of the server, a decentralized model can reduce the cost of server infrastructure. The model was proposing using Distributed Hast Table which was used for peer-to-peer networks. The decentralized model promised high availability and the more secure way to save and access the data. The result of this model can be implemented in many network topology or infrastructure also applicable to implement on Small Medium Enterprise Company.
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