With the proliferation of the use of chatbots across industries, business-to-business (B2B) businesses have started using cognitive chatbots for improved customer service which signifies our research. By extending the Technology Acceptance Model and Information Systems Success Model, this study examines personalised contextual customer service using cognitive chatbot. A quantitative research method is applied to the primary data collected from 300 respondents of B2B businesses. The study contributes to the limited research on chatbots and suggests improvement in customer service. The findings provide evidence of high value by customers, particularly while checking for real-time information on reliability and accessibility of products/services. The automated answers to repetitive questions on the recurrent issues create a seamless experience for the customers. This research makes significant theoretical contributions by integrating two models into a simplified model in chatbot literature and manifest that trust affects the willingness to use the cognitive chatbot which drives automation.

Cognitive Chatbot for Personalised Contextual Customer Service: Behind the Scene and beyond the Hype

Interpretable fuzzy clustering using unsupervised fuzzy decision trees

The application of online learning in various educational institutions in the Covid-19 Pandemic has had an impact on behavioral attitudes where many educators and students have also complained about the limited technology facilities, operations, and internet networks in some areas or quotas to access online learning. Followed by the popularity of the Zoom application in supporting education, the authors researched the application of the Technology Acceptance Model (TAM) to the acceptance of the Zoom application in online learning to determine the effect of using applications in online learning with 4 variables accompanied by multiple linear regression hypothesis testing, F-test and T-test. using SPSS. The test results in Perceived Usefulness, Perceived Ease of Use, and Behavioral Intention to Use affect Actual System Usage with significant and positive results of 20.21. Behavioral Intention to Use is more dominant than other variables with a value of 5.31, while the lowest is Perceived Ease of Use with a value of (-0.50).

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Implementation technology acceptance model (tam) on acceptance of the zoom application in online learning

PT. Inti Pratama Semesta (PT. IPS) adalah perusahaan yang bergerak dalam bidang penyediaan jasa kontruksi. Mempunyai proyek berhubungan dengan pembangunan seperti bangunan rumah, gedung dan pabrik.  Sebagai perusahaan yang bergerak dalam bidang kontruksi dalam melakukan pemantauan perkembangan proyek harus dapat dilaksanakan dengan baik agar tercapai tujuan perusahaan. Permasalahan yang di hadapi PT. Inti Pratama Semesta saat ini yaitu permasalahan dalam pengerjaan proyek tidak dapat diketahui dengan cepat mengakibatkan penyelesaian proyek menjadi lambat (tidak sesuainya antara waktu rencana kerja dengan waktu pelaksanaan pengerjaan proyek), sering terjadi kesalahan pencatatan data perkembangan proyek mengakibatkan kekeliruan dalam  menentukan data perkembangan proyek, tidak adanya gambar pengerjaan proyek akibatnya pada saat di lakukan pengecekan terhadap pekerjaan proyek sering terjadi kesalahan pengerjaan proyek. Tujuan penelitian ini adalah untuk membangun sistem informasi monitoring perkembangan proyek berbasis web untuk mempermudah  manager dalam melakukan pemantauan perkembangan proyek.  Teknik perancangan sistem menggunakan metode OOAD (Object Oriented Analysis Design) dan Tools UML (Unified Modelling Languange), Teknik  testing  sistem menggunakan teknik Blackbox, dengan metode pengembangan sistem menggunakan metode waterfall yang merupakan metode dengan model sekuensial. Hasil penelitian ini adalah sebuah sitem informasi monitoring perkembangan proyek berbasis web.

http://ejournal.uin-suska.ac.id/index.php/RMSI/article/download/1305/1165

Rancang bangun sistem informasi monitoring perkembangan proyek berbasis web (studi kasus: pt. inti pratama semesta)

Data mining (DM) is the process of extracting knowledge from data. Knowledge from customer behaviour segmentation is useful for companies in setting the target market and developing a marketing strategy. Recency Frequency Monetary (RFM) model is the most behaviour segmentation used. Many customer-segmentation studies in various application areas use the RFM model that collaborates with DM. With many methods in DM, the selection of appropriate methods can reveal useful hidden patterns in customer segments. This paper aims to analyse DM methods that collaborate with the RFM model and synthesize them to propose a customer segmentation framework. This study uses a comprehensive literature review published in 2015-2020. The most widely used methods are clustering and visualization from seven DM methods analysed. Due to the increased visualization function and the need for customers’ geo-demographic data to be considered in the analysis, this study presents a new framework for using DM methods with the RFM based segmentation in the Geographic Information Systems (GIS) environment. This framework helps analysts utilize DM methods to uncover and understand customer characteristics, so companies can set the target market and develop a marketing strategy to increase their competitive advantage.

A review of data mining methods in RFM-based customer segmentation

Analysis for Customer Lifetime Value Categorization with RFM Model

Mental Hospital of Tampan is the Pekanbaru City Government Agency which deals with health and psychiatric problems, such as excessive stress, psychiatric disorders, services to people with HIV / AIDS and the service of child development. The mental hospital of Tampan has a large drug supply system with different specifications in the pharmacy department. However, in the process of drug supply, there are still obstacles, namely recording drug supplies and managing transaction data, still using ledgers. In addition, employees often make mistakes in recording and checking as well as inventory of drugs that often occur excess drug orders. The focus of this research is to create a web-based drug inventory information system. System design method uses Object Oriented Analysis and Design (OOAD) method. D rug inventory system employees can manage drug supplies, record, sell, order medicines to suppliers and make reports through a web-based inventory system. Keywords :  Inventory system , Mental Hospital of Tampan , OOAD

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Rancang Bangun Sistem Informasi Inventory Obat Pada Rumah Sakit Jiwa Tampan Berbasis Web

The aim of study is to discover outlier of customer data to found customer behaviour. The customer behaviour determined with RFM (Recency, Frequency and Monetary) models with K-Mean and DBSCAN algorithm as clustering customer data. There are six step in this study. The first step is determining the best number of clusters with the dunn index (DN) validation method for each algorithm. Based on the dunn index, the best cluster values were 2 clusters with DN value for DBSCAN 1.19 which were minpts and epsilon value 0.2 and 3 and DN for K-Means was 1.31. The next step was to cluster the dataset with the DBSCAN and K-Means algorithm based on the best cluster that was 2. DBSCAN algorithm had 37 outliers data and K-means algorithm had 63 outliers (cluster 1 are 26 outliers and cluster 2 are 37 outliers). This research shown that outlier in DBSCAN and K-Means in cluster 1 have similarities is 100%. But overal outliers similarities is 67%. Based the outliers shown that the behaviour of customers is a small frequency of spending but high recency and monetary.

Analysis of DBSCAN and K-means algorithm for evaluating outlier on RFM model of customer behaviour

Era globalisasi sangat berpengaruh terhadap perkembangan teknologi informasi bagi sekolah, salah satunya bagi Madrasah Aliyah Negeri 2 Model (MAN 2 Model) Pekanbaru. MAN 2 Model Pekanbaru, merupakan salah satu sekolah Islam Negeri dan satuan kerja dari Kementrian Agama yang menggunakan sistem informasi, yakni dikenal dengan sistem informasi pengelolaan nilai raport. Sistem ini telah diterapkan selama 2 tahun. Permasalahan yang terjadi selama penerapannya yaitu terjadi error dalam input nilai, format data yang tertukar, dan guru harus mengetahui sendiri batasan dalam penggunaan sistem informasi. Tujuan yang ingin dicapai yaitu untuk menganalisis persepsi penerapan sistem informasi pengelolaan nilai raport berdasarkan masing-masing faktor kebermanfaatan, kemudahan, dan secara bersama-sama terhadap faktor penerimaan teknologi informasi, serta memberikan rekomendasi kepada MAN 2 Model Pekanbaru. Penelitian ini menggunakan metode Technology Acceptance Model (TAM) untuk mengetahui persepsi pengguna terhadap sistem informasi, yang terdiri dari 3 variabel yaitu perceived usefulness (PU), perceived ease of use (PEU), dan accpetance of IT (ACC). Jenis pengolahan data yang digunakan adalah regresi linier berganda, uji T dan uji F untuk hipotesis. Hasil dari regresi linier berganda berdasarkan Unstandardized Coefficent sebesar 4,330, dan seluruh hipotesis berpengaruh positif. Sehingga penelitian ini dapat memberikan rekomendasi bagi MAN 2 Model Pekanbaru.

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Siti Monalisa

Papers

Analysis for Customer Lifetime Value Categorization with RFM Model

Rancang bangun sistem informasi monitoring perkembangan proyek berbasis web (studi kasus: pt. inti pratama semesta)

Rancang Bangun Sistem Informasi Inventory Obat Pada Rumah Sakit Jiwa Tampan Berbasis Web

Analysis of DBSCAN and K-means algorithm for evaluating outlier on RFM model of customer behaviour

Analisis penerapan sistem informasi pengelolaan nilai raport menggunakan metode tam