The effect of soft and extreme action in public complaint behavior on satisfaction with complaint handling

Malaysia is experiencing a tremendous increase in mobile phone services users. Service providers are providing various complaint channels as one of the ways to improve services. Although complaining provides significant impact to organizations as well as to complainers or consumers, ironically the number of public complaints is insignificant. Based on previous study, two actions in public complaint namely public complaint soft action and public complaint extreme action were used in this study as the exogenous variables and satisfaction with complaint handling (SATCOM) as the endogenous variable. A total of 285 complainers of mobile phone user were selected as respondents. The values for goodness-of-fit, average variance extracted, construct reliability and convergent validity confirmed the measurement model prior proceeding to structural model. The structural model revealed mixed results that provide indication of consumer SATCOM specifically in the mobile phone service industry

The effect of soft and extreme action in public complaint behavior on satisfaction with complaint handling

Malaysia is experiencing a tremendous increase in mobile phone services users. Service providers are providing various complaint channels as one of the ways to improve services. Although complaining provides significant impact to organizations as well as to complainers or consumers, ironically the number of public complaints is insignificant. Based on previous study, two actions in public complaint namely public complaint soft action and public complaint extreme action were used in this study as the exogenous variables and satisfaction with complaint handling (SATCOM) as the endogenous variable. A total of 285 complainers of mobile phone user were selected as respondents. The values for goodness-of-fit, average variance extracted, construct reliability and convergent validity confirmed the measurement model prior proceeding to structural model. The structural model revealed mixed results that provide indication of consumer SATCOM specifically in the mobile phone service industry

Identifikasi Area Terdampak Oil Seep di Darat dari Data Foto Udara Menggunakan Metode Object Based Image Analysis dan Convolutional Neural Networks (Studi Kasus: Kelurahan “X”)

Rembesan minyak merupakan salah satu peristiwa yang merugikan lingkungan pada industri minyak dan gas. Hal ini dikarenakan senyawa kimia yang terkandung pada rembesan minyak dapat mengakibatkan penurunan kualitas lingkungan hidup. Rembesan minyak (Oil Seep) tidak hanya terjadi di wilayah perairan, tetapi juga di daratan, yang terserap oleh tanah. Kejadian ini dapat mengindikasikan adanya sistem perminyakan di bawah permukaan tanah. Dalam penelitian ini daerah terdampak rembesan minyak diidentifikasi menggunakan metode deep learning dengan Convolutional Neural Networks dimana mesin diharapkan meniru sistem kerja otak manusia dalam mengidentifikasi objek. Data foto udara yang telah terorthorektifikasi dilakukan proses segmentasi untuk membantu proses pelabelan training data pada tahap selanjutnya. Training data tersebut menjadi data masukan pada tahap train deep learning model, dan akan dilakukan proses klasifikasi piksel untuk mendeteksi area terdampak oil seep. Hasil pengolahan berupa tingkat akurasi model mencapai 93% dan raster yang menampilkan area terdampak oil seep, yang kemudian dihitung luasan areanya, dan menghasilkan perhitungan area terdampak oil seep seluas ±1,4 hektar