Prioritizing Barriers and Strategies Mapping in Business Intelligence Projects Using Fuzzy AHP TOPSIS Framework in Developing Country

Business Intelligence (BI) is an essential technology in an increasingly competitive landscape since it helps make decisions more accurately. To achieve an effective BI implementation, the organization must formulate the right strategy to overcome its challenges. This research aimed to develop a framework to map barriers into strategies using qualitative and quantitative methods. The qualitative approach is driven by interviewing BI experts to validate the barriers and strategies previously obtained. Based on the interview, there are 19 barriers and 9 strategies that could be used. The quantitative approach compiles a priority list of the most significant barriers and the most effective strategies to overcome these barriers using fuzzy AHP TOPSIS, an MCDM method to eliminate inconsistencies during ranking. The results indicate that the lack of collaboration between the IT and BI departments, the BI implementation demands to be done quickly, and low data quality are the main barriers that hinder BI's success. This research also found that business people's involvement in a BI project is the best strategy to overcome the obstacles. The chances of a successful BI implementation will increase by having good cooperation between IT and business units within the company. Doi: 10.28991/ESJ-2022-06-02-010 Full Text: PD

Turning Pirates into Subscribers: A Status Quo Bias Perspective on Online Movie Service Switching Intention

This study aims to analyze the factors that influence a person's intention to use a subscription-based streaming service application using the perspective of the inertia of piracy movie application users. This study investigates the factors that affect the inertia of movie piracy application users. The theory used is a combination of the status quo bias theory and coping theory. This research uses a quantitative approach and an online survey method for data collection. Data collection resulted in 378 responses that were subsequently analyzed using the covariance-based structural equation modeling (CB-SEM) technique. It was found that inertia (the level of user inertia) negatively affects intention to use (the intention to use a subscription-based streaming service application) and convenience. In addition, convenience, perceived controllability (a person's level of control over the application), and morality positively influence intention to use. Furthermore, it was also found that perceived cost and personalization do not affect the intention to use. Inertia is also positively and significantly influenced by the transition cost (effort to move). The factors that have the highest correlation values are transition cost and inertia. Doi: 10.28991/ESJ-2022-06-05-06 Full Text: PD

STRATEGI MANAJEMEN PERUBAHAN UNTUK MENDUKUNG IMPLEMENTASI SISTEM INFORMASI RUMAH SAKIT STUDI KASUS: RSUD RAA SOEWONDO PATI

Seiring dengan perkembangan rumah sakit dan teknologi informasi, Sistem Informasi Rumah Sakit (SIRS) RAA Soewondo dirasa tidak mampu lagi memenuhi kebutuhan informasi. Keterbatasan tersebut membuat pihak manajemen berencana mengganti SIRS mereka. Agar implementasi SIRS yang baru dapat berhasil, perlu dilakukan strategi manajemen perubahan yang tepat pada rumah sakit. Penelitian ini bertujuan untuk merumuskan strategi manajemen perubahan untuk implementasi SIRS di RAA Soewondo. Penelitian dilakukan menggunakan pengambilan data melalui kuesioner, wawancara, dan observasi. Tindakan perubahan didapat dengan analisis SWOT, kemudian dikelompokan ke dalam metode manajemen untuk membuat strategi manajemen perubahan. Metode manajemen perubahan yang digunakan adalah Anderson dan Anderson Nine Phase Model. Dari hasil penelitian, didapatkan hasil bahwa faktor resistensi karyawan relatif kecil. Tindakan perubahan yang sesuai dengan manajemen perubahan adalah dukungan pimpinan untuk implementasi perubahan SIRS, membuat persamaan visi dan misi ke semua bagian rumah sakit tentang perubahan SIRS, merancang keadaan perubahan yang diinginkan dengan memerhatikan divisi yang terpengaruh oleh perubahan SIRS ini, melakukan penggantian dengan metode pararel cutover, memberikan penghargaan kepada karyawan yang ikut menyukseskan program ini, serta membuat kebijakan baru agar kebijakan yang sudah berjalan menjadi permanen. Hasil akhir menunjukkan secara umum karyawan rumah sakit setuju akan perubahan SIRS saat ini. Along with the development of hospitals and information technology, the Soewondo RAA Hospital Information System (SIRS) felt unable to meet the information needs. These limitations make the management of SIRS plans to replace their SIRS. In order for successful implementation of new SIRS, change management strategy needs to be done right at the hospital. This study aims to formulate strategies for implementing change management in the RAA Soewondo SIRS. The study was conducted using data collection through questionnaires, interviews, and observation. Action changes obtained with SWOT analysis and then grouped into a management method for making the change management strategy. Change management method that had been used is Anderson and Anderson Nine Phase Model. The study shows that the staff’s resistance is relatively small. Action changes according that related to change management is leadership support for implementation of changes to SIRS, making equality vision and mission to all parts of the hospital about the change of SIRS, designing state of the desired changes with respect to the division that is affected by changes in SIRS, do the replacement with parallel cutover method , presents awards to employees who make this program succeed, and create new policies to estabilish policies that are already running to be permanent. The final results shows: in general, the employees agreed to change the current SIRS

PERBANDINGAN ALGORITMA KLASIFIKASI DALAM PENDETEKSIAN PENYAKIT KANKER

Kanker merupakan salah satu penyakit pembunuh teratas. Menurut  data dari WHO tahun 2008, kanker menyebabkan 12,6% kematian di dunia setelah penyakit jantung dan infeksi. Salah satu kesulitan dalam pendeteksian penyakit kanker adalah perlunya pasien untuk melakukan berbagai macam uji lab sebelum mereka divonis terkena penyakit kanker atau tidak. Penelitian ini bertujuan untuk melakukan deteksi penyakit kanker berdasarkan hasil uji lab yang sudah dilakukan oleh pasien. Terdapat empat hasil uji lab yang dipergunakan sebagai variabel untuk melakukan klasifikasi. Untuk melakukan deteksi penyakit kanker ini, digunakan beberapa algoritma klasifikasi yang sudah disediakan oleh SPSS Clementine 11.1 atau Weka 3.6.0, yaitu  Neural Network, C5.0, Logistic, Classification via Regression, dan LogitBoost. Algoritma Neural Network  sendiri  terdiri dari 6 metode, yaitu Dynamic ,Prune, Exhaustive Prune, Quick, RBFN dan Multiple. Percobaan dilakukan sebanyak sepuluh kali untuk masing-masing algoritma atau metode. Pada tiap percobaan, terdapat dua kali treatment terhadap data yang diolah.  Hasil percobaan menunjukkan bahwa  algoritma Neural Network dengan metode Prune menghasilkan hasil yang terbaik dalam mendeteksi penyakit kanker

Pengantar Sistem Informasi Manajemen Rumah sakit

xxviii, 244hlm., 23 c