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INDONESIA
Indonesian Journal of Business Intelligence (IJUBI)
Published by Universitas Alma Ata Yogyakarta
ISSN : 26213915     EISSN : 26213923     DOI : -
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Fokus jurnal adalah karya inovatif pada analisis, desain, pengembangan, implementasi, evaluasi program, proyek, dan produk sistem informasi dalam manajemen strategis dan intelijen bisnis.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 6 Documents
 1 
Search results for , issue "Vol 1, No 2 (2018): Indonesian Journal of Business Intelligence (IJUBI)" : 6 Documents clear
SISTEM PENDUKUNG KEPUTUSAN DENGAN MENGGUNAKAN MENGGUNAKAN METODE MULTI ATRIBUTE UTILITY THEORY (MAUT) UNTUK PENENTUAN BANTUAN RUMAH TINGGAL SEHAT Wahyu Widodo; Idi Nastoto
Indonesian Journal of Business Intelligence (IJUBI) Vol 1, No 2 (2018): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Program Studi S1 Sistem Informasi Fakultas Komputer dan Teknik Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (156.337 KB) | DOI: 10.21927/ijubi.v1i2.911

Abstract

Candi merupakan salah satu desa yang berada di Kabupaten Gunungkidul, Daerah Istimewa Yogyakarta. Desa Candi  memiliki 20 dusun. Di wilayah Desa Candi tesebar rumah – rumah penduduk  terdapat rumah tinggal sehat dan rumah tinggal tidak sehat. Dengan wilayah 20 Dusun Pemerintah Desa Candi kesulitan dalam menentukan rumah sehat tinggal dan rumah tidak sehat tinggal. Dari permasalahan di atas maka sistem pendukung keputusan  menjadi suatu kebutuhan untuk menyelesaikan permasalahan Pemerintah Desa Candirejo. Sistem pendukung keputusan dirancang dengan mengunakan metode Multi Attribute Utility Theory (MAUT). Untuk menentukan rumah tinggal sehat atau tidak sehat, terdapat 23 kriteria, dengan dua alternative. Dengan dibuatnya sistem pendukung keputusan menggunakan metode MAUT  Pemerintah Desa Candirejo bisa dengan mudah  menentukan  rumah sehat tinggal dan rumah tidak sehat tinggal.
SISTEM INFORMASI MANAJEMEN ASET SEKOLAH BERBASIS WEB . Hoiriyah; . Andriyanto
Indonesian Journal of Business Intelligence (IJUBI) Vol 1, No 2 (2018): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Program Studi S1 Sistem Informasi Fakultas Komputer dan Teknik Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1603.072 KB) | DOI: 10.21927/ijubi.v1i2.918

Abstract

Adanya sarana dan prasarana merupakan penunjang kegiatan administrasi dan pembelajaran di sebuah lembaga pendidikan. Sarana dan prasarana sangat penting untuk menunjang proses kegiatan belajar mengajar serta meningkatkan rating sebuah lembaga pendidikan. SDN Bicorong 1 merupakan salah satu SD yang memiliki aset berupa aset bangunan, tanah dan juga benda-benda seperti peralatan untuk kegiatan belajar mengajar. Manajemen penataan aset pada SDN Bicorong 1 masih konvensional sehingga data-data aset tersebut rentan rusak bahkan hilang. Adanya kekeliruan dalam proses pencatatan serta pengelolaan aset akan mengakibatkan meningkatnya biaya operasional pengadaan aset. Oleh sebab itu Sistem Informasi Manajemen Aset Sekolah dibangun untuk mengelola dan menyimpan data-data aset sekolah. Hasil yang diperoleh dalam pembuatan aplikasi ini adalah user dapat melakukan pencatatan penerimaan materiil, pencatatan pengolaan  materiil serta melaporkan seluruh data aset maupun penyusutan aset bergerak yang ada.
SEGMENTASI PELANGGAN BISNIS DENGAN MULTI KRITERIA MENGGUNAKAN K-MEANS Yanuar Wicaksono
Indonesian Journal of Business Intelligence (IJUBI) Vol 1, No 2 (2018): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Program Studi S1 Sistem Informasi Fakultas Komputer dan Teknik Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (270.089 KB) | DOI: 10.21927/ijubi.v1i2.872

Abstract

Customer knowledge is an important asset, in gathering, and managing from sharing customer knowledge into valuable capital for the company. This causes the company to continue to innovate in producing products and serving according to customer needs. To find out the needs of each customer, the company needs to make customer segmentation. Customer segmentation is defined as the division into different groups with similar characteristics to develop marketing strategies that are tailored to customer characteristics. The easiest, simplest, well-known and commonly used model of customer characteristics is the model of the recency, frequency, monetary (RFM) criteria. The RFM model still has weaknesses in low customer segmentation capacity and does not provide information on the continuity of customer transactions in understanding customer loyalty. The research method used is the Knowledge Discovery in Database (KDD) method. The data is transformed into another format that suits the needs of analysis and then the customer is segmented using clustering data mining techniques with the K-Means algorithm. From the experiments, the RFM model guesses loyal customers when reviews, frequency and monetary are high. In reality, the recency only provides information on the customer making the last transaction and the high number of transaction frequencies can be done without the customer's stability in making transactions each period. Implementing multi-criteria in customer segmentation can be better than just RFM criteria. So it will not be wrong to treat customers according to the groups that have been formed.
DESIGN OF IDENTIFICATION OF SINGLE DEPRESSION DISORDERS USING NATURAL LANGUAGE PROCESSING MODEL IN PATIENT COMPLAINTS Soma Setiawan Ponco Nugroho; Muhammad Najamuddin Dwi
Indonesian Journal of Business Intelligence (IJUBI) Vol 1, No 2 (2018): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Program Studi S1 Sistem Informasi Fakultas Komputer dan Teknik Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (300.479 KB) | DOI: 10.21927/ijubi.v1i2.882

Abstract

Unconsciously mental disorders often begin with mild symptoms such as anxiety and depression. In cases of depression with long periods of time can result in disruption of a person's mindset and suicidal arising. Based on WHO data in 2010 suicide rates due to depression in Indonesia reached 1.6 to 1.8 per 100,000 people. Unfortunately the symptoms of depressive disorders are often difficult to recognize because a series of patient complaints are in the form of medical narratives or unstructured texts written by doctors. So to get a diagnosis is done by extracting symptoms from complaints data in the form of medical narrative texts. In this study, a design for identifying a single depressive disorder will be built using rule-based reasoning and the Natural Language Processing approach to extract symptoms in a medical narrative or patient complaint text.
MEMBANGUN MEDIA PEMBELAJARAN 7 KEAJAIBAN DUNIA BERBASIS AUGMENTED REALITY PADA MATA PELAJARAN ILMU PENGETAHUAN SOSIAL KELAS VI Akbar Permana Putra; Tri Widodo; Tri Rochmadi
Indonesian Journal of Business Intelligence (IJUBI) Vol 1, No 2 (2018): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Program Studi S1 Sistem Informasi Fakultas Komputer dan Teknik Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (203.172 KB) | DOI: 10.21927/ijubi.v1i2.890

Abstract

Educational Equity in Indonesia is categorized low, it is approved by decreased amount of facilities used in learning process. There are finded in only particular sectors like city, then in village and minorities have not been got the same right. The using of learning media is so helpful in delivering the material among to the students and can be used as dynamic teaching material so it can help in catching and understanding the material. Augmented reality is one of technological development that can be used in making learning media in android operation system with using marker as object reader such as seven wonders of the world. The using of augmented reality makes the object more factual so it can increase students’s motivation in learning. The method used in making this media is Systems Development Life Cycle method followed as 1) Analysis, 2) Design, 3) Testing, 4) Implementation and 5) Maintenance. Testing in making learning media application seven wonders of the world is applied with using black box testing and media expert, material expert and users’s testing. The testing result presents this media can help teaching learning process with percentage average is 90.37 % got from media expert’s testing in 86,36%, material expert’ testing in 87,5%, and user’s testing in 97,27%. It means this learning media is so practiced.
ANALISIS KEPUASAN MAHASISWA TERHADAP KINERJA PORTAL UNIVERSITAS ALMA ATA MENGGUNAKAN PENDEKATAN END-USER COMPUTING SATISFACTION DAN DELONE AND MCLANE MODEL Asti Ratnasari
Indonesian Journal of Business Intelligence (IJUBI) Vol 1, No 2 (2018): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Program Studi S1 Sistem Informasi Fakultas Komputer dan Teknik Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (429.91 KB) | DOI: 10.21927/ijubi.v1i2.897

Abstract

Kepuasan pengguna merupakan salah satu aspek untuk mengevaluasi sistem informasi. Sistem informasi dikatakan baik, jika pengguna merasa puas terhadap sistem informasi yang diterapkan dalam suatu organisasi. End User Computing Satisfaction dan Delone and McLean Model of Information Systems, keduanya merupakan model evaluasi sistem informasi untuk mengetahui kepuasan pengguna. Penelitian ini bertujuan untuk mengetahui faktor-faktor yang mempengaruhi kepuasan pengguna terhadap kinerja Portal UAA (konten, akurasi, format, kemudahan penggunaan, ketepatan waktu, kualitas informasi, kualitas sistem dan kualitas layanan). Lebih lanjut, penelitian ini juga memodelkan kepuasan pengguna baru dengan memodifikasi End User Computing Satisfaction dan Delone and McLean Model of Information Systems. Analisis data yang digunakan untuk pengolahan data adalah analisis regresi berganda. Analisis regresi berganda digunakan untuk mengetahui pengaruh antar variabel independen terhadap variabel dependen.

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