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Oviliani Yenty Yuliana
Faculty of Economics, Petra Christian University
Computer Science & IT Industrial & Manufacturing Engineering

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IMPLEMENTASI REFERENTIAL INTEGRITY CONSTRAINT PADA MICROSOFT ACCESS DALAM UPAYA MEMELIHARA KONSISTENSI DATA Yuliana, Oviliani Yenty
Jurnal Informatika Vol 2, No 1 (2001): MAY 2001
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (371.515 KB) | DOI: 10.9744/informatika.2.1.pp. 33-43

Abstract

Data is business asset that should be safeguarded and maintained. Business data is recorded in a table/relation. Because inconeet relation structure could produce any modification anomaly, this relation should be normalized. Data modification in normalized relation will face referential integrity constraint problem. This problem could make inconsistent data and wrong information. Referential integrity constraint depends on minimum relationship cardinality. The trial and implementation of referential integrity constraint is taken on Microsoft Access. Abstract in Bahasa Indonesia : Data adalah asset perusahaan yang harus dijaga dan dipelihara. Data perusahaan dicatat pada tabel/relation. Struktur relation yang kurang baik dapat mengakibatkan modification anomaly, sehingga relation tersebut harus di-normalisasi. Modifikasi data pada relation yang sudah di-normalisasi akan menghadapi masalah referential integrity constraint. Masalah tersebut menyebabkan data tidak konsisten dan menghasilkan informasi yang salah. Referential integrity constraint tergantung pada minimum relationship cardinality. Penulis mengimplementasikan dan menguji coba referential integrity constraint pada Microsoft Access. Kata kunci: modification anomaly, normalization, referential integrity constraint, relationship cardinality constraint.
Pemetaan Penderita Pneumonia di Surabaya dengan Menggunakan Geostatistik Hartanto, Stefanie; Halim, Siana; Yuliana, Oviliani Yenty
Jurnal Teknik Industri Vol 12, No 1 (2010): JUNE 2010
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (294.777 KB) | DOI: 10.9744/jti.12.1.pp. 41-46

Abstract

In this paper we mapped the location of Pneumonia disease in Surabaya. We also analyse the survival of the afflicted and predict the spread of the disease using Kriging. The study reveals that after 45 days in the hospital, the survival of the Pneumonia’s patients decrease to 46.8%. Moreover, the centers of this disease are in Tubanan and Sukomanunggal Both of these regions are in West Surabaya which also is an industrial part of the city.
Bayesian Belief Network untuk Menghasilkan Fuzzy Association Rules Intan, Rolly; Yuliana, Oviliani Yenty; Kristanto, Dwi
Jurnal Teknik Industri Vol 12, No 1 (2010): JUNE 2010
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (201.875 KB) | DOI: 10.9744/jti.12.1.pp. 55-60

Abstract

Bayesian Belief Network (BBN), one of the data mining classification methods, is used in this research for mining and analyzing medical track record from a relational data table. In this paper, a mutual information concept is extended using fuzzy labels for determining the relation between two fuzzy nodes. The highest fuzzy information gain is used for mining fuzzy association rules in order to extend a BBN. Meaningful fuzzy labels can be defined for each domain data. For example, fuzzy labels of secondary disease and complication disease are defined for a disease classification. The implemented of the extended BBN in a application program gives a contribution for analyzing medical track record based on BBN graph and conditional probability tables.
MINING MULTIDIMENSIONAL FUZZY ASSOCIATION RULES FROM A DATABASE OF MEDICAL RECORD PATIENTS Intan, Rolly; Yuliana, Oviliani Yenty; Handojo, Andreas
Jurnal Informatika Vol 9, No 1 (2008): MAY 2008
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (273.576 KB) | DOI: 10.9744/informatika.9.1.15-22

Abstract

Mining association rules is one of the important tasks in the process of data mining application. In general, the input as used in the process of generating rules is taken from a certain data table by which all the corresponding values of every domain data have correlations one to each others as given in the table. A problem arises when we need to generate the rules expressing the relationship between two or more domains that belong to several different tables in a normalized database. To overcome the problem, before generating rules it is necessary to join the participant tables into a general table by a process called Denormalization Process. This paper shows a process of generating Multidimensional Fuzzy Association Rules mining from a normalized database of medical record patients. The process consists of two sub-processes, namely sub-process of join tables (Denormalization Process) and sub-process of generating fuzzy rules. In general, the process of generating the fuzzy rules has been discussed in our previous papers [1, 2, 3, 4]. In addition to the process of generating fuzzy rules, this paper proposes a correlation measure of the rules as an additional consideration for evaluating interestingness of provided rules.
PENDEKATAN MODEL MATEMATIS UNTUK MENENTUKAN PERSENTASE MARKUP HARGA JUAL PRODUK Yuliana, Oviliani Yenty; Wahyudi, Yohan; Halim, Siana
Jurnal Teknik Industri Vol 4, No 2 (2002): DECEMBER 2002
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1074.253 KB) | DOI: 10.9744/jti.4.2.pp. 58-72

Abstract

The purpose of this research is to design Mathematical models that can determine the selling volume as an alternative to improve the markup percentage. Mathematical models was designed with double regression statistic. Selling volume is a function of markup, market condition, and substitute condition variables. The designed Mathematical model has fulfilled by the test of: error upon assumption, accurate model, validation model, and multi collinear problem. The Mathematical model has applied in application program with expectation that the application program can give: (1) alternative to decide percentage markup for user, (2) Illustration of gross profit estimation that will be achieve for selected percentage markup, (3) Illustration of estimation percentage of the units sold that will be achieve for selected percentage markup, and (4) Illustration of total net income before tax will get for specific period. Abstract in Bahasa Indonesia : Penelitian ini bertujuan untuk merancang model Matematis guna menetapkan volume penjualan, sebagai alternatif untuk menentukan persentase markup harga jual produk. Model Matematis dirancang menggunakan Statistik Regresi Berganda. Volume penjualan merupakan fungsi dari variabel markup, kondisi pasar, dan kondisi pengganti. Model Matematis yang dirancang sudah memenuhi uji: asumsi atas error, akurasi model, validasi model, dan masalah multikolinearitas. Rancangan model Matematis tersebut diterapkan dalam program aplikasi dengan harapan dapat memberi: (1) alternatif bagi pengguna mengenai berapa besar markup yang sebaiknya ditetapkan, (2) gambaran perkiraan laba kotor yang akan diperoleh setiap pemilihan markup, (3) gambaran perkiraan persentase unit yang terjual setiap pemilihan markup, dan (4) gambaran total laba kotor sebelum pajak yang dapat diperoleh pada periode yang bersangkutan. Kata kunci: model Matematis, aplikasi program, volume penjualan, markup, laba kotor.
RANCANGAN DATABASE SUBSISTEM PRODUKSI DENGAN PENDEKATAN SEMANTIC OBJECT MODEL Yuliana, Oviliani Yenty
Jurnal Teknik Industri Vol 4, No 1 (2002): JUNE 2002
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jti.4.1.pp. 8-18

Abstract

To compete in the global market, business performer who active in industry fields should have and get information quickly and accurately, so they could make the precise decision. Traditional cost accounting system cannot give sufficient information, so many industries shift to Activity-Based Costing system (ABC). ABC system is more complex and need more data that should be save and process, so it should be applied information technology and database than traditional cost accounting system. The development of the software technology recently makes the construction of application program is not problem again. The primary problem is how to design database that presented information quickly and accurately. For that reason it necessary to make the model first. This paper discusses database modelling with semantic object model approach. This model is easier to use and is generate more normal database design than entity relationship model approach. Abstract in Bahasa Indonesia : Dalam persaingan di pasar bebas, para pelaku bisnis di bidang industri dalam membuat suatu keputusan yang tepat memerlukan informasi secara cepat dan akurat. Sistem akuntansi biaya tradisional tidak dapat menyediakan informasi yang memadai, sehingga banyak perusahaan industri yang beralih ke sistem Activity-Based Costing (ABC). Tetapi, sistem ABC merupakan sistem yang kompleks dan memerlukan banyak data yang harus disimpan dan diolah, sehingga harus menggunakan teknologi informasi dan database. Kemajuan di bidang perangkat lunak mengakibatkan pembuatan aplikasi program bukan masalah lagi. Permasalahan utama adalah bagaimana merancang database, agar dapat menyajikan informasi secara cepat dan akurat. Untuk itu, dalam makalah ini dibahas pemodelan database dengan pendekatan semantic object model. Model data ini lebih mudah digunakan dan menghasilkan transformasi yang lebih normal, jika dibandingkan dengan entity relationship model yang umum digunakan. Kata kunci: Sub Sistem Produksi, Semantic Object Model, Database Relational.
Co-Authors Andreas Handojo Dwi Kristanto Rolly Intan Siana Halim Stefanie Hartanto Tanti Octavia Yohan Wahyudi