Pembuatan Aplikasi Digital Library di Jurusan Ilmu Komputer Universitas Nusa Cendana Berbasis Web

The development of digital library (digital library) can not be separated from the development of information technology. Digital library (digital library) is built on web technology, which allows accessing collections of digital files by users, whenever and wherever the user's position is through the internet. Computer Science Department Library had information stored physical forms such as books, theses, journals and various other scientific work is a collection of 115 pieces. However, management is still closed in the sense just for the students and lecturers so that still untapped by many. Application is a web-based digital library using a global network of media, namely the Internet. Making these applications using the programming language PHP and MySQL as database. For the development of applications using the System Development Life Cycle (SDLC) Waterfall models. Based on black box testing can be seen that in running applications run well because the test result consistent with the result expected by the internal user and based on internal testing results of questionnaire use applications, the largest percentage in the results of a questionnaire on the aspects of software engineering that is 66,25 % (response 5 = very good), on the aspects of functionality that is 67,5 % (response 5 = very good) and on the aspects of visual communication that is 77,5 % (response 5 = very good). With the use of a questionnaire testing the application using Likert's Summated Rating Method (LSR), the overall total score (1000) on the interpretation of LSR, program is considered successful

Penerapan Logika Fuzzy Menggunakan Metode Mamdani dalam Optimasi Permintaan Obat

Planning a good drug supply at the puskesmas is needed to support health services provided by the puskesmas, in addressing the problem of planning drug requests to suit the needs that exist, the researcher uses Mamdani method in fuzzy form that are making fuzzy set, application of rule function, composition rule, affirmation (defuzzy) using method of MOM (Mean of Maximum). Parameters used are initial stock, receipt, preparation, use, ending and demand stock. The calculation was performed using data for 2 years, and it was done 1 year to compare the results of the Health Centre request and the system request. From the test results, the total system demand is smaller than the total demand for Puskesmas, so the system optimization is obtained at 7.623% for 3 drug data so that it can increase the efficiency of the budget funds of Rp. 3,168,223, so it can be concluded that the Fuzzy Mamdani method is a method that provides optimal solution

Sistem Pendukung Keputusan Calon Penerima Raskin dengan Metode Polygons Area Method (Pam) di Kelurahan Airnona-kota Kupang

Raskin (Beras Miskin) is one of the Indonesian government programs to help reduce the expenditure of the poor people. This program is conducted by Bulog and Local Government. Raskin distribution procedure at Airnona sub-district is still using manual method, that those who will receive Raskin is submitted by RT, so that a Decision Support System (DSS) is needed to help handle the problem. The PAM (Polygons Area Method) method is one of the methods in DSS which can help solve unstructured problems. This study uses 8 criteria namely, monthly income, quantity of dependents, floor area of the house, the type of house floor, type of the house wall, assets, lighting source, and drinking water source. System test is done by comparing the ranking system with the name issued by Dinas Sosial. This test uses 66 interview data with 2016 recipient data resulting in similarity rate of 43% and unsimilarity rate is 57%. During then analysis on several data the conclusion is system able to provide good result

SISTEM PENDUKUNG KEPUTUSAN PEMBERIAN PINJAMAN MENGGUNAKAN APLIKASI FUZZY SIMPLE ADDITIVE WEIGHTING

The loan service process is one of many routines applied to improve the welfare of either members or the community in cooperative. This process requires a high accuracy in selecting the eligible loans. Bad credits, that oftenly occurred in many cooperative membership, mainly caused by the lack of accuracy of the cooperative itself in selecting eligible loans based on the specific criterias. Implements and development for loan decision support system using Fuzzy Simple Additive Weighting (F-SAW) method. This method is able to accommodate the deficiancy of SAW in terms of providing linguistic assessments. The system is tested by comparing the system decision to the cooperative decision. According to 7 test data with loan amount below Rp 10,000,000 and 5 test data with loan amount between Rp 15,000,000 – Rp 20,000,000, it appears that 9 of them provide the same decision as what the committee decided (75%), while 3 of them do not (25%)

PEMBUATAN APLIKASI DIGITAL LIBRARY DI JURUSAN ILMU KOMPUTER UNIVERSITAS NUSA CENDANA BERBASIS WEB

The development of digital library (digital library) can not be separated from the development of information technology. Digital library (digital library) is built on web technology, which allows accessing collections of digital files by users, whenever and wherever the user's position is through the internet. Computer Science Department Library had information stored physical forms such as books, theses, journals and various other scientific work is a collection of 115 pieces. However, management is still closed in the sense just for the students and lecturers so that still untapped by many. Application is a web-based digital library using a global network of media, namely the Internet. Making these applications using the programming language PHP and MySQL as database. For the development of applications using the System Development Life Cycle (SDLC) Waterfall models. Based on black box testing can be seen that in running applications run well because the test result consistent with the result expected by the internal user and based on internal testing results of questionnaire use applications, the largest percentage in the results of a questionnaire on the aspects of software engineering that is 66,25 % (response 5 = very good), on the aspects of functionality that is 67,5 % (response 5 = very good) and on the aspects of visual communication that is 77,5 % (response 5 = very good). With the use of a questionnaire testing the application using Likert’s Summated Rating Method (LSR), the overall total score (1000) on the interpretation of LSR, program is considered successful

PENERAPAN METODE MULTI FACTOR EVALUATION PROCESS PADA APLIKASI SISTEM PENDUKUNG KEPUTUSAN PENENTUAN PERMOHONAN PINJAMAN NASABAH PADA KOPERASI SIMPAN PINJAM GLORIA

Lending to customers is one of the services provided by Koperasi Simpan Pinjam Gloria. Bad loans caused by the process of loan transactions manually causing harm to the cooperative. In this study, designed and constructed a decision support system application using MFEP (Multi Factor Evaluation Process) where the process begins with entering customer data, the criteria data including asset, utility loans, loan size, duration, guarantees, profit / loss of the principal  efforts per month and profit / loss of the financial per month, the data classification criteria, the data assessment for further calculated  and sorted based on the highest value. System testing  by comparing the manual calculation results with the results of the system  on 3 customer data as test data obtained similar results which showed that the system has  accuracy of 100% and system testing using blackbox method showed compliance with the system design. The end result of this research is the determination of the decision support system application for a loan customer with MFEP method. The output of this system is the result of several alternative rank that become the managers reference in decision-making

SISTEM PENDUKUNG KEPUTUSAN CALON PENERIMA RASKIN DENGAN METODE POLYGONS AREA METHOD (PAM) DI KELURAHAN AIRNONA-KOTA KUPANG

Raskin (Beras Miskin) is one of the Indonesian government programs to help reduce the expenditure of the poor people. This program is conducted by Bulog and Local Government. Raskin distribution procedure at Airnona sub-district is still using manual method, that those who will receive Raskin is submitted by RT, so that a Decision Support System (DSS) is needed to help handle the problem. The PAM (Polygons Area Method) method is one of the methods in DSS which can help solve unstructured problems. This study uses 8 criteria namely, monthly income, quantity of dependents, floor area of the house, the type of house floor, type of the house wall, assets, lighting source, and drinking water source. System test is done by comparing the ranking system with the name issued by Dinas Sosial. This test uses 66 interview data with 2016 recipient data resulting in similarity rate of 43% and unsimilarity rate is 57%. During then analysis on several data the conclusion is system able to provide good result

IMPLEMENTASI CASE BASED REASONINGUNTUK MENDIAGNOSIS PENYAKIT TUBERKULOSIS MENGGUNAKANALGORITMA K-NEAREST NEIGHBOR

Case-Based Reasoning produces a solution based on similarities to previous cases. New case solutions result from the placement of similarities with old cases. In this reseach the authors applied CBR to diagnose tuberculosis. System knowledge sources are obtained by collecting medical records of tuberculosis patients in 2014-2016. Calculation of similarity values using the K-Nearest Neighbor algorithm with a thereshold value of 80%. This system can diagnose 3 types of tuberculosis based on 25 symptoms. The system output consists of the type of tuberculosis based on the symptoms experienced by the patient, treatment solutions and presentation of similarities between new cases and old cases. Based on the results of testing with 51 cases the results: (a) testing with 3 new case scenarios obtained the accuracy of each system for data scenarios obtained by 31 training data (60% of 51 cases) and 20 test data (40% of 51 cases) accuracy is 63%, the second scenario accuracy obtained with 35 training data (70% of 51 cases) and 16 test data (30% of 51 cases) accuracy is 69.2% and the third scenario accuracy obtained with 41 training data (80% of 51 cases) and 10 test data (20% of 51 cases) accuracy is 90%. (b) The results of testing of the old cases in the case base obtained 100% accuracy of the system.—Penalaran Berbasis Kasus menghasilkan solusi berdasarkan kemiripan terhadap kasus-kasus yang pernah terjadi sebelumnya. Solusi kasus baru dihasilkan dari pencocokan kemiripan dengan kasus lama. Pada penelitian ini penulis menerapkan CBR untuk mendignosa penyakit tuberkulosa. Sumber pengetahuan sistem diperoleh dengan mengumpulkan berkas rekam medis pasien tuberkulosis pada tahun 2014-2016. Perhitungan nilai kemiripan menggunakan algoritma K-Nearest Neighbor dengan nilai batas kewajaran 80%. Sistem ini dapat mendiagnosis 3 jenis penyakit tuberkulosis berdasarkan 25 gejala yang ada. Luaran sistem berupa jenis penyakit tuberkulosis berdasarkan gejala yang dialami pasien, solusi pengobatan dan presentasi kemiripan antara kasus baru dan kasus lama. Berdasarkan hasil pengujian dengan 51 kasus TB didapatkan hasil: (a) pengujian dengan 3 skenario pengujian kasus baru didapatkan keakuratan sistem masing-masing untuk skenario pertama akurasi yang diperoleh dengan 31 data latih (60% dari 51 kasus) dan 20 data uji (40% dari 51 kasus) akurasinya sebesar 63%, skenario kedua akurasi yang diperoleh dengan 35 data latih (70% dari 51 kasus) dan 16 data uji (30% dari 51 kasus) akurasinya sebesar 69.2% dan skenario ketiga akurasi yg diperoleh dengan 41 data latih (80% dari 51 kasus) dan 10 data uji (20% dari 51 kasus) akurasinya sebesar 90%, (b) hasil pengujian terhadap kasus lama dalam basis kasus didapatkan keakuratan sistemsebesar 100%