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All Journal Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer
Linda Perdana Wanti
Politeknik Negeri Cilacap, Cilacap
Computer Science & IT

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Optimation Hybrid Model in Selecting Banks for Housing Loans Linda Perdana Wanti
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 3 No. 6 (2023): Juni 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v3i6.835

Abstract

Public housing loans (KPR) have so far become an alternative solution to the problem of the people who wish to have a house but do not have sufficient funds to buy or build it. The obstacle people often faced is finding the best bank from various sides to finance the housing loans. The concept of Islamic banks has recently become a quite reliable competitor for conventional banks in financing KPR. Its presence needs to be taken into account in terms of which bank people chooses to finance KPR, whether with conventional banks or Islamic banks. The research aims to provide alternative decisions for people who look for housing and intend to use public housing credit facilities by optimizing two methods of decision making. Some banks have become alternatives used as a comparison to each other. The alternatives used have their respective characteristics along with its advantages and disadvantages. Decision making methods used are analytical hierarchy process (AHP) and weighted product (WP) methods. Both of these methods are optimized to get banks that have the highest preference weights. The system development method used is user-centered design that captures all the needs of the end user. The parameters used in the selection of banks used for mortgages are the types of banks which consist of two types, namely conventional banks and Islamic banks, interest given by each type of bank, developers working with the bank, administration fees charged by the bank, contract and settlement based on the type of bank, and the last is the duration of the process which is calculated from the start of the contract agreement until the house is ready for occupancy. The output of this study is the weighting result using two methods as an alternative, in which the highest weight used as the best bank solution to finance the KPR. The most effective decision is obtained, namely BTN as a bank that is eligible to finance KPR with the highest preference weight of 14,969.
The Certainty Factor Method in An Expert System for Tuberculosis Disease Diagnosis Dimas Maulana Dwi Kumara; Linda Perdana Wanti; Riyadi Purwanto
Bulletin of Computer Science Research Vol. 5 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i4.549

Abstract

Tuberculosis is an infection caused by acid-fast bacilli (AFB) and is an infectious disease that can attack anyone through the air. This disease is hazardous and chronic, with a high prevalence among individuals aged 15-35 years. The diagnosis of tuberculosis traditionally takes a long time because it involves an interview process by medical experts and testing sputum samples in the laboratory to determine whether the patient is positive or negative for this disease. This process is not only time-consuming but also requires significant resources. To overcome this problem and speed up the diagnosis process, a technology-based approach is needed, namely the Expert System with the certainty factor method. This method can handle uncertainty in medical diagnosis by providing a certainty value for each observed symptom. This article discusses in depth the application of the certainty factor method in an expert system to diagnose Tuberculosis. By using this method, the system can provide faster and more accurate diagnosis results in diagnosing tuberculosis with a confidence level of 94.6% and reduce the workload of medical personnel. The application of the certainty factor method allows the integration of various symptoms and relevant medical data to produce more precise and reliable diagnostic conclusions.
Co-Authors Dimas Maulana Dwi Kumara Riyadi Purwanto