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ADA Journal of Information System Research
Published by ADA Research Center
ISSN : -     EISSN : 30259568     DOI : -
Core Subject : Science,
Computer Science & IT
ADA Journal of Information System Research publishes manuscripts within the fields of: 1. Big Data, 2. Informatics Techniques, 3. Data Mining 4. Decision Support System, 5. Experts System, and 6. Cryptography 7. Information System
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 5 Documents
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Search results for , issue "Vol. 1 No. 3 (2024): June 2024" : 5 Documents clear
Penerapan Algoritma K-Means Clustering Untuk Klasterisasi Penyakit Pasien Lingga, Alpazri
ADA Journal of Information System Research Vol. 1 No. 3 (2024): June 2024
Publisher : ADA Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64366/adajisr.v1i3.43

Abstract

Rs. Subulussalam City, is the centre of the regional general hospital of Subulussalam city Aceh which is already known and trusted by the local community. Various types of patient diseases that exist in this public hospital, therefore, the purpose of this study is to cluster patients at Rs. Kota Subulussalam, with the problems that are happening in the hospital, namely data retrieval. Subulussalam City, with the problems that are happening in the hospital, namely searching for patient data and also in predicting the level of the number of patients in the Subulussalam city hospital. So that employees and management at the hospital, have difficulty in classifying patient data. Based on the above problems, a patient clustering system was carried out using the K-Means Algorithm. The clustering process is divided into three categories namely self care, intermediate care and total care.With the clustering of patients can determine the number and type of staff needed and determine the value of productivity so that the number of nurses with patient needs can be balanced. By using the K-Means Clustering algorithm, the author will cluster the patient disease data of the subulussalam city public hospital, with the hope that this algorithm can be a solution to the problem so far, so that it will facilitate the parties involved in the development of the clustering that the author compiled. The final result of the application of the K-Means method is that the residents diagnosed with Lung TB are 4 people, while Tbc is 5 people and Hiv Aids is 6 people.
Implementasi Algoritma Lucifer untuk Autentikasi Sound Chat Ade Sani Afrianda
ADA Journal of Information System Research Vol. 1 No. 3 (2024): June 2024
Publisher : ADA Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64366/adajisr.v1i3.44

Abstract

Voice chat is one of the ways used to send a message through a chat application, where voice chat contains messages in the form of voice. There are problems in the process of sending voice chats, where in the delivery process there can be damage or manipulation of sound that can be done by parties who are not involved in the voice chat. In this case, security is needed to maintain the authenticity of the chat voice to avoid damage or what can be done by non-existent parties. Cryptographic techniques can be used to maintain the authenticity of voice chats with encryption and decryption processes so that they can minimize damage or damage to voice chats that can be done by parties who do not. The lucifer algorithm is an algorithm that can perform cryptographic techniques, where the lucifer algorithm encrypts data that has been divided into blocks. This study uses the lucifer algorithm for the encryption and decryption process. A voice chat will be encrypted using the lucifer algorithm to produce ciphersound. This process can increase the security and authenticity of the chat voice in the sending process and will not arouse suspicion from other parties who are not responsible for knowing the authenticity of the chat voice.
Analisa Perbandingan Metode Certainly Faktor – Naive Bayes Terhadap Diagnose Penyakit Pneumonia Zalukhu, Erniwati
ADA Journal of Information System Research Vol. 1 No. 3 (2024): June 2024
Publisher : ADA Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64366/adajisr.v1i3.49

Abstract

The development of science and technology is increasing rapidly, along with the progress of the times. Technology is becoming increasingly sophisticated and plays an important role in every aspect of life. currently growing rapidly. One disease that often attacks humans is pneumonia. Pneumonia is one of the diseases handled by the Estomihi Hospital on Jl. Sisingamangaraja No. 235 Kec. Medan City, Medan City. Pneumonia is a disease caused by viral bacteria and infects the respiratory tract. Diagnosis of pneumonia by using the certainty factor and naive Bayes methods is part of the expert system method which has a different way of working, resulting in a different percentage of confidence in the information. Given these differences, it is necessary to have an analysis that compares these two expert system methods to find and determine the best decision in diagnosing pneumonia. The percentage of Combination CF Value is only 55% while the percentage of Bayes Value is 67.6%.
Sistem Pakar Diagnosa Distrofi Otot Berbasis Web Menerapkan Metode Tsukamoto Zalukhu, Ishak
ADA Journal of Information System Research Vol. 1 No. 3 (2024): June 2024
Publisher : ADA Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64366/adajisr.v1i3.50

Abstract

Muscular dystrophy is a group of diseases that cause muscles to become weak, lose mass, and lose function. A common problem that occurs in the general public is the difficulty of knowing the diagnosis of muscular dystrophy in the body based on the symptoms experienced due to the limited number of specialist doctor consultation services in the neighborhood where they live. Overcoming the problem of difficulty in knowing the diagnosis of muscular dystrophy that has been described above, in this study the authors built a web-based expert system for diagnosis of muscular dystrophy using the Tsukamoto method. If a patient with a severity status of exactly 5 is given a diagnosis of moderate severity muscular dystrophy. The results of this study indicate that the application of the Tsukamoto method in the process of diagnosing Muscular Dystrophy gives effective results to solve the problem of diagnosing Muscular Dystrophy in accordance with expert knowledge.
Sistem Pendukung Keputusan Penentuan Penerima Bantuan Langsung Tunai (BLT) dengan Kombinasi Metode Clustering K-Means dan Visekriterijumsko Kompromisno Rangiranje (VIKOR) Reza Ariansyah
ADA Journal of Information System Research Vol. 1 No. 3 (2024): June 2024
Publisher : ADA Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64366/adajisr.v1i3.51

Abstract

Virus Certification of Vaccination Identification by Artificial Intelligence, which is often called the Corona virus, has greatly affected the economy of the world community, especially the economy of the people in Indonesia, for this reason the Indonesian government is taking appropriate steps that are useful for improving the economic problems of the Indonesian people by providing direct cash assistance or often referred to as BLT. . The main goal is to help the economy of communities affected by the impact of the Corona virus. The system for determining direct cash assistance at the Kubah Sentang village office, Pantai Labu District, still uses a simple method. Of course, with this simple system, it is very possible for errors to occur with inaccurate data or direct cash assistance not being on target. The mistake that often occurs is that there are people who do not deserve direct cash assistance but these people receive direct cash assistance. In the decision support system for determining direct cash assistance using the K-Means Clustering method, it is used to partition or divide an object into a cluster subset and the Visekterijumsko Kompromisno Rangiranje (VIKOR) method is useful for getting rankings against the criteria that will be used, as for what happens after using the K-Means Clustering method, the data sample starts with 35 people, with this method grouped into 15 people. Then the Visekterijumsko Kompromisno Rangiranje (VIKOR) method was used for ranking, so from the previous method the data amounted to 15 people. Using the VIKOR method, only 5 people were found who were considered very worthy in determining direct cash assistance (BLT).

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