Among the chronic nervous system diseases, Parkinson's disease (PD) is known for its progressiveness in impairing the speech ability, gait as well as complex muscle and nerve actions. Hence an early diagnosis of PD will help in reducing the symptoms. Telemedicine offers a cost-effective and convenient approach, and several studies have used dysphonic features to remotely detect PD. In this study, we have used a data set from Kaggle, which included voice measurements from 31 people of whom 23 were diagnosed with PD. The data set included 22 different attributes pertaining to voice measurements, including the pitch period entropy with 195 voice recordings for each of the individuals. In the data pre-processing, the correlated attributes were removed and we used 10 non-correlating attributes (< 0.7) along with individual status (0 and 1 for healthy and PD, respectively). The data set after preprocessing was split into 70:30 ratio and also ascertained that the number normal versus PD are in equal ratios in both the training and testing data sets, respectively. The data set was evaluated with four different supervised classification machine learning (ML) models, namely random forest, XGBoost, SVM and decision tree. The XGBoost classifier model was found to be highly efficient in precise classification of PD with an accuracy of 0.93.

Database design is a data design process that is used to support the operational activities and goals of organizations and agencies. The use of databases on the geographic information system of residents' lands makes it possible to store, change, and display all data quickly and easily. One of the factors that become a problem in database design is the point of view of seeing data that varies between designers, programmers, and end-users. Therefore we need a methodology in good database design by applying procedures, techniques, tools, and documentation. The method used in this study used the Research and Development (R&D) method, while the database design method used the Database Life Cycle (DBLC) method. The research variables were database design for the geographic information system of resident land with a relational data model. Research aspects include conceptual design, logical design, and physical design. The final result of this research is to produce 10 types of conceptual entities, produce a relationship diagram of the ten logical entities, and produce a physical design consisting of user_admin, user_pengguna, data_desa, data_kecamatan, data_kabupaten, jenis_tanah, data_penduduk, data_buku_c, data_mutasi, and data_sppt tables.

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