Diabetes Melitus (DM) tipe 2 merupakan suatu kelompok penyakit metabolik dengan karakteristik hiperglikemia yang terjadi karena resistensi insulin disertai defisiensi insulin relatif. Pemantauan status metabolik pasien DM merupakan hal yang penting. Salah satu metode yang dapat digunakan untuk menentukan pengendalian glukosa darah pada penderita DM adalah pengukuran hemoglobin-glikosilat (HbA1c).Tujuan penelitian ini untuk mengetahui karakteristik penderita DM berdasarkan HbA1c di wilayah kerja Puskesmas Jayabaru Kota Banda Aceh. Penelitian menggunakan desain potong lintang, dan penyajian data secara deskriptif. Sampel berjumlah 85 orang penderita DM tipe 2 di Puskesmas Jayabaru. Data karakteristik responden berupa umur, jenis kelamin, pendidikan serta lama menderita DM didapatkan melalui wawancara, dan nilai HbA1c didapatkan dengan pemeriksaan darah di laboratorium yang terstandarisasi di Kota Banda Aceh. Pada hasil penelitian terlihat bahwa dari 85 penderita DM, 84,7% memiliki nilai HbA1c ≥ 6,5%. Penderita dengan HbA1c ≥ 6,5% sebagian besar perempuan, usia lanjut, pendidikan rendah dan lama menderita DM kurang dari 5 tahun. Untuk mencegah komplikasi lebih lanjut, diperlukan kontrol glikemik melalui pemeriksaan HbA1c secara rutin.

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Most people with diabetes in the world are type 2. We can detect diabetes early to prevent things that are not desirable by checking sugar and insulin levels with the doctor. In addition to using this method, people with diabetes can also be grouped based on data from diabetes examination results. However, most of the data on health examination results have several parameters that are difficult for the public to understand. These problems can be done by means of automatic classification. In addition to these problems, there is another problem in the form of an unbalanced amount of data for diabetics and non-diabetics. This problem can be done by balancing the amount of data using the model to increase the ratio of the amount of data that is small or decrease the ratio of the amount of data that is too much. Purpose: This study aims to detect type 2 diabetes mellitus using the SVM classification model and analyze the results of the comparison using the SMOTE and ADASYN data balancing technique which is the best. Methods/Study design/approach: The research method starts from collecting the diabetes dataset, then the dataset cleaning process is carried out whether there is a null value or not. After applying two oversampling methods to analyze which method is the most appropriate. After the oversampling technique was carried out, data classification was carried out using a support vector machine model to see the accuracy results. Result/Findings: The results obtained by the ADASYN-SVM method are superior to SMOTE-SVM. The ADASYNSVM method has an accuracy of 87.3%, while the SMOTE-SVM has an accuracy of 85.4%. Novelty/Originality/Value: The data used in this study came from the Karya Medika clinic, Indonesia which contains parameters related to type 2 diabetes.

Diabetes is a non-communicable disease that has a death rate of 70% in the world. Majority of diabetes cases, 90-95%, are of diabetes cases are type 2 diabetes which is caused by an unhealthy lifestyle. Type 2 diabetes can be detected earlier by using examination that contains diabetes-related parameters. However, the dataset does not always contain complete information, the distribution between positive and negative classes is mostly imbalanced, and some parameters have low importance to the decision class. To overcome the problems, this study needs to carry out preprocessing to improve detection precision and recall. In this paper, propose an approach on dataset preprocessing, which is applied to diabetes prediction. The preprocessing approach consists of the following process: missing value process, imbalanced data process, feature importance process, and data augmentation process. The data preprocessing process uses the median for missing value, random oversampling for imbalanced data, the Gini score in the random forest for feature importance, and posterior distribution for data augmentation. This research used random forest and logistic regression as classification algorithms. The experimental results show that the classification increased by 20% precision and 24% recall by applying proposed method and random forest method compared to without proposed method and random forest method.

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis that attacks the lungs. The high incidence of Pulmonary TB in Indonesia indicates that action needs to be taken to reduce the transmission rate. The transmission prevention behavior is intended for families and people around who are often in direct contact with sufferers. The purpose of this study was to determine the factors associated with TB transmission prevention measures in Banda Aceh City and Aceh Besar district. This study used a cross-sectional study design involving pulmonary tuberculosis patients aged >15 years. Respondents involved were 262 people who were in the working areas of primary health service center and hospitals in Banda Aceh City and Aceh Besar district. Data on gender, age, education, patient category, Drug Swallowing Supervisor (PMO), regularity of taking medication, seeking treatment, knowledge, attitudes, and behavior towards TB disease were obtained through interviews. Data were analyzed by univariate, bivariate X2 (chi square), and multivariate. The results found that knowledge, attitude, faster treatment seeking regular medication, and high level of education were the most dominant factors influencing TB transmission prevention behaviour. Older age also associated with TB transmission prevention behaviour. TB transmission prevention behavior in TB patients was 53% good. Patients and family members must always be reminded to implement TB prevention and transmission behaviors. Regular visits to the patient’s home can be made by officers to provide education and monitoring of treatment. Abstrak Tuberkulosis (TB) adalah penyakit infeksi yang disebabkan oleh Mycobacterium tuberculosis yang menyerang paru-paru. Tingginya kasus TB Paru di Indonesia menunjukkan bahwa perlu dilakukan tindakan untuk menurunkan angka penularan. Perilaku pencegahan penularan ini ditujukan bagi keluarga dan orang di sekitar yang sering kontak langsung dengan penderita. Tujuan penelitian ini untukmengidentifikasi faktor-faktor yang berhubungan dengan tindakan pencegahan penularan TB pada penderita TB di Kota Banda Aceh dan Kabupaten Aceh Besar. Penelitian ini menggunakan rancangan studi cross-sectional dengan melibatkan penderita TB paru yang berumur >15 tahun. Responden yang terlibat sebanyak 262 orang yang berada di wilayah kerja puskesmas dan rumah sakit di Kota Banda Aceh dan Kabupaten Aceh Besar. Data jenis kelamin, umur, pendidikan, kategori pasien, pengawas menelan obat (PMO), keteraturan menelan obat, pencarian pengobatan, pengetahuan, sikap, dan perilaku terhadap penyakit TB didapatkan melalui wawancara. Data dianalisis secara univariat, bivariat X2 (chi square), dan multivariat. Hasil penelitian didapatkan bahwa pengetahuan, sikap, pencarian pengobatan yang lebih cepat, teratur menelan obat anti tuberkulosis (OAT), dan pendidikan tinggi merupakan faktor yang paling dominan mempengaruhi perilaku pencegahan penularan TB. Umur yang lebih tua juga berhubungan dengan perilaku pencegahan penularan TB. Perilaku pencegahan penularan TB pada pasien TB sebesar 53% baik. Penderita dan anggota keluarga harus selalu diingatkan untuk menerapkan perilaku pencegahan dan penularan TB. Kunjungan berkala ke rumah pasien dapat dilakukan oleh petugas untuk pemberian edukasi dan pemantauan pengobatan.