Klasifikasi Kelas Risiko Paien Pneumonia Menggunakan Metode Hybrid Analisis Diskriminan Linier-Particle Swarm Optimization (ADL-PSO) dan Naive Bayes Classification

sehingga penyebaran penyakit ini tergolong sangat cepat. Oleh karena itu diagnosa yang cepat dan tepat sangat diperlukan agar dapat menentukan penanganan dan perawatan yang tepat. Beberapa penilaian kelas risiko pneumonia dikembangkan untuk mempermudah diagnosis pneumonia. Terdapat berbagai sistem skoring PSI, CURB-65, modified ATS (m-ATS) dan sebagainya untuk menentukan kelas risiko pasien pneumonia, akan tetapi tidak ada patokan pasti untuk menentukan sistem apa yang harus digunakan untuk mengelompokan kelas risiko pneumonia. Oleh karena itu diperlukan studi klasifikasi untuk mengkaji variabel-variabel yang diapat digunakan untuk mengelompokan kelas risiko pneumonia secara tepat. Penelitian ini menerapkan metode Analisis Diskriminan Linier dengan seleksi variabel forward selection, backward elimination dan stepwise method, Hybrid Analisis Diskriminan Linier-Particle Swarm Optimization (ADL-PSO) dan Naïve Bayes untuk mengklasifikasikan kelompok kelas risiko pneumonia berdasarkan data rekam medis pasien kemudian ketiga metode klasifikasi tersebut dibandingkan nilai akurasinya. Hasil penelitian menunjukan bahwa metode klasifikasi terbaik adalah ADL-PSO. ========================================================================================= Pneuomonia is a disease that is transmitted through the air so that the spread of this disease is very fast. Therefore a fast and precise diagnosis is necessary in order to determine appropriate treatment and care. Several scoring assessments of pneumonia were developed to facilitate the diagnosis of pneumonia. There are PSI scoring systems, CURB-65, modified ATS (m-ATS) and so on to determine the risk class of pneumonia patients, but there is no definite benchmark to determine what system should be used to classify the risk class of pneumonia. Therefore, a classification study is needed to assess the variables used to correctly classify the risk of pneumonia. This research applies Linear Discriminant Analysis method with selection of forward selection, backward elimination and stepwise method, Hybrid Linear Discriminant Analysis-Particle Swarm Optimization (LDA-PSO) and Naïve Bayes to classify pneumonia risk class group based on patient medical record data then all classification methods are compared the value of its accuracy. The results showed that the best classification method is LDA-PSO

Comparisons of Logistic Regression and Support Vector Machines in Classification of Echocardiogram Dataset

Echocardiography is a test that uses sound waves to produce an image of our heart. This image is called an echocardiogram. This paper uses Echocardiogram Dataset, in which the problem is to classify from 7 features whether the patient will survive or not. In this study, the classification method is used to solve this problem. Some classification methods can be applied to classify category response variables, such as Logistic regression and Support Vector Machines (SVM). The method for predicting best accuracy used holdout and cross-validation. Before doing classification, some preprocessing procedures were applied to this dataset. The preprocessing procedures include missing value imputation using median imputation, outliers detection in univariate and multivariate procedures, and feature selection using the backward method. The result of classification in the analysis showed that SVM with unstratified holdout gave the best accuracy, that is 91.54%

PENGUATAN KAPASITAS PEREMPUAN MELALUI KEWIRAUSAAN ECOPRINT

ABSTRAKAdanya kewajiban dosen (Perguruan Tinggi) untuk pengabdian kepada masyarakat, KKN mahasiswa  , serta Program pemerintah kota  Surabaya untuk pengentasan Masyarakat Berpenghasilan Rendah (MBR), merupakan tantangan bagi Perguruan Tinggi untuk berpartisiasi.  Di sisi lain, salah satu kerajinan yang sedang booming adalah ecoprint.  Beberapa alasannya adalah : (i) proses produksi tidak terlalu sulit, tidak sesulit membatik, serta (ii) di wilayah Kelurahan Keputih kaya akan tanaman yang daunnya dapat digunakan untuk produksi ecoprint. Tim Pengabdian Masyarakat  ITS menggandeng UMKM Sinawa Ecoprint dan Any’s Art & Craft untuk memberdayakan ibu-ibu rumah tangga (pemberdayaan Wanita) warga Kelurahan Keputih, khususnya Masyarakat Berpenghasilan Rendah.  Kegiatan ini meliputi pelatihan produksi ecoprint, dilanjutkan  dengan mengadopsi konsep sistem intiplasma, UMKM Sinawa Ecoprint dan Any’s Art & Craft sebagai inti yang akan menyediakan sarana produksi, menampung dan memasarkan hasil kerajinan ecoprint  ibu-ibu rumah tangga warga Keputih, secara berkelanjutan. Setelah  ibu-ibu rumah tangga terampil menghasilkan  ecoprint, mereka  dapat mejual hasil ecoprint,  sehingga mendapatkan  tambahan penghasilan bagi keluarga. Selain itu, dampak kegiatan ini diharapkan turut serta berperan dalam upaya PEMKOT Surabaya untuk pengentasan kemiskinan melalui pemberdayaan wanita. Kata Kunci : pemberdayaan wanita; ecoprint; inti-plasma; berkelanjutan; MBR ABSTRACTThe existence of the obligation of lecturers (Universities) for community service, student community service activities (KKN), and the Surabaya city government program for alleviating Low-Income Communities (MBR), is a challenge for universities to participate. On the other hand, one of the booming crafts is ecoprint. Some of the reasons are: (i) the production process is not too difficult, not as difficult as batik, and (ii) the Keputih Village area is rich in plants whose leaves can be used for ecoprint production. The ITS Community Service Team collaborates with the Sinawa Ecoprint and Any's Art & Craft SMEs to empower housewives (Women Empowerment) residents of Keputih Village, especially Low-Income Community. This activity includes training on ecoprint production, followed by adopting the concept of the nucleus plasma system, the MSME Sinawa Ecoprint and Any's Art & Craft as the core which will provide production facilities, accommodate and market the ecoprint handicrafts of Keputih housewives, in a sustainable manner. After skilled housewives produce ecoprints, they can sell the ecoprints, thereby earning additional income for the family. In addition, the impact of this activity is expected to play a role in the Surabaya City Government's efforts to alleviate poverty through empowering women. Keywords: women empowerment; ecoprints; nucleus-plasma system; sustainable; low-income communit

Model Evaluation for Logistic Regression and Support Vector Machines in Diabetes Problem

Machine learning is a method or computational algorithm to solve problems based on data that already available from the database. Classification is one of the important methods of supervised learning in machine learning. Support Vector Machine and Logistic Regression are some supervised learning methods that can be used both for classification and regression. In datamining process, Preprocessing is an important part before doing further analysis. In preprocessing data, feature selection and deviding training and testing data are important part of preprocessing data. In this research will be compared some evaluation model of deviding method for training and testing data, namely Random Repeated Holdout, Stratified Repeated Holdout, Random Cross-Validation, and Startified Cross-Validation. Evaluation model would be implying in logistic regression and Support Vector Machines (SVMs). From the analysis, can be concluded that by selecting features can improve the accuracy of classification with logistic regression, but opposite of Support Vector Machines (SVMs). For training and testing data pertition method can not be sure what method is better, because each method of partition training and testing data using the concept of random selection. Model evaluation cannot sure influence to increase best perform for SVMs model in particular this case