Judul: Identifikasi Faktor yang Memengaruhi Layanan Rujuk Lanjutan Menggunakan Regresi Logistik Group LASSO
Abstrak: Health is a very important need in life and is a human right to be able to live a decent, productive, and prosper life. For its importance in everyday life, it is necessary to have good health providers as stated in the 1945 Constitution of the Republic of Indonesia Article 28 H paragraphs 1 and 3. The government has made a program run by BPJS Kesehatan, namely the National Health Insurance which aims to improve access and quality of health services in order to achieve optimal welfare degrees effectively and efficiently. With the existence of the National Health Insurance, it is hoped that health services will no longer be centered in hospitals or FKRTL but will be carried out in stages according to medical needs. The high referral ratio is caused by the implementation of referrals that are not in accordance with the level flow, which will cause an accumulation of patients in one hospital, so that it has an impact on the decline in service quality. The high ratio of referral rates is a problem in implementing a tiered referral system, so it is necessary to find out what factors affecting the referral status of FKTP patients to FKRTL. The response variable used in this study was the patient's referral status of First Level Health Facilities (FKTP) whether or not including further referral to Advanced Referral Health Facilities (FKRTL). If the response variable is no longer a quantitative variable, but a categorical variable consisting of only a few values, then linear regression cannot be used. In high-dimensional data, the response variable is related to a small number of explanatory variables among a large number of possible variables. Thus, the selection of variables is important to do in identifying the relevant variables in high-dimensional data. One alternative method to deal with this case, the penalized logistic regression method was developed. Coefficient estimators in penalized logistic regression are carried out by maximizing the log of the probability function by adding a penalty to the function which causes the coefficient estimator to be biased, but reducing the variance of the coefficient estimator will increase the accuracy of the model prediction (Hastie et al. 2008). Therefore, penalized logistic regression is often referred to as the shrinking or regularization method. In this study, the LASSO Group regularization method was used because the explanatory variables in the research data were in the form of groups. Group LASSO is an extension of the LASSO method by adding group penalties to the LASSO method. To find out what factors affecting the patient's referral status to FKRTL, logistic regression is used, in which the response variable is -1 for outpatient treatment, recovery, internal referral, forced discharge, others; death and 1 for further referral to FKRTL, following the Bernoulli distribution. The covariates included in the process of variables are age, family relationship, gender, marital status, class of treatment, segment of participants, ownership of health facilities, type of health facility, type of health facility, and level of service. Dummy/dummy variables are variables used to quantify qualitative variables such as in this study,
Keyword: group LASSO, healthcare utilization, variable selection

Judul: Model regresi logistik untuk kejadian infeksi luka operasi nosokomial
Abstrak: Indonesia. Masalah infeksi luka operasi pada tahun terakhir ini telah menjadi topik pembicaraan di banyak negara. Telah diketahui bahwa pengelolaan ILO menimbulkan biaya tinggi, baik yang ditanggung pihak penderita maupun pihak rumah sakit. Infeksi luka operasi tidak dapat ditekan sampai 0 %. Salah satu cara untuk menekan angka kejadian ILO adalah dengan menerapkan tindakan asepsis dan membiasakan para petugas berperilaku higienis. Cara lain adalah dengan mengurangi faktor-faktor yang dapat meningkatkan resiko terjadinya infeksi luka operasi. Penelitian ini bertujuan untuk melihat faktor-faktor yang dapat meningkatkan resiko terjadi ILO. Hasil dari penelitian ini menemukan dua faktor yang memegang peranan penting dalam mempengaruhi kejadian infeksi luka operasi, yaitu :1)Faktor Endogen merupakan faktor yang ada di dalam penderita sendiri seperti umur, jenis kelamin, penyakit predisposisi ILO, dan operasi dahulu. 2)Faktor Eksogen merupakan faktor di luar penderita, seperti lama penderita dirawat di rumah sakit, tingkat kebersihan luka, keteraturan penggunaan antibiotika, lama antibiotika pasca bedah, lama operasi, dan jumlah personil di kamar operasi. Model Regresi Logistik untuk mengidentifikasi resiko kejadian infeksi luka operasi adalah sebagai berikut : 1 ( ) ( ) ˆ ( ) eg x e g x x + p = Sedangkan g(x) = -2.346 – 0.411sexs – 0.008umur + 0.492OPRSIseb – 0.482TimOPRS_1 – 0.194 TimOPRS_2 + 1.036KtratAP + 0.002 LamaOPRS + 0.427BershLuka_1 + 1.994 BershLuka_2 + 1.938 BershLuka_3 + 0.742PredILO + 0.037LmRwtPost + 0.065LmABPost.
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Judul: Embriogenesis ikan buta (Astyanax fasciatus)
Abstrak: Ikan buta Astyanax fasciatus adalah spesies ikan unik dari famili Characidae yang menempati perairan dalam gua di Wilayah La Cueva Chica-San Luis Potasi-Mexico. Ikan ini memiliki mata yang tereduksi (Blind Cavefish) dan warna kulit merah muda, pucat serta mengkilap.
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