Judul: Rancang Bangun Alat Ukur Kadar Gula Darah Non-Invasive Berbasis Sensor Fotodioda
Abstrak: A non-invasive blood glucose meter has been invented before by using light dependent resistor (LDR) as its sensor. This glucose meter has not generating accurate data because LDR is susceptible to noise. Photodiode sensor has more specific wavelength spectral response than LDR, so it can be more resistant to noise. The purpose of this study are to design a non-invasive glucose meter by using photodiode as its sensor and test it on blood glucose variations. The main component of this tool are photodiode sensor, signal conditioning circuits, and microcontroller ATmega328P. This tool is tested by measuring blood glucose level and seeing its correlation with the output voltage from the circuit. The result showed that the light intensity as represented by output voltage, will actually changed when the value of blood glucose changed, following polinomial equation y = 0,0014 x2 - 0,6652 x + 139,34. Coefficient of correlation R2 = 0,9544 showed that x has a real effect toward y, so it can be concluded that photodiode has been functioning properly as non-invasive blood glucose meter’s sensor. The accuration and precision value of this glucose meter are 98,92% and 97,41%.
Keyword: Bogor Agricultural University (IPB), photodiode, non-invasive, blood glucose levels

Judul: Kalibrasi Alat Ukur Kadar Glukosa Darah Non-Invasive Berbasis Raspberry Pi
Abstrak: Glukosa darah menjadi parameter dalam kesehatan sebagai pendeteksi penyakit diabetes melitus. Bagi penderita DM, pengukuran glukosa darah sangat penting untuk memantau status glikemik. Namun saat ini rata-rata pengukuran kadar glukosa darah masih menggunakan teknik invasive (mengambil sampel darah dari pasien), yang bisa saja menyebabkan trauma. Sehingga dibutuhkan alat yang mampu bekerja secara non-invasive yang sudah terkalibrasi dengan baik. Berdasarkan hal tersebut, penelitian ini bertujuan untuk meng-upgrade dan mengetahui tingkat akurasi alat ukur kadar glukosa darah non-invasive berbasis Raspberry Pi hasil upgrade penelitian sebelumnya. Penelitian ini memanfaatkan prinsip reflektansi, dimana LED pada probe menembakkan cahaya. Selanjutnya sensor membaca tegangan yang diterima photodiode, yang kemudian dikonversi menjadi data digital oleh ADS1115. Data yang didapatkan kemudian diolah menggunakan regresi linear berganda untuk mendapatkan persamaan. Persamaan ini yang kemudian dimasukkan pada alat, guna proses kalibrasi. Didapatkan nilai Root Mean Squared Error (RMSE) sebesar 7,836, menandakan akurasi yang baik dengan toleransi kesalahan < 10 berdasarkan standar ISO 15197:2013., Blood glucose is a parameter in health as a detector for diabetes mellitus. For people with DM, blood glucose measurement is very important to monitor glycemic status. However, currently the average blood glucose level measurement is still using invasive techniques (taking blood samples from patients), which can cause trauma. So we need a tool that is able to work non-invasively that is well calibrated. Based on this, this study aims to upgrade and determine the level of accuracy of non-invasive blood glucose level measuring devices based on Raspberry Pi, the results of previous research upgrades. This research utilizes the reflectance principle, where the LED on the probe shoots light. Furthermore, the sensor reads the voltage received by the photodiode, which is then converted into digital data by ADS1115. The data obtained were then processed using multiple linear regression to obtain the equation. This equation is then entered in the tool, for the calibration process. The Root Mean Squared Error (RMSE) value is 7,836, indicating good accuracy with an error tolerance < 10 based on ISO standards 15197:2013.
Keyword: blood glucose, non-invasive, Raspberry Pi

Judul: Posisi Filogenetik Kura-Kura Carettochelys Insculpta  (Reptillia: Testudinata)
Abstrak: Carettochelys insculpta is an endemic freshwater turtle of southern Papua and northern Australia. Phylogenetic position of this turtle is remain unresolved until now. Most of the research conducted show close relationships of C. insculpta and members of Trionychidae family. However, some of the research show distance between C. insculpta and members of Trionychidae family. This research is conducted to analyze phylogenetic relationship between C. insculpta and other members of Testudinata using 12S rRNA, 16S rRNA, and both gene as markers. DNA samples were obtained from three different organisms of C. insculpta. Two species used as outgroups were Alligator mississippiensis and Iguana iguana. Phylogenetic analysis was carried out using Neighbor-Joining method with Felsenstein 1981 (F81) modeltest. A polytomy tree of Testudinata was produced by using 12S rRNA gene. However, analysis using 16S rRNA and both genes as markers confirmed that C. insculpta was located between the Chelonidae and the Trionychidae family.
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