Perancangan Monitoring Prestasi Akademik dan Aktivitas Siswa Menggunakan Pendekatan Key Performance Indicator (Studi Kasus SMA N 1 Kalirejo)

Sekolah saat ini adalah prioritas utama bagi pihak orang tua agar anak-anaknya dapat menuntut ilmu dan menjadi anak yang cerdas, pintar dan berbakti kepada orang tua dan dapat membanggakan nama baik keluarga maupun bangsa, namun saat ini kondisi pendidikan yang ada di Indonesia khususnya di tempat pedalaman atau tempat-tempat yang jarang dapat perhatian oleh pemerintah mengalami kemunduran bagi sarana dan prasarana dan kurangnya pemanfaatan teknologi sekarang ini, sehingga harus dilakukan Perubahan agar dapat memanfaaatkannya dengan baik. Metode yang digunakan dalam pemecahan masalah pada penelitian ini adalah metode pengembangan sistem menggunakan metode Waterfall serta perancangan sistem menggunakan UML (Unified Modelling Language): Usecase Diagram, Activity Diagram, Class Diagram, dan Sequence Diagram, sedangkan untuk bahasa pemrograman menggunakan PHP, aplikasinya dreamweaver dan MySQL sebagai database Monitoring.Perancangan Monitoring prestasi akademik dan aktifitas siswa berbasis web dapat memudahkan guru, orang tua dalam mengetahui informasi nilai si anak dengan cara membuka website Perancangan Monitoring Prestasi Akademik dan Aktifitas Siswa

Hypertension, Body Mass Index, and their Associations with Type 2 Diabetes Mellitus in Deli Serdang, North Sumatera

Background: Diabetes mellitus (DM) is a major public health problem world-wide. Current global estimates indicate that this condition affects 415 million people and is set to escalate to 642 million by the year 2040. Type 2 DM is a metabolic disease that occurs due to abnormalities in insulin secretion. This study aimed to analyze the associations of hypertension and body mass index with type 2 DM in Deli Serdang, North Sumatera. Subjects and Methods: This was a case-control study conducted in Deli Serdang, North Sumatera. A sample of 92 patients was selected for this study consisting 46 patients with type 2 DM and 46 patients without type 2 DM. The dependent variable was type 2 DM. The independent variables were hypertension and body mass index. Type 2 DM and hypertension data were obtained from the medical record. The other data were collected by questionnaire. The data were analyzed by multiple logistic regression. Results: Type 2 DM was associated with hypertension (OR= 3.56; p= 0.004) and BMI ≥25 (OR= 5.66; p<0.001). Conclusion: Type 2 DM is associated with hypertension and BMI ≥25. Keywords: type 2 DM, hypertension, body mass inde

Deveploment of Novel Talus Implant Based on Artificial Neural Network Prediction of Talus Morphological Parameters

The design philosophies of current talus implant focus too much on mechanical simplicity and usually based on certain population which tends to ignore the bony geometry difference between populations. Thus, the novel talus implant (NTI) for particular population was developed based on artificial neural network (ANN) prediction of talus morphometrics. By using Finite Element Method (FEM), numerical models that include mainly the talus bone and the talus implants are created to compare the performance of the NTI with the three different kind of current talus implant designs. The study demonstrates that not all current talus implant are perfect match for this particular population. While, the ANN method showed a greater capacity of prediction regarding on the low percentage of error and high correlative values with the measurements obtained through Computer Tomographic (CT) scan. ANN is highly accurate predictive methods and has the potential to be used as assisting tools in designing talus implant. For FEM results, only BOX and NTI exceeded the contact stress recommended for the superior articular surface compared to the others. The results also showed that the stress increased near the resected surface. Thus, it is agreed that excessive bone resection may not support the force at the ankle which consequently may contribute to early loosening and subsidence of the talus implant. It is concluded that the excessive bone resection can be avoided by perfectly match talus implant which only can be achieved by designing talus implant for a particular population

Neural network as an assisting tool in designing talus implant

The design of current talus implant are focusing too much on mechanical simplicity and usually based on certain population which tends to ignore the anatomically difference between populations. An anatomically talus implant design is known can reduce the contact pressure but one of the constraints for designing implant anatomically is to get bone parameters. This is due to the difficulty to get enough volunteers in getting bone parameters using hazardous method (X-ray or CT scan) .Thus, the talus implant (TI) for particular population was developed based on artificial neural network (ANN) prediction. By using Finite Element Method (FEM), numerical models that include mainly the talus bone and the talus implants are created to compare the contact pressure distribution of the newly develop talus implant with the three different kind of current talus implant designs (BOX, STAR & TNK). For FEM results, only BOX and the newly develop talus implant exceeded the contact stress recommended for the superior articular surface compared to the others. The results also showed that the stress increased near the resected surface. Thus, it is agreed that excessive bone resection may not support the force at the ankle which consequently may contribute to early loosening and subsidence of the talus implant. It is concluded that the excessive bone resection can be avoided by perfectly match talus implant which only can be achieved by designing talus implant for a particular population