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Abstrak :
Prevalensi gejala depresi pada orang dengan demensia ODD berkisar 30-50 . Hal ini menandakan bahwa pada sebagian besar ODD gejala depresi timbul beriringan dengan penurunan kognitif. Beberapa penelitian mengemukakan bahwa gejala depresi pada demensia timbul karena ODD kehilangan kemandirian dalam beraktivitas sehari-hari serta melupakan banyak hal esensial dalam hidup, seperti nama keluarga dan kerabat, terutama pada ODD dengan tingkat pendidikan yang tinggi. Penelitian ini ingin melihat apakah terdapat korelasi antara skor gejala depresi dan skor kognitif global dengan memeriksa 42 ODD menggunakan Montgomery-Asberg Depression Rating Scale MADRS untuk menilai skor gejala depresi dan Mini Mental State Examination MMSE untuk menilai skor kognitif global. Pada penelitian ini ODD yang digunakan sebagai subjek penelitian dibatasi, yaitu hanya ODD dengan rentang skor MMSE 17-23 gangguan kognitif ringan dan MADRS.

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T is estimated that 30 50 of people with dementia PWD suffer from significant depression. This fact marks that in most PWD, depression occurs at the same time with cognitive decline. Several researches explain that this happens because PWD cannot run their daily activities independently and forgot many essential things, such as family. It is also known that depression occurs more in highly educated people. Therefore, this research is made with the intention to find the correlation between the depression score and global cognitive score in 42 PWD using Montgomery Asberg Depression Rating Scale MADRS to assess the symptoms of depression and Mini Mental State Examination MMSE to assess te global cognitive score. PWD that are included in this research restricted only they who had MMSE score between 17 and 23 mild cognitive impairment , and MADRS score below 34 no depression, mild depression, and moderate depression . Of 42 subjects, depression occurred in 41 97,6 of 42 subjects and the global cognitive score mean is 19,53. Depression score has a strong correlation with global cognitive score r 0,647, p

Abstrak :
ABSTRAK
Gangguan kognitif ringan merupakan gejala awal dari perkembangan penyakit demensia yang dapat dicegah dan diperbaiki. Deteksi MCI menggunakan bantuan informan memiliki kelebihan dibandingkan pemeriksaan langsung ke lansia. Salah satu pemeriksaan berdasarkan informan adalah IQCODE-S. Tujuan dari penelitian ini untuk melakukan adaptasi lintas budaya, uji validitas dan reliabilitas IQCODE-S Bahasa Indonesia.Metode Penelitian. Penelitian dibagi menjadi 2 tahap. Tahap pertama meliputi adaptasi lintas budaya berdasarkan ketentuan World Health Organization WHO , dilanjutkan uji validitas interna, reliabilitas interna dan reliabilitas test-retest pada 30 pasien epilepsi yang memenuhi kriteria inklusi. Tahap kedua adalah uji diagnostik. Hasil IQCODE-S dengan titik potong ge;3,19 dibandingkan dengan pemeriksaan neuropsikologi sebagai baku emas.Hasil. Kuesioner IQCODE-S versi bahasa Indonesia didapatkan melalui proses adaptasi lintas budaya menurut WHO. Hasil uji validitas interna dengan korelasi Spearman didapatkan koefisien korelasi 0,382 hingga 0,778. Uji reliabilitas konsistensi interna dengan Cronbach rsquo;s Alpha 0,854. Perbedaan nilai koefisien korelasi dan Cronbach rsquo;s Alpha antara pemeriksaan pertama dan retest menunjukkan reliabilitas test-retest yang baik. Dari 63 subyek uji diagnostik, proporsi MCI hasil pemeriksaan neuropsikologi sebanyak 87,3 . Dengan titik potong ge;3,19, IQCODE-S memiliki sensitivitas 76,4 dan spesifisitas 87,5 . Kesimpulan. Kuesioner IQCODE-S versi Indonesia terbukti valid dan reliabel sehingga dapat digunakan untuk menapis MCI. Dengan titik potong ge;3,19, IQCODE-S memiliki nilai akurasi yang tinggi tapi belum dapat menjadi alat skrining MCI di komunitas.Kata Kunci. MCI, IQCODE-S versi Indonesia, uji validitas dan reliabilitas, uji diagnostik.

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ABSTRACT
Mild cognitive impairment MCI is the most early clinical symptom from the progression stage of dementia which this stage can be prevented or fixed. Detection of MCI by using informant based report has many advantages compared with objective screening test. One of informant based tools is Informant Questionnaire on Cognitive Decline in the Elderly short version IQCODE S . The aim of this study is to develop transcultural adaptation, validity and reliability test and diagnostic test with neuropsychological test of the IQCODE S.Method. The study was conducted in two phases. The first phase included transcultural adaptation based on World Health Organization WHO standards, followed by internal validity test, internal reliability test and test retest in 30 elderly patients within their informants who fulfill the inclusion criteria. The second phase was diagnostic test, in which, IQCODE S, with cut off point ge 3,19,will be compared with Neuropsychological test as the gold standard examination for diagnosing MCI.Results. The Indonesian version of IQCODE S was obtained by transcultural adaptation based on WHO standards. Internal validity test with Spearman correlation obtained the correlation coefficient 0.38 to 0.778 Internal consistency reliability test with Cronbach rsquo s Alpha was 0.854. The difference of correlation coefficient and Cronbach rsquo s Alpha between the first and the retest showed good test retest reliability. Out of 63 of subjects of diagnostic test, the proportion of MCI using neuropsychological test was 87.3 . With cut off point 3,19, IQCODE S had sensitivity rate of 76,4 and specificity 87,5 .Conclusion. The Indonesian version of the the IQCODE S was proven to be valid and reliable, also was found to be accurate but there should be cut off point determination as screening test so sensitivity could be higher than specificity. Keywords. MCI, IQCODE S Indonesian version, validity and reliability test, diagnostic test.

Abstrak :
Demensia adalah suatu istilah umum yang menggambarkan penurunan kemampuan mengingat yang cukup parah. Demensia paling umum disebabkan oleh alzheimer yang mana diagnosisnya seringkali sulit dan telat dilakukan. Padahal, pada tahap demensia sangat ringan merupakan tahap yang paling efektif dilakukan. Oleh karena itu, akan menjadi suatu keuntungan yang sangat besar apabila berhasil mendiagnosis pada tahap awal. Pendekatan paling populer untuk melakukan diagnosis pada demensia adalah dengan machine learning yang kemudian diperdalam kembali dengan deep learning. Sudah banyak arsitektur pada deep learning, di mana yang paling terkenal digunakan untuk klasifikasi berbentuk gambar adalah Convolutional Neural Network (CNN). Salah satu contoh turunan dari CNN adalah VGG di mana pertama kali diusulkan oleh tim dari Universitas Oxford. Pendekatan dengan arsitektur VGG dilakukan dalam skripsi ini, di mana menggunakan VGG-16 dan VGG-19. Hasil dari skripsi ini berhasil mendeteksi 4 kelas (sangat ringan, ringan, cukup, dan orang normal) dengan capaian akurasi di atas 89% untuk seluruh skenario, bahkan beberapa sampai 99%. Nilai akurasi tertinggi tercatat mencapai 99.68% untuk training dan 99.36% untuk validasi. Tidak hanya akurasi, pada skripsi ini juga akan menganalisis berdasar confusion matrix, presisi, recall, dan F1 Score sehingga bisa lebih mendalam analisis pendeteksiannya untuk tiap kelasnya. ......Dementia is a general term that describes a severe impairment of memory. Dementia is most commonly caused by Alzheimer's and diagnosis is often difficult and late. In fact, the very mild stage of dementia is the most effective stage to do. Therefore, it will be a huge advantage if the diagnosis is successful at an early stage. The most popular approach to diagnosing dementia is machine learning which is then deepened by deep learning. There have been many architectures in deep learning, where the most well-known being used for image classification is the Convolutional Neural Network (CNN). One example of a derivative from CNN is VGG which was first proposed by a team from the University of Oxford. Approach to the VGG architecture is carried out in this thesis, which uses VGG-16 and VGG-19. The results of this thesis have successfully detected 4 classes (very light, light, moderate, and normal people) with accuracy above 89% for all scenarios, even some up to 99%. The highest accuracy value was recorded at 99.68% for training and 99.36% for validation. Not only accuracy, but this thesis will also analyze based on confusion matrix, precision, recall, and F1 Score so that the detection analysis can be more in-depth for each class.

Abstrak :
This book provides a comprehensive collection for experts in the Neuroscience and Biomedical technology fields, outlining various concepts from cognitive neuroscience and dementia to neural technology and rehabilitation--Provided by publisher.