Abstrak: Uang Nai': Antara Cinta dan Gengsi. Studi ini bertujuan memahami doi menre atau uang Nai' dalam Budaya Panai' Bugis Makassar saat menentukan besaran uang belanja perkawinan Data dianalisis dengan menggunakan pola budaya perkawinan adat masyarakat Bugis yang dikemukakakan oleh Lamallongeng Hasil penelitian menemukan bahwa fenomena tingginya uang Nai', mahar dan sompa dipandang kaum muda Bugis dan orang luar sebagai bentuk harga Lamaran dianggap transaksi antara kedua keluarga calon pengantin Pandangan ini keliru, sebab budaya panai' merupakan bentuk penghargaan budaya Bugis terhadap wanita, siri', prestise dan status sosial Uang nai' merupakan bentuk penghargaan keluarga pihak pria terhadap keluarga wanita karena telah mendidik anak gadisnya dengan baik Diskursus mengenai akuntansi dan budaya bukan hal yang baru (lihat misalnya Randa dan Daromes 2014) dan menjadi penting karena akuntansi harus dipahami sebagai bentukan dari budaya di mana akuntansi tumbuh Artikel ini menelaah bagaimana akuntansi penetapan uang nai' atau harga suatu pernikahan dilandasi oleh nilainilai budaya lokal Budaya Panai' merupakan proses penentuan jumlah uang belanja pesta perkawinan yang berasal dari daerah Provinsi Sulawesi Selatan Budaya ini juga masih kuat dipertahankan oleh sebagian besar orang Bugis-Makassar perantauan Walaupun sudah meninggalkan daerah nenek moyang bertahun-tahun, bahkan telah lahir di daerah perantauan, budaya panai' tetap juga digunakan dalam proses lamaran sebelum pernikahan Budaya ini menimbulkan kegelisahan bagi pihak laki-laki baik dari masyarakat Bugis maupun dari luar masyarakat Bugis berkaitan de ngan mahalnya uang nai' yang akan diberikan oleh pihak keluarga laki-laki Bagi orang tua sederhana yang mempunyai anak laki-laki akan merasa gelisah oleh masalah penda naan yang harus disediakan untuk doi menre Sementara pihak wanita yang menunggu datangnya lamaran dari seorang laki-laki juga akan gelisah karena kekhawatiran tidak adanya laki-laki yang menyanggupi doi menre yang ditetapkan oleh keluarganya Sesuai dengan adat yang berlaku dalam masyarakat Bugis, persyaratan lebih banyak dibebankan kepada pihak laki-laki Hampir seluruh pembiayaan dalam pelaksanaan perkawinan ditanggung oleh pihak laki-laki (Lamallongeng 2007: 6) Pembiayaan terse-

Problem statement:Research on Smooth Support Vector Machine (SSVM) is an active field in data mining. Many researchers developed the method to improve accuracy of the result. This study proposed a new SSVM for classification problems. It is called Multiple Knot Spline SSVM (MKS-SSVM). To evaluate the effectiveness of our method, we carried out an experiment on Pima Indian diabetes dataset. The accuracy of previous results of this data still under 80% so far. Approach: First, theoretical of MKS-SSVM was presented. Then, application of MKS-SSVM and comparison with SSVM in diabetes disease diagnosis were given. Results: Compared to the SSVM, the proposed MKS-SSVM showed better performance in classifying diabetes disease diagnosis with accuracy 93.2%. Conclusion: The results of this study showed that the MKS-SSVM was effective to detect diabetes disease diagnosis and this is very promising compared to the previously reported results.

One of the main causes of death is cancer. The most common cancer in women is breast cancer. This disease if it be known early could be overcome and even prevented. Data classification techniques could be used to predict which patients had breast cancer and not with some parameters. Using the Neural Network method and Rapid Miner 9.0 tools aims to predict breast cancer diagnosis and then produced an accuracy value of 71,83%, precision 81,08% and recall of 69,17% with AUC of 0,806 which means that the classification was good so that patients with parameters there could be predicted which ones were breast cancer patients and which were not, so this pattern could be used as a benchmark for diagnosis so that it could be detected earlier and was expected to reduce the number of deaths from breast cancer.

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The stock price is the main factor that is considered by investors in making investment. The purpose of this study is to observe the relationship between earnings per share, capital structure and financial performance with stock prices. The type of research data that can be used is a quantitative approach. The sampling that can be used is the purposive sampling technique, and there are 19 companies in the mining sector that are sampled in 44 companies. The data source used is secondary data obtained from the Indonesia Stock Exchange, 2017 to 2019. The results of this study indicate that, individually, earnings per share have a positive and significant impact on stock prices and structural capital has a negative and significant impact on stock prices, while financial performance has no significant effect on stock prices.

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The largest income for Southeast Asian countries comes from the export activities of wood production. The potential for timber exports in Indonesia continues to increase each year. This soaring potential needs to be continually improved by maintaining quality so that trust and good cooperation can continue to be established with partner countries. Wood quality is closely related to wood defects. The faster the detection of wood defects is, the faster the quality of the wood will be determined. The wood industry which is still manual is also very susceptible to human eye fatigue. Technology is currently developing rapidly to help human productive activities and image processing is a breakthrough to detect wood defects. This study aims to identify swietenia mahagoni wood defects using the euclidean distance method from the extraction of 6 texture and shape features GLCM (Gray Level Co-Occurance Method) including metric, eccentricity, contrast, correlation, energy, and homogeneity, which was previously segmented with the best segmentation from the comparison results of thresholding and k-means segmentation and produced an average accuracy of 95.33% with an F1 score value of 0.95. The dataset used is the primary dataset with a total of 54 images on 3 types of wood defects, namely growing skin defects on wood ends, rotten wood eye on the body, and healthy wood eye on the body. Cross validation is also applied to test the reliability of the proposed model. By using 3-fold cross validation, the optimal average accuracy is 88.90%. Validation with other similar datasets was also carried out by identifying potato leaf defects resulting in an average accuracy of 92.86% with the most optimal 3-fold cross validation value achieved an average accuracy of 83.33%. Image augmentation is also carried out in order to reproduce the image so that the reliability test of the proposed method can be carried out, namely by rotating the image 45 degrees,90 degrees,120 degrees,180 degrees which produces 84 images of augmentation, so that the total image is 138 images and gets an average accuracy from the image augmentation is 80%.

Memiliki keturunan yang sehat, normal dan tidak beresiko bukan hal mudah didapatkan, pada kondisi tertentu melahirkan secara normal bukan solusi terbaik, operasi sesar bisa menjadi salah satu opsi yang dianggap relatif aman sejauh ini. Namun, karena sesar merupakan operasi besar, besar pula risikonya. Maka perlu pertimbangan yang matang mengenai metode melahirkan dengan normal atau operasi sesar. Penelitian ini bertujuan untuk mengklasifikasi harus menggunakan metode sesar atau tidak dengan memperhitungkan parameter yang ada yaitu diantaranya Age, Delivery Time, Delivery, Blood, Heart sehingga dapat memprediksi keselamatan ibu dan bayi dalam proses lahiran dengan menggunakan metode Neural Network dengan 80 dataset caesarian, training cycles 200, learning rate 0.01 dan momentum 0.9 dan menghasilkan akurasi sebesar 71,25% dan dengan nilai AUC (Area Under Curve) sebesar 0,721 yang artinya mendapat status fair classification.