No abstract

Breast cancer is the most important cause of death among women. A prediction of breast cancer in early stage provides a greater possibility of its cure. It needs a breast cancer prediction tool that can classify a breast tumor whether it was a harmful malignant tumor or un-harmful benign tumor. In this paper, two algorithms of machine learning, namely Support Vector Machine and Extreme Gradient Boosting technique will be compared for classification purpose. Prior to the classification, the number of data attribute will be reduced from the raw data by extracting features using Principal Component Analysis. A clustering method, namely K-Means is also used for dimensionality reduction besides the Principal Component Analysis. This paper will present a comparison among four models based on two dimensionality reduction methods combined with two classifiers which applied on Wisconsin Breast Cancer Dataset. The comparison will be measured by using accuracy, sensitivity and specificity metrics evaluated from the confusion matrices. The experimental results have indicated that the K-Means method, which is not usually used for dimensionality reduction can perform well compared to the popular Principal Component Analysis.

<p align="center"><strong>Abstrak</strong> </p><p><em>Teknologi komputer mempengaruhi setiap bidang kehidupan saat ini. ia masuk dan mengubah setiap bidang di dunia, mulai dari industri dan bisnis, transportasi, komunikasi, kesehatan, dan lain-lain. Setiap siswa memiliki kesempatan yang sama untuk mempleajari dan menguasai teknologi, belajar coding, menguasai algoritma, mempelajari bagaimana cara membuat aplikasi, bagaimana internet bekerja, dalam rangka memupuk kreativitas dan keterampilan menyelesaikan masalah (problem solving) yang akan sangat berguna bagi kehidupan mereka di masa depan. Program komputer/perangkat lunak atau software akan menjadi hal yang sangat penting, bahkan mungkin akan menjadi bahasa dunia ke depan. Tidak menguasai programming atau bahasa komputer di masa depan, akan sama efeknya dengan tidak bias baca tulis saat ini. Belajar ilmu komputer tidak hanya belajar tentang teknologi itu sendiri, namun juga belajar logika, penyelesaian masalah (problem solving), dan kreativitas. Oleh karena itu perlu adanya pengenalan dan pelatihan pemrograman untuk siswa sekolah untuk melatih kemampuan logika dan problem solving. Pelatihan pemrograman diberikan dalam bentuk simulasi Blockly berupa games yang menarik dan interaktif. Hasil dari pelatihan didapatkan bahwa siswa SMA peserta pelatihan merasa kegiatan ini sangat menarik dan bermanfaat dan dapat menambah pamahaman dan keterampilan mereka dalam hal IT dan penerapannya.</em></p><p><strong>Kata kunci<em>: </em></strong><strong><em>Coding, </em></strong><strong><em>Komputer, Pemrograman, TIK</em></strong></p><p><strong><em><br /></em></strong></p><p align="center"><strong>Abstract</strong></p><p><em>Computer technology affects every area of life today. he entered and changed every field in the world, starting from industry and business, transportation, communication, health, and others. Every student has the same opportunity to learn and master technology, learn coding, master algorithms, learn how to make applications, how the internet works, in order to foster creativity and problem solving skills that will be very useful for their lives in the future . Computer / software or software programs will be very important, maybe even become the world language in the future. Not mastering programming or computer language in the future, it will have the same effect as the current non-literacy. Learning computer science not only learns about technology itself, but also learns logic, problem solving, and creativity.</em> <em>Therefore there is a need for introduction and programming training for school students to practice logic and problem solving skills. Programming training is provided in the form of Blockly simulations in the form of interesting and interactive games. The results of the training found that high school students participating in the training felt this activity was very interesting and useful and could add to their understanding and skills in terms of IT and its application.</em> </p><p><strong>Keywords<em>: </em></strong><strong><em>Coding, </em></strong><strong><em>Computer, Computer Science, Programming</em></strong></p>

<p><em>Abstrak</em> - <strong>Proses penjadwalan kuliah di suatu Universitas merupakan suatu proses yang memiliki peran penting. Dengan adanya sistem yang dapat melakukan penjadwalan dengan mempersingkat proses dan tidak adanya jadwal yang bentrok, kegiatan perkuliahan akan berjalan secara tertib. Penelitian ini akan membahas mengenai proses penjadwalan kuliah di Universitas Al Azhar Indonesia (UAI) dengan menggunakan algoritma genetika. Analisa kebutuhan sistem dilakukan sesuai dengan proses bisnis penjadwalan kuliah di UAI. Pada algoritma genetika ini terdapat <em>hard constrain</em> dan <em>soft constrain</em> yang bisa ditentukan sesuai dengan kebutuhan, seperti satu jadwal kuliah tidak boleh ada yang beririsan dengan jadwal kuliah yang lainnya. Sistem dapat merekam jadwal yang dapat dipenuhi dan juga tidak dapat dipenuhi dosen, sehingga ketika dalam proses penjadwalan, sistem dapat mencari waktu pengganti lainnya. Terdapat perubahan proses bisnis penjadwalan kuliah di UAI, dan juga berdampak pada pengembangan sistem informasi penjadwalan kuliah. Terdapat input dan output file json yang digunakan untuk komunikasi antara sistem informasi penjadwalan kuliah yang ada dengan sistem penjadwalan algoritma genetik. </strong></p><p><strong> </strong></p><p><strong><em>Kata Kunci</em></strong><strong> – </strong><em>Penjadwalan Kuliah, Algoritma Evolusi, Presensi Waktu Dosen</em></p><p> </p><p><strong>Abstract - The process of scheduling a lecture at a university is a process that has an important role. With a system that can perform scheduling by shortening the process and the absence of conflicting schedules, lecture activities will run in an orderly manner. This research will discuss about the process of scheduling lecture at Al Azhar University of Indonesia (UAI) by using genetic algorithm. Analysis of system requirements is done in accordance with business process scheduling lectures at UAI. In this genetic algorithm there is a hard constrain and soft constrain that can be determined according to need, such as a lecture schedule should not be any that incline with other lecture schedules. The system can record schedules that can be met and also can’t be met lecturers, so that when in the process of scheduling, the system can find another replacement time. There is a change in the business process of lecture scheduling in UAI, and also has an impact on the development of lecture scheduling information system. There is an input and output json file that is used for communication between existing lecture scheduling information systems with genetic algorithm scheduling system.</strong></p><p><strong> </strong></p><strong><em>Keywords</em> - </strong><em>Scheduling Lectures, Evolution Algorithm, Lecturer Time Presentation</em>

<p><em>Abstrak</em> – <strong>Indonesia memiliki tingkat kerawanan tinggi terhadap bencana alam dan kecelakaan yang mengakibatkan terjadinya korban massal. Banyak cara untuk mengidentifikasi korban, salah satunya menggunakan citra gigi. Gigi merupakan bagian dari tubuh yang lebih tahan lama karena struktur gigi yang padat dan kuat. </strong><strong>Identifikasi menggunakan sarana gigi dapat dilakukan dengan cara membandingkan data gigi yang telah diperoleh dari pemeriksaan gigi jenazah yang tidak dikenal (data <em>postmortem</em>) dengan data gigi yang sebelumnya pernah dibuat (data <em>antemortem</em>). Terdapat beberapa tahapan dalam melakukan identifikasi korban menggunakan citra gigi. Tahapan yang dilakukan oleh peneliti adalah tahap segmentasi gigi. Pertama, citra dilakukan <em>cropping</em> hingga mendapatkan dimensi berukuran 1564×589 piksel serta perbaikan citra menggunakan <em>Histogram Equalization</em>. Selanjutnya dilakukan pemisahan citra gigi menggunakan metode <em>Integral Projection</em> dilengkapi penggunaan <em>Spline Interpolation</em> untuk menggambar garis pemisah antara rahang atas-bawah serta gigi tunggal. Tiap citra memiliki nilai n-blok kolom yang berbeda sehingga dibutuhkan parameter sebesar 3 hingga 30 n-blok kolom untuk membentuk garis pemisah rahang atas-bawah. Citra gigi berjenis <em>Dental Panoramic Radiograph</em>. Hasil evaluasi kesalahan<em> </em>terkecil saat melakukan pemisahan rahang atas-bawah menggunakan <em>Horizontal Integral Projection</em> sebesar 56.8% dengan nilai n-blok kolom adalah 8 dan saat<em> </em>segmentasi gigi pada tahap <em>Vertical Integral Projection</em> sebesar 38.27% dengan nilai <em>average filter</em> adalah<em> </em>17.</strong></p><p><em>Abstract</em> – <strong>Indonesia has a high level of vulnerability to natural disasters and accidents that result in mass casualties. There are many ways to identify victims, especially by using dental images. The teeth are part of the body that are more durable because of the solid and strong tooth structure. Identification using dental images can be done by comparing dental data that has been obtained from unknown victim dental examination (postmortem data) with dental data previously made (antemortem data). There are several stages in identifying victims using dental images and researcher worked on tooth segmentation stage. First, the image need to cropped up to get dimensions size of 1564</strong><strong>×</strong><strong>589 pixels and improved contrast using Histogram Equalization method. Then, tooth separation is performed using Integral Projection method which is equipped with the use of Spline Interpolation to draw the separator line between the upper-lower jaws and single tooth. Each image has a different n-block column value, so researcher selected range number of n-block column is between 3-30. In this reseach, dental panoramic radiographs are used. The smallest error rate in the images is found when performing an Integral Projection to separate upper and lower jaws by 56.8% with n-block column value = 8 and when separating each tooth from the image by 38.27% with average filter value = 17.</strong></p><p><strong><em>Keywords</em></strong> – <em>Antemortem, Postmortem, Segmentation, Histogram Equalization, Integral Projection, Spline Interpolation</em></p>