http://repository.potensi-utama.ac.id/jspui/jspui/handle/123456789/5460 2026-04-16T15:20:17Z 2026-04-16T15:20:17Z Bob Subhan, Riza http://repository.potensi-utama.ac.id/jspui/jspui/handle/123456789/5463 2023-01-07T07:31:13Z 2021-02-20T00:00:00Z

Title: Students Grade Grouping to Optimize On-Time Graduation Predictions by Combining K-Means and C4.5 Algorithms (Case Study : University Potensi Utama Authors: Bob Subhan, Riza Abstract: Graduating on time is the dream of every student who studies in universities. Some factors that can lead to failure in graduating on time, such as grades, though students are sometimes careless and underestimating this factor, despite knowing that problematic Grade will hinder the student from graduating on time. This research helps the study program to predict which students will graduate on time. There are 2 stages in the research, first is the process of clustering students' data using the KMeans algorithm, while the second stage predicts students' graduation using the C4.5 algorithm. Variable used are Grade, Failing Grade, Specialization, Internship, Thesis, Undergraduate Thesis 1, Undergraduate Thesis 2, and Passing Grade. Using RapidMiner and processing these data using this software can predict students that graduate on time. Description: The problem that occurs today is students who do not realize nor care about the problematic grades (failed Grade). Problematic grades can affect students in taking specialization, street vendors, thesis 1 and thesis 2 not on the right time, where it impacts graduation. In the 2015 information system study program of students' data showed that there were 0.49% of students who had failed or problematic grades that did not pass on time, and so were students who could not complete internship and thesis on time, thus resulting in graduating not on time with a percentage value of 100%. So the criteria that will be included in this case study are Failing Grade, Grade, Specialization, Internship, Undergraduate Thesis 1 and 2. This case study also uses RapidMiner software. The clustering method uses K-Means, which functions to cluster students' data to make it easier for the next process, and C4.5 is used to process predictive decisions of students who can graduate on time. This research only discusses the prediction of students graduating on time, where the benefits are that students are more concerned with grades and courses to be taken next to graduate in time, and the study program can find out which students have problematic grades.

2021-02-20T00:00:00Z Bob Subhan, Riza http://repository.potensi-utama.ac.id/jspui/jspui/handle/123456789/5462 2023-01-07T07:23:13Z 2021-04-01T00:00:00Z

Title: RANCANG BANGUN SISTEM INFORMASI PENJUALAN PAKAN TERNAK BERBASIS MOBILE Authors: Bob Subhan, Riza Abstract: Penjualan merupakan salah satu hal yang sangat menentukan maju tidaknya sebuah perusahaan. Banyak perusahaan yang merupakan perusahaan yang bergerak dalam bidang penjualan bahan pakan ternak. Dari sejumlah perusahaan tersebut sering terjadi permasalahan, khususnya masalah pengolahan penjualan pakan ternak. Masalah tersebut diantaranya adalah kesalahan dalam pencatatan data penjualan pakan ternak, kesalahan dalam perhitungan data penjualan, keterlambatan dalam penyelesaian laporan dan masih banyak masalah lainnya. Walaupun ada beberapa perusahaan yang memiliki website, namun dalam melakukan pemesanan produk pakan ternak tidak dapat dilakukan secara online. Oleh karena itu, diperlukan sebuah system yang berupa aplikasi yang berbasis mobile untuk membantu permasalahan tersebut dengan lebih efektif dan efesian. Dalam penelitian ini untuk membuat terwujudnya aplikasi tersebuat peneliti menggunakan Android studio dan Mysql untuk membantu perancangan dan pembuatan aplikasi yang berbasis mobile tersebut. Dengan adanya aplikasi mobile ini maka dapat membantu penjualan khususnya perusahaan pakan ternak baik untuk proses jual-beli, transaksi, dan juga memberikan pemasaran yang lebih luas. Description: Saat ini banyak perusahaan bergerak dalam bidang penjualan bahan pakan. Komunikasi dan informasi dibutuhkan untuk kelangsungan produksi perusahaan, lembaga maupun kemajuan sebuah instansi. Kemampuan aplikasi digitisasi penjualan menawarkan banyak peluang baru terutama kesempatan memperluas pangsa pasar dengan biaya

2021-04-01T00:00:00Z Bob Subhan, Riza http://repository.potensi-utama.ac.id/jspui/jspui/handle/123456789/5461 2023-01-07T07:18:12Z 2022-05-13T00:00:00Z

Title: Comparison of K-Means Clustering and Otsu Thresholding Methods in the Detection of Tuberculosis Extra Pulmonary Bacilli in the HSV Color Space Authors: Bob Subhan, Riza Abstract: Tuberkulosis Ekstra Paru (TBEP) adalah salah satu penyakit menular yang disebabkan oleh bakteri Mycobacterium Tuberculosis dan dapat menyebabkan kematian. Pasien yang menderita penyakit ini harus cepat diobati tanpa menunggu waktu yang lama. Saat ini, setiap orang yang akan dideteksi penyakit akibat bakteri ini membutuhkan waktu yang lama dan biaya besar. Biopsi merupakan salah satu teknik yang digunakan dalam mengambil cairan pada paruparu dan diluar paru pasien. Cairan ini diberi pewarnaan kimiawi Ziehl Neelsen selanjutnya dilakukan pemeriksaan menggunakan mikroskop untuk mengidentifikasi penyakit Tuberkulosis. Penelitian ini bertujuan membantu mendeteksi bakteri dengan cepat dan tepat dengan melakukan pengolahan citra berbantu komputer dengan membuat sebuah sistem aplikasi. Teknik yang digunakan adalah melakukan pengembangan terhadap metode segmentasi. Penelitian ini diawali dengan melakukan transformasi ruang warna HSV (Hue Saturation Value) dimana Kelebihan menggunakan ruang warna HSV adalah terdapat warna-warna yang sama dengan yang dicapture oleh indera manusia. Proses segmentasi yang dilakukan adalah mengembangkan dengan teknik K-Means dan Otsu Thresholding. Dari hasil kedua metode yang digunakan ternyata metode Otsu Thresholding yang dapat mendeteksi basil TBEP dengan tingkat akurasi yang lebih baik dari metode K-Means. Sehingga metode yang dikembangkan ini sangat membantu dalam mempercepat dan meminimalisasi biaya untuk mendeteksi TBEP. Description: Tuberculosis is a life-threatening infectious disease worldwide caused by the bacterium Mycobacterium tuberculosis. These bacteria are in the form of acid-fast bacilli or often called acid-fast bacilli (AFB). This bacillus measuring 1-4 m long and 0.3-0.56 m wide, as shown in Figure 1, is not spore-forming, non-motile, and facultative. Bacterial cell walls contain long-chain glycolipids that are mycolic and rich in acids and phosphopoglycans [1][2][3]. Tuberculosis (TB) is a chronic and infectious disease that affects the world's human population and requires complex treatment. It is a public health problem with more than 9 million estimated new cases and 1.5 million deaths annually worldwide [4]. Of the estimated 9 million people who contracted TB in 2013, more than 80% were in Southeast Asia, the Western Pacific, and Africa. The majority of the infected population comes from poor and marginalized communities with weak health services infrastructure[5]. Tuberculosis can affect every human being regardless of region. Usually, the ones who develop this disease are adults, with 30 countries affected by Tuberculosis where almost 90% of those affected fall ill. Those of productive age are susceptible to TB between 15 to 50 years and children. TB usually comes out through phlegm and coughing. If the saliva is scattered at low temperatures, the possibility for germs to survive will be long enough to allow the transmission process to occur. There are two types of Tuberculosis, namely Tuberculosis Pulmonary (TBP) and Tuberculosis Extra Pulmonary (TBEP). TBP affects the lungs, whereas TBEP can affect any organ of the body except the spine, heart, pancreas, skeletal muscle, and thyroid. So far, to detect Tuberculosis Extra Pulmonary (TBEP) through a biopsy, namely by taking fluid from a person's lymph nodes which a doctor or health analyst will detect, then placed on the preparation and viewed through a microscope for readings on the preparation to see the presence of germs or tuberculosis bacilli. Noticing what is happening will take a long time because the liquid preparations are viewed under the microscope carefully, and the liquid preparations contain 150 fields of vision[6]. Tuberculosis Extra Pulmonary can cause complications. Based on this, we need a system for good reporting and recording for TB control [7].

2022-05-13T00:00:00Z