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All Journal Jurnal Energi Dan Manufaktur Mechatronics, Electrical Power, and Vehicular Technology Simetris Jurnal Simetris Transformasi: Jurnal Pengabdian Masyarakat Compiler INFOMATEK: Jurnal Informatika, Manajemen dan Teknologi Jurnal Teknik Mesin Jurnal Informatika dan Rekayasa Elektronik Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC) Jurnal Abdi Insani BERNAS: Jurnal Pengabdian Kepada Masyarakat Jurnal Ilmiah Intech : Information Technology Journal of UMUS Jurnal Teknik Informatika (JUTIF) Prima Abdika: Jurnal Pengabdian Masyarakat International Journal for Applied Information Management LOGIC : Jurnal Ilmu Komputer dan Pendidikan Jurnal Ilmiah Informatika dan Komputer Fokus Abdimas The Indonesian Journal of Computer Science International Conference on Digital Advanced Tourism, Management, and Technology Lumbung Ngabdi: Jurnal Pengabdian Masyarakat Jurnal Komtika (Komputasi dan Informatika)
Wahyusari, Retno
Sekolah Tinggi Teknologi Ronggolawe Cepu
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Journal : Simetris

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PENERAPAN ALGORITMA VIOLA JONES UNTUK DETEKSI WAJAH Retno Wahyusari; Bambang Haryoko
SIMETRIS No 18 (2014): SIMETRIS
Publisher : Sekolah Tinggi Teknologi Ronggolawe Cepu

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Abstract

Deteksi wajah merupakan langkah awal dan fundamental dalam interaksi manusia, image retrieval, tracking, pengenalan wajah dan lain sebagainya. Saat ini detetksi wajah merupakan topik yang sangat menarik untuk diangkat menjadi penelitian. Algoritma viola jones merupakan standart defacto untuk deteksi wajah. Maka penelitian yang dilakukan menggunakan algoritma viola jones. Algoritma viola jones memiliki 3 konstribusi: citra integral, kontribusi kedua citra integral memungkinkan evaluasi fitur yang sangat cepat dengan menggunakan Adaboost dalam pemilihan fitur, dan yang ketiga penggunaan cascade classifier. Dari hasil penelitian menunjukkan nilai precission sebesar 94,95% dan recall sebesar 91,39% untuk dataset Baodataset. Sedangkan untuk data pribadi untuk precision sebesar 91,53% dan recall sebesar 80,60%.
Rancang Bangun Saron Digital (Laron) Berbasis Capacitive Sensor Pada Arduino Uno retno wahyusari; Lastoni Wibowo
SIMETRIS Vol 12 No 1 (2018): SIMETRIS
Publisher : Sekolah Tinggi Teknologi Ronggolawe Cepu

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Abstract

Blora Regency has a diverse artistic treasury. Various arts have been preserved until now. Besides attracting tourists to Blora, the art is also a manifestation of the high creativity of Blora people. The five distinctive arts of Blora Regency that are still preserved by the community are: Barongan Blora, Tayub Blora, Kadroh, Ketoprak, and Karawitan. Almost all of the typical arts of Blora Regency use gamelan instruments. Gamelan itself is a musical instrument not only owned by Blora Regency, but also an Indonesian traditional musical instrument that is worldwide. Gamelan for ancient people is considered as their identity, according to them traditional music is something to be proud of and liked. But why do young people today even dislike traditional music. One effort to attract the interest of the younger generation is to modernize the gamelan. Modernizing gamelan is not only to attract the interest of the younger generation, it will also be used as a solution to of preserving culture. Keywords: Arduino Uno, Capasitive Sensor, Saron Digital
PERBAIKAN CITRA MENGGUNAKAN HISTOGRAM EQUALIZATION PADA DETEKSI TEPI BATIK retno wahyusari
SIMETRIS Vol 13 No 1 (2019): SIMETRIS
Publisher : Sekolah Tinggi Teknologi Ronggolawe Cepu

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Abstract

ABSTRACTIndonesia has 17 diverse cultures that have been recognized by UNESCO, one of which is batik.There is recognition from UNESCO that Indonesian cultural heritage of batik may not berecognized by other countries. Batik as a cultural heritage has its own uniqueness, to maintain theuniqueness of batik, it is necessary to document batik motifs. Batik motifs can be documented bychanging batik motifs into images or images. One way to change batik motifs into images is by using optical devices such as cameras,scanners, and so on. The authenticity of batik motifs from the documentation needs to be done bydetecting the edge of the batik so that the batik motif can be maintained properly. One methodused is to use the canny method in Matlab 2013, but edge detection with canny has weaknesses inimages that have uneven gray values, so to level up the grayishness of batik it is necessary toimprove the image using the histogram equalization method. Detection of batik edges with image improvement using histogram equalization methodand canny method can improve the detection results with the number of test data 13 with a totalof batik images that can be repaired 10 batik images and 3 batik images have not been able to berepaired. The best MSE value is 0.229538 and PSNR is 54.5563. Poor value with MSE 0.676356and PSNR 49,863.
IMPLEMENTASI ALGORITMA C4.5 UNTUK PENENTUAN PENERIMAN BEASISWA (Studi Kasus: SMA N 2 Cepu) retno wahyusari
SIMETRIS Vol 15 No 2 (2021): Simetris
Publisher : Sekolah Tinggi Teknologi Ronggolawe Cepu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51901/simetris.v15i2.209

Abstract

One of human rights is the right to education. In organizing quality education requires substantial costs. Scholarships are a way to overcome cost problems for those who are less well off. Scholarships are assistance from the government of the private sector in the form of a sum of money given to students who are currently or who will attend school education. The granting of this sholarships is very important, in order to give students peace of mind in attending teaching and learning. Because many students apply for scholarships and too many indicators result in receivi9ng scholarships that are not well targeted. To overcome this problem, a scholarships acceptance Decision Support System was created using the C4.5 Algorithm which will make it easier for the 2 Cepu High School selection team to select students who are entitled to scholarships because in High School 2 Cepu the selection proses still uses manual methods and requires a long time. C4.5 Algorithm is a development of the ID3 Algorithm based on Supervised Learning. By using the Decision Tree method C4.5 Algorithm it is hoped that the awarding of scholarships can be right on target. In this study the researchers used class 11 and class 12 as training data to determine the decision tree in RapidMiner, while class 10 data became the testing data for the matlab proses. There are 99 students in grades 11 and 12 who are eligible for scholarships, while 402 grade 11 and 12 students who do not deseve a scholarship. The results of the decision tree support system research with the decision tree method for the recommendation of students to be eligibel or not to receive sholarships using the C4.5 arlgorithm can prosuce a high level of accuracy that is equal to 96,80%.
Penerapan Algoritma Apriori Untuk Menemukan Pola Peminjaman Buku Di Perpustakaan (Studi Kasus: Sekolah Menengah Atas Negeri 2 Cepu) Retno Wahyusari
SIMETRIS Vol 16 No 1 (2022): Simetris
Publisher : Sekolah Tinggi Teknologi Ronggolawe Cepu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51901/simetris.v16i1.236

Abstract

The library is a means of providing information, sources of knowledge and means of supporting teaching and learning activities for users to obtain the desired information. Cepu Public High School 2 library has a collection of books ranging from subject books to other types of books around 600 copies. More than 280 new students with all students ranging from 10th to 12th grade around 750 students, therefore with this increase in number of students the library is also required to increase its book collection to support the activities of its students. Cepu Public High School 2 library is more than 10 visitors per visit, one of the activities in the library is borrowing books. Every year the library staff reports on books that have been borrowed by students, about 100 books lending transactions per year. The average student in publishing more than one book, they buy books based on the relevance of the subject matter. Students in the search for books that have a connection takes quite a long time, this is related to the placement of books that are not based on the relevance of the textbook. Linkages between books can be identified by gathering information by collecting lending data sets. Extracting the linkage information between book items is known as the association rule method. The rule association method in this study uses the Apriori algorithm to provide book placement recommendations. Apriori algortiam selection because Apriori algorithm is the most established algorithm in the rules of association. The results of the research conducted resulted in 3 rules of association rules with a minimum support value of 20% with a minimum trust value of 50% and 70% obtained the highest value of the confidence of 78% and 47% support if using books 500-599 books will be purchased 300-499.
Penerapan Algoritma K-Medoids Untuk Mengelompokkan Status Obesitas Wahyusari, Retno
SIMETRIS Vol 18 No 1 (2024): SIMETRIS
Publisher : Sekolah Tinggi Teknologi Ronggolawe Cepu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51901/simetris.v18i1.405

Abstract

Obesitas merupakan salah satu masalah kesehatan global yang semakin mendesak untuk ditangani. Organisasi Kesehatan Dunia (WHO) mencatat bahwa angka kejadian obesitas telah meningkat tiga kali lipat sejak tahun 1975, dengan lebih dari 1,9 miliar orang dewasa mengalami kelebihan berat badan, dan di antaranya, lebih dari 650 juta orang terdiagnosis obesitas. Penelitian ini bertujuan untuk menerapkan algoritma K-Medoids dalam pengelompokan data status obesitas. Pengelompokan dilakukan menggunakan RapidMiner dengan berbagai konfigurasi jumlah kluster, dan hasil dievaluasi menggunakan beberapa metrik validasi kluster termasuk Davies-Bouldin Index (DBI). Hasil penelitian menunjukkan bahwa jumlah kluster tiga (k = 3) adalah yang paling optimal dalam mengelompokkan data obesitas, dengan nilai DBI sebesar 0,071, dibandingkan dengan dua kluster (k = 2) yang memiliki nilai DBI sebesar 0,101. Nilai DBI yang lebih rendah menunjukkan bahwa kluster yang terbentuk lebih kompak dan terpisah dengan baik, menandakan performa yang lebih baik dalam pengelompokan data status obesitas.
Penerapan Algoritma K-Medoids Untuk Mengelompokkan Status Obesitas Wahyusari, Retno
SIMETRIS Vol 18 No 1 (2024): SIMETRIS
Publisher : Sekolah Tinggi Teknologi Ronggolawe Cepu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51901/simetris.v18i1.405

Abstract

Obesitas merupakan salah satu masalah kesehatan global yang semakin mendesak untuk ditangani. Organisasi Kesehatan Dunia (WHO) mencatat bahwa angka kejadian obesitas telah meningkat tiga kali lipat sejak tahun 1975, dengan lebih dari 1,9 miliar orang dewasa mengalami kelebihan berat badan, dan di antaranya, lebih dari 650 juta orang terdiagnosis obesitas. Penelitian ini bertujuan untuk menerapkan algoritma K-Medoids dalam pengelompokan data status obesitas. Pengelompokan dilakukan menggunakan RapidMiner dengan berbagai konfigurasi jumlah kluster, dan hasil dievaluasi menggunakan beberapa metrik validasi kluster termasuk Davies-Bouldin Index (DBI). Hasil penelitian menunjukkan bahwa jumlah kluster tiga (k = 3) adalah yang paling optimal dalam mengelompokkan data obesitas, dengan nilai DBI sebesar 0,071, dibandingkan dengan dua kluster (k = 2) yang memiliki nilai DBI sebesar 0,101. Nilai DBI yang lebih rendah menunjukkan bahwa kluster yang terbentuk lebih kompak dan terpisah dengan baik, menandakan performa yang lebih baik dalam pengelompokan data status obesitas.
Co-Authors ., Suprawikno Abdul Azis Abdul Fadlil Achmad Furqon Nur Fitriadhi Adhika Pramita Widyassari Agung D.N.P, Muhammad Aji, Doni Kurnia Al Hadi, Fahreza Amrozi, M Ali Anang Widianto Aprilia, Dyah Ayu Safitri Aris Rakhmadi Astika AyuningTyas, Astika Ayu, Anggi Mutia Bambang Haryoko Carreon, Jonathan Rante Devi Tiana Kartikasari Dwi Purnomo Putro Eka Y, Sandy Pramudya Endang Kurniawati, Endang Eva Hertnacahyani Herraprastansi Fachry Abda El Rahman Figo SW, Denni Ghifari, Muhammad Al Gunawan, Helmi Hamzah, Fahmi Aliefuddin Imam Riadi Indra Gunawan Joko Handoyo Korawan, Agus Dwi Kuncoro, Bagus Tri Lastoni Wibowo Lies Indriyatni Mahdum, Esa Adistiya Fajarwati Masuri, Masuri Maziyah, Hilda Nur Mohamad Ardy An’syah Muchlas Muchlas Mudjijanto, Mudjijanto Muhammad Abdimas Khalifuddin Nagari, Bintang Putra Nugraha, Anung Satria Nur Azizah Puput Eka Suryani Putro, Dwi Purnomo Rahmasari, Nagita Ratna Dwi Rahayu Rochmadi, Tri Safiq Rosad Salsabilla, Dea Sarmini Setiawan, David Harry Shofia, Aina Subkan, Muhamad Nur Sulistiyo, Yogi Sunardi Sunardi suryani, puput eka Suryanto, Hendri Suryanto, Hendri Sushananto W, Denni Figo Sutriyani, Wulan Teguh Adi Saputro Teguh Yuwono Teguh Yuwono Wiranti, Dwiana Asih