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All Journal Bulletin of Electrical Engineering and Informatics Jurnal Penelitian Pendidikan Kreano, Jurnal Matematika Kreatif-Inovatif International Journal of Advances in Intelligent Informatics Scientific Journal of Informatics Buletin Ilmiah Sarjana Teknik Elektro Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Manajemen Transportasi & Logistik (JMTRANSLOG) Journal of Soft Computing Exploration Devotion: Journal of Research and Community Service Unnes Journal of Mathematics Education Unnes Journal of Mathematics Journal of Advances in Information Systems and Technology Proceeding ISETH (International Summit on Science, Technology, and Humanity) Jurnal Inovasi Pengabdian dan Pemberdayaan Masyarakat Innovative: Journal Of Social Science Research Recursive Journal of Informatics Scientific Journal of Informatics
Endang Sugiharti, Endang
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Public Health Social Sciences Other

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PENERAPAN ALGORITMA PRIM DAN KRUSKAL PADA JARINGAN DISTRIBUSI AIR PDAM TIRTA MOEDAL CABANG SEMARANG UTARA Latifah, Umi; Sugiharti, Endang
Unnes Journal of Mathematics Vol 4 No 1 (2015)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/ujm.v4i1.7418

Abstract

Algoritma Prim dan Kruskal adalah algoritma yang dapat digunakan untuk mencari pohon rentang minimum untuk graf berbobot. Permasalahan dalam penulisan skripsi ini adalah bagaimana hasil pohon rentang minimum menggunakan algoritma Prim dan Kruskal, serta bagaimana aplikasinya menggunakan MATLAB. Dari data yang diperoleh dapat disusun gambar jaringan. Selanjutnya dari gambar jaringan dapat diperoleh pohon rentang minimum menggunakan algoritma Prim dan Kruskal, dengan bantuan program MATLAB. Berdasarkan hasil penelitian dan pembahasan dapat disimpulkan bahwa pohon rentang minimum dari A1 (PDAM) ke A51 (titik penyambungan pipa) menggunakan algoritma Prim dan program MATLAB adalah 24.365 m. Begitupula menggunakan algoritma Kruskal dan program MATLAB ternyata 24.365 m. Hal ini mengakibatkan penghematan pipa pendistribusian sepanjang 12.735 m dari panjang total sebelumnya yaitu 37.100 m.
IMPLEMENTASI ALGORITMA GENETIKA DENGAN TEKNIK KENDALI LOGIKA FUZZY UNTUK MENGATASI TRAVELLING SALESMAN PROBLEM MENGGUNAKAN MATLAB Fitriana, Erma Nurul; Sugiharti, Endang
Unnes Journal of Mathematics Vol 4 No 2 (2015)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/ujm.v4i2.9352

Abstract

Algoritma Genetika dengan Teknik Kendali Logika Fuzzy adalah algoritma yang dapat digunakan untuk mengatasi Travelling Salesman Problem. Permasalahan dalam penulisan skripsi ini adalah bagaimana hasil jarak minimum dari jaringan TSP menggunakan algoritma genetika dengan teknik kendali logika fuzzy, serta bagaimana aplikasinya menggunakan MATLAB. Dari data yang diperoleh dapat ditentukan koordinat. Selanjutnya dari koordinat dapat diperoleh solusi optimal dengan menggunakan masukan populasi dan generasi tertentu dengan bantuan software MATLAB. Dari hasil analisis algoritma genetika dengan teknik kendali logika fuzzy diperoleh hasil bahwa solusi optimal menggunakan masukkan populasi 100 dan generasi 1000 lebih baik dari solusi optimal yang didapatkan dengan masukkan populasi dan generasinya berturut-turut adalah (100 dan 100), (100 dan 200), (100 dan 500), (200 dan 100), (500 dan 100) dan (1000 dan 100). Kemudian didapatkan rute terbaiknya adalah 1-3-4-6-9-8-7-19-18-16-17-20-21-22-15-12-11-10-14-13-5-2-1 dan panjang jalur terbaiknya adalah 22,63 Km
Aplikasi Mobile Sistem Informasi Akademik Labschool Universitas Negeri Semarang Berbasis Android Hariyanto, Abdul; Sugiharti, Endang; Arifudin, Riza
Unnes Journal of Mathematics Vol 8 No 1 (2019)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/ujm.v8i1.13915

Abstract

Kemajuan teknologi yang sangat pesat terutama teknologi mobile, sudah memaksa segala bidang untuk mengikuti perkembangan teknologi yang sudah ada. Salah satunya adalah bidang pendidikan. Labschool Universitas Negeri Semarang telah menerapkan teknologi informasi pada sistem pembelajarannya. Teknologi informasi yang telah dikembangkan adalah SIAKAL (Sistem Informasi Akademik Labschool). Masalah selanjutnya adalah ketika perkembangan teknologi mobile sudah jauh berkembang menjadikan SIAKAL susah untuk dibuka dengan perangkat mobile, karena tampilan masih belum responsive. Dalam penelitian ini, peneliti akan merancang dan membangun aplikasi mobile sistem informasi akademik Labschool berbasis android. Aplikasi dikembangkan dengan menggunakan metode waterfall, dengan proses analisa sistem, desain sistem, pembuatan sistem, pengujian, dan pemeliharaan. Pengujian aplikasi dilakukan dengan metode Blackbox dan pengujian oleh user. Hasil akhir penelitian diketahui bahwa aplikasi dapat terimplementasi dengan baik pada perangkat android dengan versi 4.2 Jelly Bean sampai 4.4 Kitkat yang memiliki ukuran layar yang berbeda.
Sistem informasi administrasi pengelolaan iuran bulanan berbasis SMS gateway dengan menggunakan model perangkat lunak prototype Adha, Nugraha Saputra; Sugiharti, Endang; Arifudin, Riza
Unnes Journal of Mathematics Vol 7 No 2 (2018)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/ujm.v7i2.14165

Abstract

Tujuan dari penelitian ini adalah untuk membuat sistem informasi administrasi pengelola iuran bulanan berbasis SMS Gateway yang dapat merekap setiap transaksi iuran bulanan sekolah serta mengirimkan SMS kepada wali murid sebagai bukti pembayaran serta wali murid dapat mengirimkan SMS kepada sistem untuk memeriksa pembayaran iuran bulanan putra/putrinya. Dalam pembuatan sistem informasi administrasi ini menggunakan software Visual Basic .Net dan MySQL sebagai pengolah database. Selain itu, model pengembangan perangkat lunak Prototype juga digunakan untuk mempermudah proses pengembangan aplikasi ini. Data yang digunakan dalam penelitian ini diperoleh berdasakan observasi lapangan di sekolah MA-Al Ishlah. Data tersebut digunakan untuk membentuk struktur database agar sistem berjalan dengan baik sesuai dengan kebutuhan. Berdasarkan hasil penenlitian, diperoleh sebuah aplikasi yang mampu membantu petugas tata usaha dalam mengelola administrasi keuangan sekolah. Pada program ini petugas tata usaha dapat melakukan pengelolaan transaksi pembayaran, membuat laporan transaksi baik laporan pembayaran maupun laporan tunggakan. The purpose of this research is to create administrative information system management of monthly fee based on SMS Gateway which can reconcile every transaction of monthly fee and send SMS to parents as proof of payment and parents can send SMS to system to check payment of monthly fee of their son/their daughter. To create this administrative information system using Visual Basic.Net software and MySQL as a database processor. In addition, Prototype software development model is also used to simplify the process of developing this application.The data used in this research is obtained based on field observation at MA-Al Ishlah school. The data is used to create the database structure for the system to run properly in accordance with the needs. Based on the results of this research, obtained an application that is able to help administrative officers in managing school financial administration. In this program administrative officers can manage payment transactions, making transaction reports both payment reports and arrears reports.
EFEKTIVITAS ALGORITMA CLARKE-WRIGHT DAN SEQUENTIAL INSERTION DALAM PENENTUAN RUTE PENDISTRIBUSIAN TABUNG GAS LPG Rupiah, Siti; Mulyono, Mulyono; Sugiharti, Endang
Unnes Journal of Mathematics Vol 6 No 2 (2017)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/ujm.v6i2.20484

Abstract

Permasalahan distribusi tabung gas LPG dari salah satu agen LPG di Blora yaitu PT. X ke beberapa sub agen/pangkalan merupakan contoh kasus permasalahan Capacitated Vehicle Routing Problem (CVRP). Permasalahan dalam penelitian ini adalah bagaimana menyelesaikan masalah rute pendistribusian tabung gas LPG menggunakan algoritma Clarke-Wright dan algoritma Sequential Insertion. Pencarian rute tersebut dilakukan secara hitungan manual dan dengan bantuan program Matlab R2014a. Selanjutnya akan ditentukan keefektifan dari penggunaan kedua algoritma tersebut. Pengambilan data dilakukan dengan metode observasi dan wawancara secara langsung dengan pegawai di PT. X. Simpulan yang diperoleh adalah pada solusi algoritma Clarke-Wright diperoleh penghematan jarak sebesar 146,2 km/minggu dan penghematan biaya transportasi sebesar Rp94.116,25/minggu; Sedangkan pada solusi algoritma Sequential Insertion diperoleh penghematan jarak sebesar 160,2 km/minggu dan penghematan biaya transportasi sebesar Rp103.128,75/minggu. Dengan demikian dapat disimpulkan bahwa rute yang dibentuk menggunakan algoritma Sequential Insertion pada kasus ini lebih efektif dibandingkan rute yang dibentuk menggunakan algoritma Clarke-Wright.
Integration of convolutional neural network and extreme gradient boosting for breast cancer detection Endang Sugiharti; Riza Arifudin; Dian Tri Wiyanti; Arief Broto Susilo
Bulletin of Electrical Engineering and Informatics Vol 11, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i2.3562

Abstract

With the most recent advances in technology, computer programming has reached the capabilities of human brain to decide things for almost all healthcare systems. The implementation of Convolutional Neural Network (CNN) and Extreme Gradient Boosting (XGBoost) is expected to improve the accurateness of breast cancer detection. The aims of this research were to; i) determine the stages of CNN-XGBoost integration in diagnosis of breast cancer and ii) calculate the accuracy of the CNN-XGBoost integration in breast cancer detection. By combining transfer learning and data augmentation, CNN with XGBoost as a classifier was used. After acquiring accuracy results through transfer learning, this reasearch connects the final layer to the XGBoost classifier. Furthermore, the interface design for the evaluation process was established using the Python programming language and the Django platform. The results: i) the stages of CNN-XGBoost integration on histopathology images for breast cancer detection were discovered. ii) Achieved a higher level of accuracy as a result of the CNN-XGBoost integration for breast cancer detection. In conclusion, breast cancer detection was revealed through the integration of CNN-XGBoost through histopathological images. The combination of CNN and XGBoost can enhance the accuracy of breast cancer detection.
Implementation of NXT 2.0 Mindstorm Robot Sensors on Mobile Education for Students Rizki Danang Kartiko Kuncoro; Riza Arifudin; Endang Sugiharti
Proceeding ISETH (International Summit on Science, Technology, and Humanity) 2018: Proceeding ISETH (International Summit on Science, Technology, and Humanity)
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In the current 4.0 industry era, technological development is very fast and fast. In the world of education the lessons about technology should have been introduced to students since elementary school. Do not have to use complex technology, enough to use robotics technology from the NXT 2.0 LEGO minstorm robot which is lego-based to play and learn algorithms in composing technology. Using this tool can also be controlled by the smartphone application. Using a mobile application that we designed will make it easier for students to use and play this educational media. In this media, each sensor in the robot will be interrelated to the mobile control, we have tested this control with 83.33% detection accuracy. So that it can effectively become an interactive and fun technology-based learning media for students. The purpose of this educational media is to improve the quality of education in Indonesia so that it can be technology-based and enjoyable for students. Because the application of technology to education is very important to hone the power of creative thinking in composing programming algorithms using robots. Students will be very interested and have good enthusiasm in learning robotics based on this mobile application.
Implementation of Discretisation and Correlation-based Feature Selection to Optimize Support Vector Machine in Diagnosis of Chronic Kidney Disease Dwika Ananda Agustina Pertiwi; Pipit Riski Setyorini; Much Aziz Muslim; Endang Sugiharti
Buletin Ilmiah Sarjana Teknik Elektro Vol. 5 No. 2 (2023): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v5i2.7548

Abstract

This study aims to improve the accuracy of the classification algorithm for diagnosing chronic kidney disease. There are several models of data mining. In classification, the Support Vector Machine (SVM) algorithm is widely used by researchers worldwide. The data used is a chronic kidney disease dataset taken from the UCI machine learning repository. This data consists of 25 attributes and 11 numeric data attributes, and 14 negative attributes. To call continuously, discrete data is used. Meanwhile, data is selected using Correlation-based Feature Selection (CFS) to reduce irrelevant and redundant data. The research results by applying discretization and feature selection based on correlation for classification in the SVM algorithm with 10-fold cross-validation show an increase in accuracy of 0.5%. The classification of the vector machine support algorithm in the diagnosis of chronic kidney disease produces an accuracy of 99.25%, and after applying discretization and correlation-based feature selection, produces an accuracy of 99.75%. Implementation of discretion and correlation-based feature selection to optimize support vector machine for diagnosis of chronic kidney disease has increased accuracy by 0.5%. The proposed method is feasible as a method of diagnosing chronic kidney disease.
MENINGKATKAN KEMAMPUAN MEMECAHKAN MASALAH BAGI MAHASISWA PGMIPABI DALAM PERKULIAHAN TELKURMAT-2 MELALUI PENERAPANMIND-MAPPING BERCIRI KONSERVASI Amin Suyitno; Endang Sugiharti
Jurnal Penelitian Pendidikan Vol 30, No 1 (2013): April 2013
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jpp.v30i1.5661

Abstract

Ability to solve problems for students of PGMIPABI Programin Analysis of Mathematics Curriculum 2 stillneeds to be improved.One way of it istoimplementof Mind Mapping based-on Conservationthattrain studentsfor independent study, creatitive, and get to knowthe environment by themselves.The problem ishow to improveproblem-solving abilityfor studentsof PGMIPABIof MathematicsEducation Study Program of UNNES, especiallyin the Analysis of Mathematics Curriculum 2 lecturing. The purposeof this researchis to improve problem-solving abilityfor studentsof PGMIPABIof MathematicsEducation Study Program of UNNES, especiallyin the Analysis of Mathematics Curriculum 2 lecturing.The resultsand conclusionsare asfollows.By applyingof Mind Mapping based-onConservation thenproblem-solving skillsfor studentsof PGMIPABIof MathematicsEducation Study Program of UNNES, especiallyin the Analysis of Mathematics Curriculum 2 lecturing canbe increased. The averagescoreobtained bystudentswas85.6,the averagescorewas higherthanthe averagescore ofthe previous years.The suggestions are (1)development ofapplyingof Mind Mapping based-on Conservation to improve problem-solving abilityfor studentsof PGMIPABIof MathematicsEducation Study Program of UNNES, especiallyin the Analysis of Mathematics Curriculum 2 shouldbe followed. (2)Needafurther research tothe othersubject and learning model base-on conservation.
Alphabet Classification of Sign System Using Convolutional Neural Network with Contrast Limited Adaptive Histogram Equalization and Canny Edge Detection Ahmad Solikhin Gayuh Raharjo; Endang Sugiharti
Scientific Journal of Informatics Vol 10, No 3 (2023): August 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i3.44137

Abstract

Purpose: There are deaf people who have problems in communicating orally because they do not have the ability to speak and hear. The sign system is used as a solution to this problem, but not everyone understands the use and meaning of the sign system, even in terms of the alphabet. Therefore, it is necessary to classify a sign system in the form of American Sign Language (ASL) using Artificial Intelligence technology to get good results.Methods: This research focuses on improving the accuracy of ASL alphabet classification using the VGG-19 and ResNet50 architecture of the Convolutional Neural Network (CNN) method combined with Contrast Limited Adaptive Histogram Equalization (CLAHE) to improve the detail quality of images and Canny Edge Detection to produce images that focus on the objects in it. The focused result is the accuracy value. This study uses the ASL alphabet dataset from Kaggle.Result: Based on the test results, there are three best accuracy results. The first is using the ResNet50 architecture, CLAHE, and an image size of 128 x 128 pixels with an accuracy of 99.9%, followed by the ResNet50 architecture, CLAHE + Canny Edge Detection, and an image size of 128 x 128 pixels with an accuracy of 99.82 %, and in third place are the VGG-19 architecture, CLAHE, and an image size of 128 x 128 pixels with an accuracy of 98.93%.Novelty: The novelty of this study is the increase in the accuracy value of ASL image classification from previous studies.
Co-Authors Abas Setiawan Adha, Nugraha Saputra Adi, Pungky Tri Kisworo Adi, Pungky Tri Kisworo Afifah, Eka Nur Afifah, Eka Nur Ahmad Solikhin Gayuh Raharjo Al Hakim, M. Faris Alamsyah - Amin Suyitno Anggara, Dian Christopher Anggyi Trisnawan Putra Arief Broto Susilo Astuti, Winda Try Astuti, Winda Try Asyrofiyyah, Nuril Atikah Ari Pramesti, Atikah Ari Auni, Ahmad Ramadhan Budi Prasetiyo, Budi Choirunnisa, Rizkiyanti Clarissa Amanda Josaputri, Clarissa Amanda Devi, Feroza Rosalina Devi, Feroza Rosalina Dian Tri Wiyanti Dwijanto Dwijanto, Dwijanto Dwika Ananda Agustina Pertiwi Fitriana, Erma Nurul Florentina Yuni Arini, Florentina Yuni Hani'ah, Ulfatun Hariyanto, Abdul Heryadi, Muhammad Heri Isa Akhlis Juliater Simamarta Jumanto Unjung Korzhakin, Dian Alya Krida Singgih Kuncoro Kurniawati, Putri Aida Nur Lestari, Dewi Indah Listiana, Eka Malisan, Johny Maulidia Rahmah Hidayah, Maulidia Rahmah Much Aziz Muslim Much Aziz Muslim Muhammad Kharis Mulyono Mulyono Mutiara Hernowo Muzayanah, Rini Nofrisel, Nofrisel Oktaria Gina Khoirunnisa Perbawawati, Anna Adi Perbawawati, Anna Adi Pipit Riski Setyorini Pradana, Dany Pradhana, Fajar Eska Purnamasari, Ratnaningtyas Widyani Ratri Rahayu Riza Arifudin Rizki Danang Kartiko Kuncoro Rofik Rofik, Rofik Rupiah, Siti S.Pd. M Kes I Ketut Sudiana . Sampurno, Global Ilham Sampurno, Global Ilham Sari, Firar Anitya Sekarwati Ariadi, Tiara Subarkah, Agus Sukestiyarno Sukestiyarno Sukmadewanti, Irahayu Sukmadewanti, Irahayu Sulis Eli Triliani, Sulis Eli Supriyono Supriyono Susanti, Eka Lia Sutarti, Sri Sutarti, Sri Umi Latifah Vedayoko, Lucky Gagah Vedayoko, Lucky Gagah Whisnu Ulinnuha Setiabudi, Whisnu Ulinnuha Wijaya, Henry Putra Imam Zaaidatunni'mah, Untsa Zaenal Abidin