Article Per Year (5 Year)
p-Index From 2021 - 2026
1.376
P-Index
This Author published in this journals
All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmu Komputer dan Informasi Jurnal Teknik Elektro Jurnal Teknologi Informasi dan Ilmu Komputer Edu Elektrika Journal Edu Komputika Journal Innovative Journal of Curriculum and Educational Technology Jurnal Teknologi dan Sistem Komputer IJIE (Indonesian Journal of Informatics Education) Unnes Journal of Mathematics Education Research Jurnal Abdi Insani Journal of Research and Educational Research Evaluation Journal of Vocational and Career Education Prosiding Seminar Nasional Pascasarjana Jurnal Sistem Informasi Jurnal Informatika Polinema (JIP)
Hari Wibawanto
Jurusan Teknik Elektro, Fakultas Teknik, Universitas Negeri Semarang
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics

Published : 62 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 62 Documents
Search

 3   4   5   6   7 
Identifikasi Citra Massa Kistik Berdasar Fitur Gray-Level Co-Occurrence Matrix Hari Wibawanto; Adhi Susanto; Thomas Sri Widodo; S. Maesadji Tjokronegoro
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2008
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

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

Abstract

We have studied the effectiveness of using texture features derived from gray-level co-occurrence matrix(GLCM) matrices for classification of cystic mass and non-cystic mass in ultra sonograms. Twenty-three (23)region of interest (ROIs) containing cystic masses and fifty-five (55) non-cystic masses were extracted from ultrasonogram for this study. For each ROI of 50x50 pixels, seven features (energy, inertia, entropy, homogeneity,maximum probability, inverse difference moment, and correlation) were calculated. The importance of eachfeature in distinguishing cystic masses from non-cystic masses was determined by linear discriminant analysiswith SPSS version 11.5 program. As a result of a study, it was found that all seven features can distinguishingcystic masses from non-cystic masses with an accuracy about 91 %-92.3%. Those levels of accuracy also foundwhen two features (energy and inverse difference moment) was excluded from analysis. The result demonstratethe feasibility of using texture features based on GLCM for distinguishing cystic masses from non-cystic massesof ultra sonogram .Keywords: Gray-level Co-occurrence Matrix Ultrasonografi, massa kistik, fitur tekstur, analisis tekstur, analisisdiskriminan
Identifikasi Citra Massa Kistik Berdasar Fitur Graylevel Co Occurrence Matrix Hari Wibawanto; Adhi Susanto; Thomas Sri Widodo; S. Maesadji Tjokronegoro
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2009
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

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

Abstract

We have studied the effectiveness of using texture features derived from gray-level co-occurrence matrix(GLCM) matrices for classification of cystic mass and non-cystic mass in ultra sonograms. Twenty-three (23)region of interest (ROIs) containing cystic masses and fifty-five (55) non-cystic masses were extracted from ultrasonogram for this study. For each ROI of 50x50 pixels, seven features (energy, inertia, entropy, homogeneity,maximum probability, inverse difference moment, and correlation) were calculated. The importance of eachfeature in distinguishing cystic masses from non-cystic masses was determined by linear discriminant analysiswith SPSS version 11.5 program. As a result of a study, it was found that all seven features can distinguishingcystic masses from non-cystic masses with an accuracy about 91 %-92.3%. Those levels of accuracy also foundwhen two features (energy and inverse difference moment) was excluded from analysis. The result demonstratethe feasibility of using texture features based on GLCM for distinguishing cystic masses from non-cystic massesof ultra sonogram .Keywords: Gray-level Co-occurrence Matrix Ultrasonografi, massa kistik, fitur tekstur, analisis tekstur, analisisdiskriminan
Sistem pengenalan wajah dengan algoritme PCA-GA untuk keamanan pintu rumah pintar menggunakan Rasberry Pi Subiyanto Subiyanto; Dina Priliyana; Moh. Eki Riyadani; Nur Iksan; Hari Wibawanto
Jurnal Teknologi dan Sistem Komputer Volume 8, Issue 3, Year 2020 (July 2020)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2020.13590

Abstract

Genetic algorithm (GA) can improve the classification of the face recognition process in the principal component analysis (PCA). However, the accuracy of this algorithm for the smart home security system has not been further analyzed. This paper presents the accuracy of face recognition using PCA-GA for the smart home security system on Raspberry Pi. PCA was used as the face recognition algorithm, while GA to improve the classification performance of face image search. The PCA-GA algorithm was implemented on the Raspberry Pi. If an authorized person accesses the door of the house, the relay circuit will unlock the door. The accuracy of the system was compared to other face recognition algorithms, namely LBPH-GA and PCA. The results show that PCA-GA face recognition has an accuracy of 90 %, while PCA and LBPH-GA have 80 % and 90 %, respectively.
The management of On-the-job training through web-based application at Vocational High School (SMK) in network computer engineering majors Tito Suryono; Hari Wibawanto; Samsudi Samsudi
IJIE (Indonesian Journal of Informatics Education) Vol 2, No 1 (2018): IJIE (Indonesian Journal of Informatics Education)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijie.v2i1.18594

Abstract

Multiple system education in SMK through On-the-job training is an effort to increase graduate quality in industrial capability. The stages of this research are data collection stage (introduction), system development stage, and evaluation phase (testing). This study, which is research and development, aims to know the feasibility and practicality of the design of web-based applications.The research was conducted at State Vocational High School (SMK Negeri) Jumantono Karanganyar particularly in majors of network computer engineering which involved 12 students of small trial group and 109 students of large-scale test.The data collection method used was observation, documentation, and questionnaire. The data obtained were then analyzed by descriptive analysis technique. The result of black box test done by using 43 items was in accordance with its function. The application expert's validation of this research was 88% meaning that it was very reasonable criteria. Meanwhile, the validation of substance was 89% meaning that it was very feasibleThe result of the usability test for the small-scale group was 68% then, it was improved and tested on a large scale that resulted 85% and was considered as practical. Thus, it can be concluded that the development of web-based On-the-job training management applications is very feasible and practical to be used On-the-job training management in SMK. It is suggested that the use of On-the-job training applications must be intensified.
Web-based Application for Cancerous Object Segmentation in Ultrasound Images Using Active Contour Method Dwi Oktaviyanti; Anan Nugroho; Hari Wibawanto; Subiyanto
Jurnal Sistem Informasi Vol. 19 No. 2 (2023): Jurnal Sistem Informasi (Journal of Information System)
Publisher : Faculty of Computer Science Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21609/jsi.v19i2.1280

Abstract

Segmentation, or the process of separating clinical objects from surrounding tissue in medical images, is an important step in the Computer-Aided Diagnosis (CAD) system. The CAD system is developed to assist radiologists in diagnosing cancer malignancy, which in this research is found in ultrasound (US) medical imaging. The manual segmentation process, which cannot be accessed remotely, is a limitation of the CAD system because cancer objects are screened frequently, continuously, and at all times. Therefore, this research aims to build a user-friendly web application called COSION (Cancerous Object Segmentation) that provides easy access for radiologists to segment cancer objects in US images by adopting an active contour method called HERBAC (Hybrid Edge & Region-Based Active Contour). The waterfall method was used to develop the web application with Django as the web framework. The successfully built web application is named Cosion. Cosion was tested on 114 radiology breast and thyroid US images. Functional, portability, efficiency, reliability, expert validation, and usability testing concluded that Cosion runs well and is suitable for use with a functionality value of 0.9375, an average GTmetrix score of 96.43±0.66%, 100% stress testing percentage, 77.5% expert validation, and 75.8% usability. These quantitative performances indicate that the COSION web application is suitable for implementation in the CAD system for US medical imaging.
Pelatihan Google Classroom Menggunakan Model ADDIE Untuk Guru Sekolah Dasar Dewi Ayu Sulistyaningrum; Hari Wibawanto; Eko Purwanti
Prosiding Seminar Nasional Pascasarjana Vol. 5 No. 1 (2022)
Publisher : Pascasarjana Universitas Negeri Semarang

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

Abstract

Pada masa ini terjadinya pendemi Covid-19 yang menyebabkan dampak sangat besar kehidupan termasuk bidang pendidikan. Maka terjadinya penutupan sekolah dan pemerintah mengeluarkan surat edaran yang berisi masa perahlian dengan melakukan pembelajaran daring. Namun proses pembelajaran daring terdapat kendala yang menyebabkan proses pembelajatan tidak efektif. Tujuan dari penelitian adalah meningkatan kompetensi guru pada pengetahuan dan kreatifitas proses pembelajaran daring dengan melakukan pelatihan bagi guru sekolah dasar menggunakan platfrom Google Classroom. Metode penelitian ini menggunakan pengembangan Research and Development desain model ADDIE Analysis, Design, Development, Implementation, and Evaluation. Hasil pelatihan pembelajaran daring google classroom dapat meningkatkan kompetensi guru terhadap pembelajaran daring, model pelatihan ADDIE layak digunakan berdasarkan hasil validasi ahli materi dengan 4,7 kretria sangat layak, dan hasil validasi ahli materi dengan rata-rata 4,7 kriteria sangat layak, berdasarkan hasil reponden peserta pelatihan dengan 4,3 dengan kreteria sangat layak. Untuk keefektifan model pelatihan dengan melakukan pretest mendapatkan 55,38 kretria cukup sedangkan posttest mendapatkan 85,54 kreteria sangat layak. Sehingga model pelatihan google classroom sangat efektif sebagai media pelatihan bagi guru meningkatkan kompetensi guru.
SIMPLIFIKASI MODEL CV BERPADU OPERASI MORFOLOGI UNTUK DETEKSI OBJEK KANKER PADA CITRA USG Anan Nugroho; Anas Fauzi; Budi Sunarko; Hari Wibawanto; Nur Iksan
Jurnal Informatika Polinema Vol. 8 No. 2 (2022): Vol 8 No 2 (2022)
Publisher : UPT P2M State Polytechnic of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jip.v8i2.923

Abstract

Saat ini, Computer Aided Diagnosis (CAD) tengah dikembangkan secara masif sebagai second opinion reader di berbagai modalitas pencitraan medis, salah satunya ultrasonografi (USG). Untuk skrining otomatis citra USG yang banyak, berulang-ulang dan terus-menerus, teknik deteksi objek memainkan peran krusial pada sistem CAD. Deteksi objek kanker pada citra USG tidak mudah karena objek-objek tersebut berkontras rendah dan bertepi kabur akibat gangguan derau speckle dan artifak. Studi ini mengatasi tantangan ini dengan mengusulkan metode deteksi berbasis model active-contour Chan-Vese (CV) tersimplifikasi diikuti operasi morfologi. Adapun performa kuantitatif diperoleh menggunakan skor Intersection of Union (IoU) antara objek-objek terdeteksi dengan ground truth-nya. Usulan metode divalidasi menggunakan 20 citra USG tiroid dan payudara dengan hasil rerata skor IoU mencapai 92,36%. Performa yang menjanjikan ini menunjukkan bahwa usulan metode layak diimplementasikan pada sistem CAD.
Segmentasi Objek Citra Ultrasonografi Terotomatisasi Menggunakan Metode Aktif Kontur Kombinatorial Nugroho, Anan; Sunarko, Budi; Wibawanto, Hari; Mulwinda, Anggraini; Fauzi, Anas; Oktaviyanti, Dwi; Savitri, Dina Wulung
Jurnal Teknologi dan Sistem Komputer [IN PRESS] Volume 11, Issue 1, Year 2023 (January 2023)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2023.14712

Abstract

Active Contour (AC) merupakan algoritme yang banyak digunakan dalam melakukan segmentasi dalam mengembangkan sistem Computer Aided Diagnosis (CAD) pada pencitraan USG. Namun metode yang berkembang masih bersifat interaktif yang menyebabkan human error serta adanya berbagai masalah akibat inhomogenitas pada citra Ultrasonografi (USG) seperti leakage, terjadinya false area serta local minima. Pada studi ini dikembangkan metode segmentasi objek otomatis pada citra USG untuk membantu radiolog dalam proses diagnosis yang efisien. Metode yang dikembangkan disebut Automatic Combinatorial Active Contour (ACAC) yang mengkombinasikan turunan simplifikasi model global region-based CV (Chan-Vese) dan improved-GAC (Geodesic Active Contour) untuk segmentasi lokal. Hasil studi dengan 50 dataset yang diuji coba yaitu didapatkannya nilai accuracy sebesar 98.83%, precission 95.26%, sensitivity 86.58%, specificity 99.63%, similarity 90.58%, dan IoU 82.87%. performa kuantitatif ini membuktikan bahwa metode ACAC layak diimplementasikan pada sistem CAD yang lebih efisien dan akurat.
Implementasi Metode Backpropogation dengan Inisialisasi Bobot Nguyen Widrow untuk Peramalan Harga Saham Kurniawan, Eliv; Wibawanto, Hari; Widodo, Djoko Adi
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 6 No 1: Februari 2019
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2898.248 KB) | DOI: 10.25126/jtiik.201961904

Abstract

Jaringan saraf tiruan merupakan suatu ilmu yang terus berkembang pesat hingga saat ini. Jaringan saraf tiruan merupakan suatu ilmu komputasi yang didasarkan dan terinspirasi dari cara kerja sistem saraf manusia. Sama halnya dengan sistem saraf manusia, jaringan saraf tiruan bekerja melalui proses pembelajaran terhadap data-data yang sudah ada untuk memformulakan keluaran dari data-data baru. Jaringan saraf tiruan dengan metode backpropagation mampu melakukan peramalan untuk data nonlinear seperti bentuk data harian harga saham. Salah satu algoritma inisialisasi bobot yang dapat meningkatkan waktu eksekusi adalah nguyen-widrow. Pada penelitian ini akan dilakukan implementasi metode backpropagation dengan inisialisasi bobot nguyen widrow untuk meramalkan harga saham. Proses implementasi melalui 3 tahapan, yaitu preprosesing data, pelatihan jaringan, dan pengujian jaringan. Hasil dari penelitian ini menunjukkan bahwa pelatihan jaringan saraf tiruan dengan jumlah dataset yang banyak membutuhkan perhitungan yang kompleks, sehingga jaringan saraf tiruan dengan arsitektur jaringan yang sederhana kurang efektif dan dapat terjebak pada titik lokal minimum. Hasil peramalan untuk harga close saham BBCA.JK memiliki nilai MAPE 0,85% dan untuk harga close saham AALI.JK memiliki nilai MAPE sebesar 1,84%.AbstractArtificial neural network is a hot topic and invite a lot of admiration in the last decade. Artificial Neural Network is one of the artificial representations of the humans brain who always try to simulate the learning process of the humans brain. Artificial neural network with backpropagation method is able to forecast nonlinear data such as daily data form stock price. One of the weight initialization algorithms that can be increase the execution time is nguyen-widrow. In this research will be implemented backpropagation method with nguyen widrow weight initialization to forecast stock prices. The process of implementation through 3 stages, that is preprosesing data, training, and testing or simulate. The results of this research indicate that the training of artificial neural networks with many datasets required a complex calculations, so the artificial neural network with simple architectures is less effective and can get stuck at minimum local points. The results forecasting for the close price of BBCA.JK have a MAPE value 0.85% and for the close price of AALI.JK have 1.84% of MAPE value
Pengembangan Mobile Learning berbasis Android pada Mata Pelajaran Rekayasa Perangkat Lunak di SMK Sultan Trenggono Kota Semarang Wulandari, Dania Ayu; Wibawanto, Hari; Suryanto, Agus; Murnomo, Agus
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 6 No 5: Oktober 2019
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (76.47 KB) | DOI: 10.25126/jtiik.201965994

Abstract

Perkembangan jumlah pengguna smartphone sudah merambah di kalangan siswa. Hal ini dapat dimanfaatkan sebagai media pendukung proses pembelajaran. Penggunaan media merupakan salah satu komponen metode untuk mencapai tujuan pembelajaran. Berdasarkan observasi di SMK Sultan Trenggono Kota Semarang, media pembelajaran masih terbatas pada slide show power point yang monoton, e-book, dan LKS (Lembar Kerja Siswa) atau buku-buku teks lainnya yang dinilai kurang memenuhi kelayakan. Penelitian ini bertujuan untuk mengetahui: (1) pengembangan media, (2) kelayakan media dan; (3) penilaian kemudahan dan kemanfaatan penggunaan media oleh siswa dan guru. Mobile learning didefinisikan sebagai model pembelajaran menggunakan perangkat IT (information technology) genggam dan bergerak. Model pengembangan yang digunakan adalah 4-D (Four D Models), yaitu: define (pendefinisian), design (perancangan), develop (pengembangan), dan disseminate (penyebaran). Berdasarkan penilaian kelayakan oleh validator media menunjukkan bahwa: aplikasi mendapat penilaian sebesar 86,93% dari ahli media dan 87% dari ahli materi. Sedangkan hasil uji coba menunjukkan nilai kemudahan dan kemanfaatan penggunaan aplikasi sebesar 87,5% oleh guru dan 82,27% oleh siswa. Hal ini menunjukkan bahwa media sangat layak untuk digunakan, mudah, dan bermanfaat dalam proses pembelajaran. AbsctractThe growth number of smartphone users has penetrated among the students. This can be used as a supporting media of the learning process. The use of media is one component method to achieve learning objectives. Based on the observations at SMK Sultan Trenggono Kota Semarang, the learning media is still limited to the monotonous power point slide show, e-book, and LKS (student worksheet) or other textbooks that are considered less feasibile. This study aims to determine: (1) media development, (2) media feasibility, and (3) assessment of ease and usefulness of media usage by students and teachers. Mobile learning is defined as a learning model using IT (information technology) handheld and mobile devices. The development model used is 4-D (Four D Models), which are: define, design, develop, and disseminate. Based on the feasibility assessment by the media validator shows that: the application received an assessment is 86.93% of media experts and 87% of material experts. While the test results show the value of ease and usefulness of application usage is 87.5% by teachers and 82.27% by students. This shows that the media is very feasible to use, easy, and useful in the learning process.
Co-Authors - Kustiono -, Widya A Tri Widodo Achsin, Muchammad Achsin Adhi Susanto Agus Murnomo Agus Suryanto Alfa Faridh Suni Amat Basir, Amat Anan Nugroho Anan Nugroho Anggraini Mulwinda Anita, Yopi Arfriandi, Arief Aris Munandar Budi Sunarko Budiarso, Alfian Budiarso, Alfian Dewi Ayu Sulistyaningrum Dharu Wihartasih, Dharu Dina Priliyana Djoko Widodo Dwi Oktaviyanti Dwi Oktaviyanti, Dwi Eko Purwanti Eko Saputro, Eko Eko Supraptono Esti Rahmawati, Esti FAUZI, ANAS Firyomanto, Firyomanto Hapsari, Widya Haryono Haryono I Made Sudana Ika Umaya Sinta, Ika Umaya Indaryanto, Faizal Juliantri, Luqman Azhar Juliantri, Luqman Azhar Kartono - Khairun Nisa Meiah Ngafidin Kurniawan, Eliv Lestari, Ria Rosita M Asysyifaul Firdaus Mahanani, Fauzan A Mariam, Metta Mikha Bimantara Warsito, Mikha Bimantara Moh. Eki Riyadani Muhammad Khumaedi Muhammad Yan Eka Adiptya Noor, Muhammad Elfin Noor, Muhammad Elfin Nugroho, Anan Nur Iksan Nur Laely Fatimah, Nur Laely Puji Astuti Rais Alfian Ansharullah, Rais Alfian Rodia Syamwil S. Maesadji Tjokronegoro Samsudi Samsudi Savitri, Dina Wulung Slamet Seno Adi Subiyanto Sumianingrum, Ninok Eyiz Sumianingrum, Ninok Eyiz Susilo, Dwi Budi Syarifudin, Muhammad Nanda Tatyantoro Andrasto Thomas Sri Widodo Tito Suryono Totok Sumaryanto Florentinus, Totok Sumaryanto Usman Channy Affandi, Usman Channy Wahyu Hardyanto Wibowo, Hilal Aji Wibowo, Hilal Aji Widya Puji Astuti, Widya Puji Wiji Wahyudi, Urip Muhayat Wiji Wahyudi, Urip Muhayat Windrajaya, Eko Rudy Wiwik Handayani Wulandari, Dania Ayu