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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Advances in Applied Sciences Media Kesehatan Masyarakat Indonesia BERKALA FISIKA MATEMATIKA SAINS DAN MATEMATIKA JURNAL SISTEM INFORMASI BISNIS YOUNGSTER PHYSICS JOURNAL Jurnal Sistem Komputer Telematika : Jurnal Informatika dan Teknologi Informasi Speed - Sentra Penelitian Engineering dan Edukasi Jurnal Teknologi Informasi dan Ilmu Komputer Jurnas Nasional Teknologi dan Sistem Informasi Jurnal Imejing Diagnostik Register: Jurnal Ilmiah Teknologi Sistem Informasi Jurnal Manajemen Kesehatan Indonesia Jurnal Teknologi dan Sistem Komputer Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal Of Vocational Health Studies Jurnal Penelitian Pendidikan IPA (JPPIPA) Syntax Literate: Jurnal Ilmiah Indonesia Jurnal Teknoinfo Journal of Physics and Its Applications Jurnal Sisfokom (Sistem Informasi dan Komputer) JURTEKSI Unnes Journal of Public Health Jurnal Komunika : Jurnal Komunikasi, Media dan Informatika JARES (Journal of Academic Research and Sciences) Jurnal Manajemen Informasi Kesehatan Indonesia (JMIKI) Journal of Electronics, Electromedical Engineering, and Medical Informatics Journal of Information Systems and Informatics Jurnal Teknik Elektro dan Komputasi (ELKOM) Indonesian Journal of Electrical Engineering and Computer Science Jurnal Aisyah : Jurnal Ilmu Kesehatan Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Media Publikasi Promosi Kesehatan Indonesia (MPPKI) Jurnal Multidisiplin Madani (MUDIMA) East Asian Journal of Multidisciplinary Research (EAJMR) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Prisma Sains: Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram Makara Journal of Technology International Journal Of Health And Social Behavior
Kusworo Adi
Jurusan Fisika, Fakultas Sains Dan Matematika, Universitas Diponegoro Jl. Prof. Soedharto, SH., Tembalang, Semarang, Jawa Tengah
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Journal : JURNAL SISTEM INFORMASI BISNIS

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Sistem Deteksi Retinopati Diabetik Menggunakan Support Vector Machine Setiawan, Wahyudi; Adi, Kusworo; Sugiharto, Aris
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 2, No 3 (2012): Volume 2 Nomor 3 Tahun 2012
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (928.963 KB) | DOI: 10.21456/vol2iss3pp109-116

Abstract

Diabetic Retinopathy is a complication of Diabetes Melitus. It can be a blindness if untreated settled as early as possible. System created in this thesis is the detection of diabetic retinopathy level of the image obtained from fundus photographs. There are three main steps to resolve the problems, preprocessing, feature extraction and classification. Preprocessing methods that used in this system are Grayscale Green Channel, Gaussian Filter, Contrast Limited Adaptive Histogram Equalization and Masking. Two Dimensional Linear Discriminant Analysis (2DLDA) is used for feature extraction. Support Vector Machine (SVM) is used for classification. The test result performed by taking a dataset of MESSIDOR with number of images that vary for the training phase, otherwise is used for the testing phase. Test result show the optimal accuracy are 84% .   Keywords : Diabetic Retinopathy, Support Vector Machine, Two Dimensional Linear Discriminant Analysis, MESSIDOR
Sistem Identifikasi Biometrika Wajah Menggunakan Metode Gabor KPCA dan Mahalanobis Distance Kurniawan, Dwi Ely; Adi, Kusworo; Rohim, Adian Fatchur
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 2, No 1 (2012): Volume 2 Nomor 1 Tahun 2012
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (516.973 KB) | DOI: 10.21456/vol2iss1pp006-010

Abstract

Sistem  biometrika  pengenalan  wajah  merupakan  pengembangan  metode  dasar  sistem  autentifikasi  dengan  menggunakan  karakteristik alami  wajah  sebagai  basisnya.  Pendekatan  sistem  identifikasi  merupakan  pengenalan  wajah  seseorang  dengan  mencari  keseluruhan template dalam database untuk pencocokan karakteristik satu ke banyak (1:M). Sistem biometrika pada penelitian ini dibagi menjadi dua tahap  pemasukan  data  (enrollment)  dan  pencocokan  ciri  (matching).  Sistem  mengakuisisi  wajah  dengan  beberapa  posisi  sudut, pencahyaan dan ekspresi yang berbeda-beda. Citra wajah hasil dari akuisisi, diekstraksi menggunakan metode Gabor KPCA  (8x5 filter) untuk  didaftarkan  ke  dalam  database  sebagai  tahap  enrollment  citra  wajah  dan  tahap  selanjutnya  pencocokan  ciri  (matching)  denganmelakukan  pengukuran  jarak  antara  citra  uji  dengan  citra  database  wajah  menggunakan  Mahalanobis  Distance.  Penelitian  ini menggunakan  database  citra  wajah  AT&T  Face  dengan  sampel  40  orang  dan  10  posisi  wajah.  Hasil  penelitian  menunjukkan  bahwa sistem biometrika yang dikembangkan dapat mengenali wajah dengan tingkat akurasi mencapai 97.5%.Keywords : Identifikasi, Filter Gabor, KPCA, Mahalanobis Distance
Implementasi Metode Promethee Dan Borda Dalam Sistem Pendukung Keputusan Pemilihan Lokasi Pembukaan Cabang Baru Bank Apriliani, Dyah; Adi, Kusworo; Gernowo, Rachmat
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 5, No 2 (2015): Volume 5 Nomor 2 Tahun 2015
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (710.309 KB) | DOI: 10.21456/vol5iss2pp145-150

Abstract

The selection of a new branch bank location is crucial to the success of the bank in the future. The object of this research is BMT Muamalat. PROMETHEE method is used to manage individual decision of each decision makers, while Borda method is used to manage group decisions of PROMETHEE method in ranking the results. The use of these two methods is one solution to produce a more objective group decision. Ranked of alternative location have appropriated with the opening rules of the new branches of BMT Muamalat. As for the variables in this study are criminality, facilities and infrastructures, per capita income, economic growth, population, and the number of competitors around the alternative location of a new branch. The results of this research is Banyuputih as the best alternative location.  
Prediksi Harga Saham Harian Menggunakan Jaringan Syaraf Tiruan (JST) Dengan Algoritma Propagasi Balik Purwanto, Purwanto; Adi, Kusworo
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 3, No 3 (2013): Volume 3 Nomor 3 Tahun 2013
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol3iss3pp

Abstract

Prediksi harga saham berguna bagi investor untuk memahami bagaimana investasi masuk dalam suatu organisasi di masa depan. Prediksi dapat mengantisipasi fluktuasi harga saham dan juga dapat membantu investor untuk membuat keputusan. Jaringan Syaraf Tiruan (JST) menyediakan cara yang cepat dan fleksibel untuk memprediksi harga saham, dan menunjukkan hasil yang baik dibandingkan dengan metode konvensional. Algoritma yang digunakan untuk prediksi saham adalah backpropagation dengan model data time series. Algoritma ini merupakan metode pelatihan terawasi yang berfungsi untuk meminimalkan error pada output yang dihasilkan oleh jaringan. Hasil penelitian ini menunjukkan bahwa hasil optimal yang diperoleh dari Jaringan Syaraf Tiruan adalah menggunakan kombinasi fungsi aktivasi Logsig-Purelin, dengan tingkat nilai Mean Absolute Percentage Error (MAPE) adalah 2.43% dan nilai koefesien korelasinya adalah  94.08%, sehingga algoritma ini layak dan efektif untuk prediksi harga saham.   Kata kunci : Jaringan Syaraf Tiruan, Backpropagation, Peramalan, Harga Saham, Time Series
Support Vector Machine Untuk Klasifikasi Citra Jenis Daging Berdasarkan Tekstur Menggunakan Ekstraksi Ciri Gray Level Co-Occurrence Matrices (GLCM) Neneng, Neneng; Adi, Kusworo; Isnanto, Rizal
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 6, No 1 (2016): Volume 6 Nomor 1 Tahun 2016
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3977.488 KB) | DOI: 10.21456/vol6iss1pp1-10

Abstract

Texture is one of the most important features for image analysis, which provides informations such as the composition of texture on the surface structure, changes of the intensity, or brightness. Gray level co-occurence matrix (GLCM) is a method that can be used for statistical texture analysis. GLCM has proven to be the most powerful texture descriptors used in image analysis. This study uses the four-way GLCM 0o, 45o, 90o, and 135o. Support vector machine (SVM) is a machine learning that can be used for image classification. SVM has a high generalization capability without any requirement of additional knowledge, even with the high dimension of the input space. The data used in this study are the image of goat meat, buffalo meat, horse meat, and beef with shooting distance 20 cm, 30 cm and 40 cm. The result of this study shows that the best recognition rate of 87.5% was taken at a distance of 20 cm with neighboring pixels distance d = 2 in the direction GLCM 135o.
Evaluasi Implementasi Radiology Information System Picture Archiving and Communication System (RISPACS) dengan Pendekatan Model HOT-FIT Suandari, Putu Vierda Lya; Adi, Kusworo; Suryawati, Chriswardani
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 9, No 1 (2019): Volume 9 Nomor 1 Tahun 2019
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (77.48 KB) | DOI: 10.21456/vol9iss1pp55-62

Abstract

The application of current technology such as the Radiology Information System Picture Archiving and Communication System (RISPACS) in radiology that doesn’t meet the user’s expectation can raise the inconvenience and affect their productivity. To anticipate this, it is important to understand the basic factors that contribute to the reception and successfulness of applicating RISPACS. This study aims to describe the evaluation of the successful implementation of RISPACS using the Human Organization Technology (HOT FIT) model approach in Radiology Installation at Sanglah Hospital Denpasar. The data in this research were analyzed by Partial Least Square (PLS) test and measuring 71 radiologists as respondents who use RISPACS. The evaluation results of the Human Organization Technology (HOT FIT) model show that the successful implementation of RISPACS technology has a positive assessment that is seen from the user's attitude in responding to a RISPACS technology that is felt to be in accordance with the expectations and operational needs of the user. Variable of system quality, information quality, service quality have a positive influence on system user variable and user satisfaction. While the variable of system users, user satisfaction, organizational structure, and organizational environment had a positive and significant effect by the t-statistic value of >1,96.
Sistem Pemilihan Perumahan dengan Metode Kombinasi Fuzzy C-Means Clustering dan Simple Additive Weighting Jaya, Tri Sandhika; Adi, Kusworo; Noranita, Beta
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 1, No 3 (2011): Volume 1 Nomor 3 Tahun 2011
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (455.072 KB) | DOI: 10.21456/vol1iss3pp153-158

Abstract

Housing is one of human secondary needs. In selecting the most appropriate housing, there are lots of aspects to be considered to satisfy the costumers  want. In order to get optimal result, a system is needed to help the costumers to decide which housing fit them   most. System that will be built in this thesis is a system that supports costumers’ satisfaction in housing selection. There are 2 main stages in the  system,  namely  data  grouping  and  ranking.  Data  grouping  method  used  is  Fuzzy  C -Means  Clustering  (FCM).  Simple  Additive Weighting (SAW) is used for ranking purpose. Testing is carried out by comparing  interview result with system counting result. The testing result produces 9 cases that derive similar recommendation.Keywords : Housing selection; FCM; SAW; Recommendation; Grouping
Penilaian Kinerja Pegawai Lingkungan Perguruan Tinggi dengan Metode Topsis Setyadi, Ary; Adi, Kusworo; Sugiharto, Aris
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 2, No 3 (2012): Volume 2 Nomor 3 Tahun 2012
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (559.616 KB) | DOI: 10.21456/vol2iss3pp139-145

Abstract

Employee performance measurement is very important for evaluation and future planning. Most of the government and private agencies are still using Daftar Penilaian Pelaksanaan Pekerjaan (DP3) to assess the performance their employees. DP3 goal is to obtain an objective consideration to employee development and career system based on job performance, formally it used to be a principal consideration material of periodic salary increases and promotions. In this research made ​​a Decision Support System (DSS) for employee performance appraisal DP3 at the college by using TOPSIS method. In this DSS ​​of which there are eight criteria in the DP3, everything is broken down into several sub criteria to get more objective assessment. Initial input of the TOPSIS method is obtained through a calculation using the AHP to find the eigen value of each criterion and the intensity. System created to describe the process of AHP and TOPSIS at each step in a matrix  that can be studied and evaluated the truth of each step in the method used. In testing, this system  is quite effective in the calculation that uses looping and selection. Keywords: TOPSIS, employee performance evaluation, DP3
Jaringan Syaraf Tiruan Perambatan Balik Untuk Pengenalan Wajah Saubari, Nahdi; Isnanto, Rizal; Adi, Kusworo
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 6, No 1 (2016): Volume 6 Nomor 1 Tahun 2016
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (865.153 KB) | DOI: 10.21456/vol6iss1pp30-37

Abstract

This research discusses about face detection and face recognition in an image. Face detection has only two classifications, i.e face and not face. Face recognition is compatible with some classifications of a number individuals who want to be recognized. Face detection and face recognition in thi study using Haar-Like Feature method and Artificial Neural Network Backpropagation. A method Haar-Like Feature used for detection and extraction in an image, because the clasification on this method showed success at used to detect image of the face. Artificial Neural Network Backpropagation is a training algorithm that is used to do training simulated on facial image data training stored in a database. This study uses Ms. Excel 2007 as database with 10 individual sample image, every image in each individuals having three distance with every range has four defferent light intensities, so that the data training stored in the database reached 120 data training. The results shows that the face detection and face recognition which is developed can recognize a face image with an average accuracy rate reaches 80,8% for each distance.
Sistem Informasi Penyebaran Penyakit Demam Berdarah Menggunakan Metode Jaringan Syaraf Tiruan Backpropagation Supriyadi, Didi; Adi, Kusworo; Sarwoko, Eko Adi
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 1, No 3 (2011): Volume 1 Nomor 3 Tahun 2011
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (525.341 KB) | DOI: 10.21456/vol1iss3pp159-167

Abstract

Dengue  disease  is  a  major  health  problem  and  endemic  in  several  countries  including  Indonesia.  Indonesia  is  included  in  the  category  "A"  in  the stratification of DHF by WHO in 2001 which indicates the high rate of treatment in hospital and deaths from dengue. The purpose of this study was to investigate the ability of artificial neural networks Backpropagation method for information of the spread of dengue fever in   a region. In this study uses six input variables which are environmental factors that influence the spread of dengue fever, include average temperature  -  average, rainfall, number of rainy days, the population density, sea surface height, and the percentage of larvae-free number for  which data is sourced from BMKG, BPS and the Public Health Service. Network architecture applied to a multilayer network that uses an input with 6 neurons, one hidden lay er and an output with the output neuron is one. From the results obtained by training  the best network architecture is the number one hidden layer with the number of neurons obtained a total of 110 neurons and also the system can recognize the entire training data. The best training algorithm using  a variable learning rate and momentum of 0.9 by 0.6 by the end of the training MSE 0.000999879. in the process of testing using test data obtained 17 tissue levels of  approximately 88.23% accuracy. Therefore we can conclude that the network is implemented in this study when subjected to the test  data other then the error rate of about 11.77%.Keywords : Artificial Neural Networks; Backpropagation; Dengue fever
Co-Authors - Magister Sistem Informasi Universitas Diponegoro, Vincencius Gunawan S.K Abdillah Noor Fajrin Achmad Widodo Adi Pamungkas Adian Fatchur Rohim Adila Safitri Agus Atabik Anwar Agustini, Eka Puji Agvion Virsaw Alfajri, Willy Bima Andrian Bayu Suksmono Andriyan B. Suksmono Andriyan Suksmono Andriyan Suksmono, Andriyan Antono Suryo Putro Apoina Kartini Aprilia Ayu Andarinny Ardhi, Ovide Decroly Wisnu Ari Bawono Putranto Arief Rachman Aris P Widodo Aris Puji Widodo Aris Puji Widodo Aris Sugiharto Ary Setyadi Aryasa, Komang Budi Atik Zilziana Muflihati Noor Baital, Muhammad Sawal Basuki Wibowo Beta Noranita Cahya Tri Purnami Cahya Tri Purnami Carissa Devina Usman Catur Adi Widodo Catur Edi Widodo Chakim Annubaha Choirul Anam Choirul Anam AM Diponegoro Dartini Dartini Dartini Dartini, Dartini Dedi Apriyandi Dedi Sepriana Delfia, Fila Dewi, Adinda Cipta Dian Anggraini Didi Supriyadi Dwi Ely Kurniawan Dwi Rochmayanti Dyah Apriliani Eka Vickraien Dangkua, Eka Vickraien Eko Adi Sarwoko Eko Sediono Elvira Situmorang Esa Prakasa, Esa Evi Setiawati Evita Ayu Suryaningtyas Faikhin . Faisal Rahman Fanny, Nabilatul Fardana, Nouvel Izza Farid Agushybana Farid Farid Agushybana Fatkhurrazi Basyid Figur Humani Fila Delfia Frida Fallo Gatot Murti Wibowo Gatot Murti Wibowo, Gatot Murti Hadyan Arifianto Hariri, Ahmad Harnanto, Rudy Haryati Haryati Hastuti, Dyah Dewi Havez Vazirani Al Kautsar Hendra Gunawan HENDRA GUNAWAN B11211055 Hernowo Danusaputro Ibrahim, Muhammad Rivani Imam Syafii Ircham Ali Isnain Gunadi Isnain Gunadi Jatmiko Endor Suseno Jatmiko Endro Suseno Jatmiko Endro Suseno Jayawarsa, A.A. Ketut Julianto, Dewa Rizki Rahmat Laila Rahmawati Linda Nuryanti M.Irwan Katili Mailia Putri Utami Mailia Putri Utami MAIZZA NADIA PUTR Maratullatifah, Yulaikha MARTINI Martini Martini Mengko, Tati L.R. Muhammad Ikhsan Nahdi Saubari Nanang Sulaksono, Nanang Natalia Kristiani Nava Muzdalifah Nelly Mirnasari Neneng Neneng Nina Dwi Astuti Noor Azizah Nugroho Adhi Santoso Nugroho, Irwan Andriyanto Nur Hamid Nurul Firdausi Nuzula, Nurul Firdausi Nurul Huda Prasetyo Oky Dwi Nurhayati Pamungkas, Ardian Prakasa, Fawwaz Bimo Puji Widodo, Aris Purwanto Purwanto Puspita Sari, Kiki Putri Nuriskianti Qoriani Widayati R Rizal Isnanto Rachmat Gernowo Rachmatullah, Robby Rahmat Gernowo Rahmat Gernowo Rasyid Rasyid, Rasyid Retnaningsih Soeprobowati, Tri Ria Amitasari Rima Ayuning Ratri Riris Trima Derita Sari Rizky Ayomi Syifa Rr. Tony Yulianto Saiful Widianto Salsabila Naqiyah Sari, Kiki Puspita Septya Maharani, Septya Setyowati Setyowati Shahmirul Hafizullah Imanuddin Sidin Hariyanto Sifaunajah, Agus Siti A'isyah Siti Nur Endahyani Sri Bintang Pamungkas Suandari P.V.L Suryono Suryono Suseno, Jatmiko Endor Sutopo Patria Jati Tati Mengko Tati Mengko, Tati Tito Rano Pradibto Toni Wijanarko Adi Putra Tri Mulyono Tri Retnaningsih Soeprobowati Tri Sandhika Jaya Tutur Urip Undari Nurkalis Vincencius Gunawan, Vincencius Vincensius Gunawan S.K. Wahyu Setia Budi Wahyudi Setiawan Wahyuni, Wilda Waliyansyah, Rahmat Robi Weirna Yusanti Wicaksono, Januar Agung Widagdo, Krisan Aprian Wisnu Ardhi, Ovide Decroly Wiwit Agus Triyanto Yuliani Setyaningsih Zaenal Arifin Zaenul Muhlisin Zainal Bachrudin