bluuebunny/crossref_metadata_2025 huggingface dataset:
Laser Beam Melting of Complexly Shaped Honeycomb Structures
Authors: Illgner Matthias , Binder Maximilian , Schlick Georg , Seidel Christian , Reinhart Gunther
Published: August 2020

Laser beam melting (LBM) offers the opportunity to manufacture highly complex structures and geometries and thus provides a big potential to produce lightweight parts. In previous research projects, a software tool has been developed that achieves the placement of hexagonal honeycombs (of any size and wall thickness) on free formed surfaces in a load-oriented manner and thus offers entirely new possibilities for designing lightweight components in CAD (e.g. [1–2]).

This work examines the production of metal hexagonal honeycombs from the material AlSi10Mg with the LBM-process. By adapting the exposure and process parameters, it was possible to manufacture overhanging structures with an overhang angel < 30° (relative to build platform) without support structures, while still achieving an acceptable surface roughness (in the context of this study: Ra = 45 µm). Conventional complex and time consuming post-processing steps can thus be avoided and a higher utilization of building space can be achieved. Furthermore, since the critical size for a lightweight structure is the minimum possible density, it was investigated to which minimum values the wall thicknesses of the hexagonal structures can be reduced using LBM. Apart from that, the stability of the manufactured honeycombs was analyzed in as-built condition and heat treated by pressure test and related to the honeycomb density. This has been used to compare additively manufactured honeycombs with conventionally manufactured ones.
The most filigree structure made by remote laser cutting
Authors: Baumann Robert , Herwig Patrick , Beyer Eckhard
Published: August 2020

It is well known that the global climate change is the largest challenge for the society of the 21th century. In order for us to manage the resulting consequences, innovative materials for energy efficient applications become more and more important. Open cell metal foam contributes promising solutions to the light weight design, battery applications and renewable energy harvesting. Still, challenges are present concerning the cutting into a defined shape. The remote laser cutting offers a solution for decreasing the production costs as well as the needed component accuracy. Our investigations consider that this technique has a high potential concerning cutting speed which was increased by more than 500 %, compared to state of the art laser separation. Next to that, the contour accuracy was improved as well, resulting in tolerances with less than 30 μm. Together with the forceless process of remote laser cutting, the possibility is given to generate filigree components with a wall thickness less than 0.75 pore sizes. This paper offers insight into the viability of remote laser cutting in overcoming the challenges dealing with mechanical milling or grinding. Investigating the process concerning thermal stress input as well as particle attachments will be the next steps in the future.
Bonding Strength of FRP-Metal Hybrids
Authors: Sebastiani Gerd , Pfeifer Sebastian , Röber Lars , Katoh Jun , Yamaguchi Zenzo , Takada Satoru
Published: August 2020

The lightweight credo “the right material in the right place” raises an interesting concern once different materials are meant to provide a watertight bond. Therefore, we investigate the bonding behavior of metals with Fiber-Reinforced-Plastic (FRP) materials. In order to optimize the bond, the major influencing factors and their interactions are studied.In order to identify the above interactions, FRP-metal hybrid specimens were investigated with regard to peel forces and shear strengths. During manufacturing the influencing factors such as sheet metal and FRP type, surface treatments, and bonding processes were varied.Considering the peel force, a thermoset plastic matrix adhesively bonded to steel provided the best results, along with the use of a novel surface etching method by Kobelco. The latter yielded the highest shear strengths within this investigation. No bond could be obtained applying thermoset plastic matrices for in-operandi connections.Using adhesives or surface treatments introduced additional production costs. Hence, in-operandi bonding would be a favorable option, however, one requiring further research. Compared to the material costs, the additional production costs could prove to be insignificant once the bonding process has been properly robustified and automated.
Association Between Public Knowledge About COVID-19, Trust in Information Sources, and Adherence to Social Distancing: Cross-Sectional Survey
Authors: Fridman Ilona , Lucas Nicole , Henke Debra , Zigler Christina K
Published: August 2020

Background

The success of behavioral interventions and policies designed to reduce the impact of the COVID-19 pandemic depends on how well individuals are informed about both the consequences of infection and the steps that should be taken to reduce the impact of the disease.

Objective

The aim of this study was to investigate associations between public knowledge about COVID-19, adherence to social distancing, and public trust in government information sources (eg, the US Centers for Disease Control and Prevention), private sources (eg, FOX and CNN), and social networks (eg, Facebook and Twitter) to inform future policies related to critical information distribution.

Methods

We conducted a cross-sectional survey (N=1243) between April 10 and 14, 2020. Data collection was stratified by US region and other demographics to ensure representativeness of the sample.

Results

Government information sources were the most trusted among the public. However, we observed trends in the data that suggested variations in trust by age and gender. White and older populations generally expressed higher trust in government sources, while non-White and younger populations expressed higher trust in private sources (eg, CNN) and social networks (eg, Twitter). Trust in government sources was positively associated with accurate knowledge about COVID-19 and adherence to social distancing. However, trust in private sources (eg, FOX and CNN) was negatively associated with knowledge about COVID-19. Similarly, trust in social networks (eg, Facebook and Twitter) was negatively associated with both knowledge and adherence to social distancing.

Conclusions

During pandemics such as the COVID-19 outbreak, policy makers should carefully consider the quality of information disseminated through private sources and social networks. Furthermore, when disseminating urgent health information, a variety of information sources should be used to ensure that diverse populations have timely access to critical knowledge.
Feasibility of Asynchronous and Automated Telemedicine in Otolaryngology: Prospective Cross-Sectional Study (Preprint)
Authors: Cha Dongchul , Shin Seung Ho , Kim Jungghi , Eo Tae Seong , Na Gina , Bae Seonghoon , Jung Jinsei , Kim Sung Huhn , Moon In Seok , Choi Jaeyoung , Park Yu Rang
Published: August 2020

BACKGROUND

COVID-19 often causes respiratory symptoms, making otolaryngology offices one of the most susceptible places for community transmission of the virus. Thus, telemedicine may benefit both patients and physicians.

OBJECTIVE

This study aims to explore the feasibility of telemedicine for the diagnosis of all otologic disease types.

METHODS

A total of 177 patients were prospectively enrolled, and the patient’s clinical manifestations with otoendoscopic images were written in the electrical medical records. Asynchronous diagnoses were made for each patient to assess Top-1 and Top-2 accuracy, and we selected 20 cases to conduct a survey among four different otolaryngologists to assess the accuracy, interrater agreement, and diagnostic speed. We also constructed an experimental automated diagnosis system and assessed Top-1 accuracy and diagnostic speed.

RESULTS

Asynchronous diagnosis showed Top-1 and Top-2 accuracies of 77.40% and 86.44%, respectively. In the selected 20 cases, the Top-2 accuracy of the four otolaryngologists was on average 91.25% (SD 7.50%), with an almost perfect agreement between them (Cohen kappa=0.91). The automated diagnostic model system showed 69.50% Top-1 accuracy. Otolaryngologists could diagnose an average of 1.55 (SD 0.48) patients per minute, while the machine learning model was capable of diagnosing on average 667.90 (SD 8.3) patients per minute.

CONCLUSIONS

Asynchronous telemedicine in otology is feasible owing to the reasonable Top-2 accuracy when assessed by experienced otolaryngologists. Moreover, enhanced diagnostic speed while sustaining the accuracy shows the possibility of optimizing medical resources to provide expertise in areas short of physicians.
An Evaluation of Suitable Landscape to Crop Food Cultivation By Using Neural Networks
Authors: Azis Anifudin , Sunarminto Bambang Hendro , Renanti Medhanita Dewi
Published: August 2020

Penentuan jenis tanaman pangan yang sesuai ditanam pada lahan tertentu berdasarkan nilai-nilai karakteristik lahan sangat diperlukan sebagai pendukung pengambilan keputusan, koordinasi, dan pengendalian bagi para peneliti, praktisi, dan perencana penggunaan lahan, sehingga kerugian (finansial) yang cukup besar tidak terjadi nantinya. Program komputer dengan menggunakan Jaringan Syaraf Tiruan (JST) metode Learning Vector Quantization (LVQ) dapat digunakan sebagai alat yang tepat dalam memberikan informasi tanaman yang cocok ditanam dengan mudah, cepat, dan akurat. Data pelatihan didapat dari kombinasi nilai karakteristik lahan yang termasuk dalam kelas kesesuaian S1 dan S2. Hasil pengujian menunjukkan bahwa nilai Eps (error minimum yang diharapkan) = 0.005, nilai ?? ?? = 0.05, nilai maksimum epoh = 10, dan nilai pengurangan learning rate sebesar 0.1*?? ?? merupakan nilai-nilai yang cukup efektif dan efisien dalam melakukan prediksi jenis tanaman pangan yang sesuai ditanam pada lahan tertentu karena tingkat ketepatan prediksinya adalah 100%.
A Web Based Expert System for Identifying Bloomed Plants
Authors: Sari Anny Kartika , Aryani Adriana Sari
Published: August 2020

This research discusses the development of a web based expert system for identifying bloomed plants. The identification is based on the seven visible features of a bloomed plant, i.e. the root type, the type of the plant, the shape of the flowers, the shape of the leaves, the height of the plant, and the length and the width of the leaves. For inference process, the forward chaining method is used. The system is developed using PHP as the programming language and MySQL as the database management system. Based on some testing conducted to the system, it can be concluded that the system can identify bloomed plants with the accuracy of 100%. The system can accommodate the update on its knowledge as long as the update is only on the available features in the system. This drawback can be used as starting point for the future development of the system.
An Implementation of Catmap-Rijndael (AES) Algorithm For Image Security (Case Study on A Software For Making Students Card At Universitas Jenderal Soedirman)
Authors: Wijayanto Bangun , Wardoyo Retantyo
Published: August 2020

Abstract— The function of image encryption is to transform known have that meaning to images that cannot be read or irregular images in order to security. Storing the image data in local computer system will bring some risks on the image security.The aim of this research is to construct an image encryption system based on Catmap-Rijndael algorithm. The system is implemented on a software form making students card at Universitas Jenderal Soedirman. The result shows that the combination of Catmap-Rijndael algorithm on bitmap image 200x200 pixel by using 3 times repetition of the Catmap algorithm (with parameter a=1 and b=1) can overcome the problem of textured of the object that caused by base colour on the image and uniform histogram of the encrypted image in short time process.Keywords— Rijndael, AES, Catmap, image security, students card.
Aplikasi Mobile WEB Map Service Pada Mobile Device Dengan SVGT
Authors: Priyanta Sigit , Imanuddin Ghulam , Prilistya Suci Karunia
Published: August 2020

Abstract— Teknologi informasi geografi berkembang sangat pesat dalam beberapa dekade terakhir ini. Sekarang ini, WMS (Web Map Services) tidak hanya dapat menghasilkan gambar raster tetapi juga gambar vektor. Contohnya adalah SVGT (Scalable Vector Graphics Tiny) yang merupakan bagian dari SVG (Scalable Vector Graphics) yang digunakan pada piranti mobile device. Mahalnya biaya komunikasi antara handheld device dengan jaringan internet melalui GPRS (Global Pocket Radio System) menimbulkan sebuah masalah dalam penerapan aplikasi mobile mapping. Untuk mengeliminasi masalah tersebut, harus dibuat sebuah aplikasi mobile mapping yang dapat mentransfer data sekecil mungkin. Didalam penelitian ini, dicoba untuk dibuat sebuah server pemetaan yang memanfaatkan teknologi SVGT dan XML. Kedua format data tersebut digunakan untuk menghasilkan data sekecil mungkin agar dapat menghemat biaya komunikasi antara klien dan server. Pada akhirnya, aplikasi yang dibangun akan menjadi sebuah server yang memiliki klien berupa handheld / mobile device.Aplikasi ini dibangun dengan bahasa pemrograman PHP dan memanfaatkan database PostgreSQL beserta ekstensi PostGIS-nya pada sisi server dan J2ME (Java 2 Micro Edition) pada sisi mobile client. Aplikasi yang telah dibangun mampu untuk menampung peta jalan dari sebuah daerah, menampilkannya dalam format SVGT kepada klien, serta mencari rute terpendek antara dua buah jalan dengan menggunakan algoritma Floyd-Warshall. Mobile device sebagai client mempunyai beberapa fungsi utama, yaitu download map dengan format SVGT dari server, menyimpan map ke dalam record store, menampilkan map dan juga melakukan fungsi pan dan zoom terhadap map. Fungsi lainnya adalah searching atau mencari  titik tertentu pada map sesuai dengan permintaan user, request path ke server untuk mendapatkan jalur terpendek antara dua titik, dan set mark atau menyimpan titik-titik pada peta yang telah diberi tanda oleh user.Keywords— SVG, SVGT, Mobile Mapping, Web Map Services, J2ME, Java 2 Micro Editon.
Detecting A Botnet By Reverse Engineering
Authors: Kelana Oesman Hendra , Mustofa Khabib
Published: August 2020

Abstract— Botnet malware is a malicious program. Botnet that infects computers, called bots, will be controlled by a botmaster to do various things such as: spamming, phishing, keylogging Distributed Denial of Service (DDoS) and other activities that are generally profitable to the owner of the bot (botmaster) or those who use botnet services. The problem is that many computers have been controlled by botnets without the knowledge of the computer owner.  There are many ways to examine botnets, for example by studying the traffic from the botnet network, studying how botnets communicate to each, studying how each robot receives orders to do something, and so forth. Of the many methods, the most frequently and commonly used is the reverse engineering, where researchers study how a botnet works by botnet debugging.In this study the author tries to understand or research botnets by taking a type of botnet, namely Agobot, using reverse engineering.  One of the result of the research is that malware program files in general and in particular botnet has a technique to obscure the way that research using reverse engineering.Another result also shows that the botnet Agobot runs on computers by using the Windows service, and by changing the Windows registry so that every time the computer starts, Agobot always actively works in the computer memory.Keywords— Malware, Bot, Botnet, Botmaster, Agobot, Spam, Distributed Denial of Services, Identity Theft, Computer Security, Reverse Engineering, Debug, Windows Service, the Registry.
Sistem Pendukung Keputusan Pemilihan Subkontrak Menggunakan Metode Entropy dan TOPSIS
Authors: Jamila Jamila , Hartati Sri
Published: August 2020

Abstract— Outsourcing is a part of production process of manufacturing industry which contribute for suitainability of a manufacture process. Choosing appropriate subcontractor which match spesification is not easy. In order to help company in determining credible subcontractors is needed a decision support system.Selection of decision support system for the production of subcontracting gloves uses Entropy and TOPSIS methods. Entropy method is used to give weight to the criteria. TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method is used to select the best subcontractors, where subcontracting was elected not only has the shortest distance from the positive ideal solution but it also has the longest distance from the negative ideal solution. Designing of systems use ERD and DFD for identifying the needs of users and systems, and as for guiding the software implementation. The results of this research are the establishment of an application used to select subcontractors based on established criteria. Test results on the application can provide decision input/suggestion, although the criteria used in making decision is different. Subcontract selection decision support system can be an alternative to choose subcontractors for the production of gloves in PT. Adi Satria Abadi Yogyakarta.Keywords— DSS, Decision Support  System,  Entropy, TOPSIS, Subcontract
Reversible Watermarking dengan Metode Modifikasi Histogram pada Difference Image
Authors: Retno Yustina , Harjoko Agus
Published: August 2020

Abstract— Reversible watermarking schemes are widely used to maintain the authenticity of the digital image. This research will discuss a method on histogram modification of difference image in which the difference image is created from the difference value of adjacent pixels of the image grayscale.  Embedding process begins by dividing the host image and watermark into b blocks, followed by making a difference image of the host image block. From the difference image histogram, determine the peak value, and modify the histogram based on the peak value. Then, insert each block of the watermark to the difference image that has been modified and transform back into the grayscale image.Extraction and recovery process is the inverted version of the embedding stage. This process begins by dividing the watermarked image into b blocks, followed by making a difference image of each block. Then, extract the data and shift difference image histogram using a peak value. That difference image is transformed back into a grayscale image. Experimental results demonstrate that the average insertion capacity is 14% greater than Xue's with PSNR value over 48 dB for 4 x 4 pixels and 23 % greater with PSNR over 46 dB for 8 x 8 pixels. From the comparison of robustness to line and salt n’ pepper on the density of 0.05 noises is obtained that the watermark with ECC is more robust than a watermark without ECC. JPEG compression in lossless mode may be applied to the watermarked image. Multiple insertion of watermark can be done with the consequence that the more insertions will result in lower PSNR values.Keywords—difference image, histogram modification, reversible watermarking
Analisis Fitur Kalimat untuk Peringkas Teks Otomatis pada Bahasa Indonesia
Authors: Zaman Badrus , Winarko Edi
Published: August 2020

Abstract— Automatic Text Summarization (ATS) is a technique to create a summary of the document automatically by using computer applications to produce the most important information from the original document. Features are required to perform weighting of sentences, including Log-TFISF (term frequency index sentence frequency), sentence location, sentence overlap, title overlap and sentence relative length. This research conducted an analysis of five features in order to determine the weights of each feature that will get the results of a coherent summary. The five features are implemented in automated text summarization system in Indonesian language that was developed using the method of relative importance of topics. Results from experiments show that sentence location feature has the highest F-Measures namely 0.46 and then consecutive sentence overlap, title overlap, sentence relative length and Log-TFISF, with a value of 0.42, 0.42, 0.35 and 0.32. Relative weights of feature extraction consecutive from the largest are sentence location, sentence overlap, title overlap, sentence relative length and Log-TFISF with a value of 0.25, 0.22, 0.22, 0.19 and 0.12. These relative weights are implemented on ATS, so we get accuracy of 70.62%. It is more accurate 2,86% than without relative weights which accuracy of 67,72%.. .Keywords— Automatic Text Summarization (ATS), Log-TFISF, sentence location, sentence overlap, title overlap, sentence relative length, bahasa Indonesia
Rancang Bangun Keamanan Web Service Dengan Metode Ws-Security
Authors: Muzakir Ari , Ashari Ahmad
Published: August 2020

AbstrakWeb service menggunakan teknologi XML dalam melakukan pertukaran data. Umumnya penggunaan web service terjadi pertukaran data ataupun informasi penting yang perlu dijaga keamanannya. Bentuk pengamanan yang diterapkan pada web services adalah dengan penggunaan teknik kriptografi kunci-publik. Adapun serangan dapat berupa pengintaian, perusakan maupun pencurian data. Salah satu cara penyelesaian terbaik adalah dengan membuat data tersebut tidak dapat dibaca orang lain. Implementasi yang telah dilakukan dengan menggunakan library keamanan akan memberikan kemudahan dalam membangun keamanan web service karena dengan dukungan library XMLSEC sebagai library pendukung dan library class_wss yang telah dibangun mampu mengatasi masalah keamanan pada jalur transport khususnya untuk otentikasi, otorisasi, dan konfidensialitas pesan SOAP request. Model WS-Security dengan menggunakan XML Signature, XML Encryption, serta Security Token yang memanfaatkan algoritma kriptografi RSA dengan panjang kunci 1024 bit mampu memberikan perlindungan terhadap transmisi data antara client dan server web service. Pengujian yang dilakukan pada web service dengan menerapkan model library class_wss sebagai keamanan web service yang dibangun memberikan hasil yang baik, yaitu pesan SOAP request terenkripsi dan mampu didekripsi dengan baik serta dapat tertandatangani dan dicek keasliannya.Kata kunci— Keamanan Web Service, XML Signature, XML  Encryption, Security Token. Abstract Web service uses XML technology to exchange data in. Generally, the use of the web service exchanges data or important information that needs to be guarded security. Form of security is applied to web services is to use public-key cryptography techniques. The attack can be a reconnaissance, destruction or theft of data. One way the best solution is to create data that can not read anyone else, even if someone else managed to retrieve the data, he will not be able to read it.            The implementation was done by using the security library will provide facilities in developing a web security service for the library support XMLSEC as library supporters and library class_wss that have been built able to overcome the problem of security on the transport path, especially for authentication, authorization, and confidentiality request SOAP message. Model WS-Security using XML Signature, XML Encryption, and Security Token which utilizes the cryptographic algorithm RSA with 1024 bit key length to provide protection against transmission of data between client and server web service. Tests performed on the web service by implementing a security model class_wss library web service that is built to give good results, the SOAP request message is encrypted and decrypted with a good and able to sign and check their authenticity too.Keywords— Web Service Security, XML Signature, XML Encryption, Security Token
Evaluation Existential of Medical Record Laboratory at the Diploma 3 Program for Medical Record & Health Information, Mathematics and Natural Science Faculty, Gadjah Mada University
Authors: Budi Savitri Citra , Hariyono Hariyono , Purwatiningsih Sri
Published: August 2020

The availability of Medical Record Laboratory to support Medical Record education is one that the education provider should prepare. In addition, education providers should also organize the usage, instrument provision, HRD provision and clear planning and objectives.The present research used evaluation topic on the existence of Medical Record Laboratory at the Diploma 3 Program for Medical Record and Health Information, MIPA Faculty, Gadjah Mada University. This topic was used by considering the Government Regulation on education provision, especially Medical Record Education (The Regulation of Minister Health Number 1192/Menkes/Per/X/2004) as thinking base. Data were taken from initial survey that the Laboratory was considered as not maximally performed. Base on instrument availability, this laboratory had no complete instrument, especially manually data processing completeness. Moreover, in fact, the usage and planning on this facility had not been well organized, while there was mostly high demand on the usage. To this end, evaluation was highly required for future progress. Evaluation was gradually performed. First was evaluation on input related technology, human resources, costs, facilities and management. Second was evaluation on process related to whether the planned activities had been completed or not. Third, evaluation on inputs related to attitudes, norms and skill knowledge of those involved in the laboratory (staffs, students, and stakeholder).The present research exploited descriptive method with qualitative approach using single data variable (the existence of Medical Record Laboratory at the Diploma 3 Program for Medical Record and Health Information Gadjah Mada University). Data were collected using source triangulation approach through data cross-checking with fact from other sources. Data analysis was performed by comparing data taken to the existing standard (Government Regulation and theory). To simplify discussion, data were discussed based on principle elements of health services, among others, including: inputs, process, and outputs.Evaluation on the existence of laboratory was presumably exploited to consider future development and management as expected that this Laboratory could be taken as example for medical record management in hospitals.
Telaah Metode-metode Pendeteksi Kebohongan
Authors: Gunadi I Gede Aris , Harjoko Agus
Published: August 2020

AbstrakPendeteksi kebohongan adalah aplikasi yang menerapkan berbagai cabang ilmu pengetahuan(psikologi,kedokteran,biologi,fisika,komputer,dan lain lain). Aplikasi pendeteksi kebohongan sangatlah berguna terutama dikalangan penegak hukum, untuk mengungkap fakta fakta. Pada prinsipnya metode pendekteksi kebohongan bekerja berdasarkan perubahan respon fisiologis tubuh manusia, yang diakibatkan oleh usahanya untuk menutupi kebohongannya.Dalam paper ini akan dibahas berbagai pendekatan  metode yang telah dikembangkan untuk mendeteksi kebohongan,diantaranya deteksi kebohongan berdasarkan konduktivitas kulit, bentuk tulisan tangan , isi ( content tulisan), analisis suara, termograpy, dan gesture.Kata kunci— Lie detector, Detection Deception, Polygraph,  PDD Test.AbstractLie detector is an application that applying various of knowledge  such as psychology,medicine,biology,physics, computer , and etc. This application is very  useful especially  among law officer  to detect deception. In principle , the lie detector’s methods work based on change of fisilogy respon at human being body. The change of psiology respon is caused by effort to keep their deception. In this papers, we present an approach  various methods of lie detection  which have been developed . we will present lie detection based on skin conductivity respon, handwriting form, article content, voice analysis, image infrared, and gesture.  Keywords—  Lie detecotor, Detection Deception, Polygraph, PDD( polygraph Detection deception) Test.
Penerapan Algoritma Optimasi Chaos pada Jaringan Ridge Polynomial untuk Prediksi Jumlah Pengangguran
Authors: Pramitasari Rina , Wardoyo Retantyo
Published: August 2020

AbstrakRidge polynomial neural network (RPNN) awalnya diusulkan oleh Shin dan Ghosh, dibangun dari jumlah peningkatan order pi-sigma neuron (PSN). RPNN mempertahankan pembelajaran cepat, pemetaan yang kuat dari layer tunggal higher order neural network (HONN) dan menghindari banyaknya bobot karena meningkatnya sejumlah input. Algoritma optimasi chaos digunakan dengan memanfaatkan persamaan logistik yang sensitif terhadap kondisi awal, sehingga pergerakan chaos dapat berubah di setiap keadaan dalam skala tertentu menurut keteraturan, ergodik dan mempertahankan keragaman solusi.Algoritma Optimasi Chaos diterapkan pada RPNN dan digunakan untuk prediksi jumlah pengangguran di Kalimantan Barat. Proses pelatihan jaringan menggunakan ridge polynomial neural network, sedangkan pencarian nilai awal bobot dan bias jaringan menggunakan algoritma optimasi chaos. Struktur yang digunakan terdiri dari 6 neuron layer input dan 1 neuron layer output. Data diperoleh dari Badan Pusat Statistik.Hasil dari penelitian ini menunjukkan bahwa algoritma yang diusulkan dapat digunakan untuk prediksi. Kata kunci—prediksi jumlah pengangguran, jaringan syaraf tiruan, algoritma optimasi chaos, ridge polynomial neural network  Abstract Ridge polynomial neural network was initially proposed by Shin and Ghosh, made of total increased pi-sigma neural (PSN) orders. Ridge polynomial neural network maintains quick learning, strong mapping of single layer of higher order neural network (HONN) and avoids many weights because total increased inputs. Chaos optimization algorithm is used by utilizing sensitive logistic equation to initial condition, so that chaos movement can change in each condition in specific scale according to orderliness, ergodic, and maintaining solution variety.             Chaos optimization algorithm is applied to ridge polynomial neural network and used to predict total unemployed persons in West Kalimantan. Network training process used ridge polynomial neural network; while, initial values and weights and bias of network were found using Chaos optimization algorithm. Structure used consisted of 6 input layer neurons and one output layer neuron. Data were obtained from Central Statistic Agency.            The results of research indicated that algorithm proposed could be used to predict Keywords— predict the number of unemployed, neural networks, chaos optimization algorithm, ridge polynomial neural network
An Application of Fuzzy Inference System by Clustering Subtractive Fuzzy Method for Estimating of Product Requirement
Authors: Tufeil Fajar Ibnu , Musdholifah Aina
Published: August 2020

Model fuzzy memiliki kemampuan untuk menjelaskan secara linguistik suatu sistem yang terlalu kompleks. Aturan-aturan dalam model fuzzy pada umumnya dibangun berdasarkan keahlian manusia dan pengetahuan heuristik dari sistem yang dimodelkan. Teknik ini selanjutnya dikembangkan menjadi teknik yang dapat mengidentifikasi aturan-aturan dari suatu basis data yang telah dikelompokkan berdasarkan persamaan strukturnya. Dalam hal ini metode pengelompokan fuzzy berfungsi untuk mencari kelompok-kelompok data. Informasi yang dihasilkan dari metode pengelompokan ini, yaitu informasi tentang pusat kelompok, digunakan untuk membentuk aturan-aturan dalam sistem penalaran fuzzy. Dalam skripsi ini dibahas mengenai penerapan fuzzy infereance system dengan metode pengelompokan fuzzy subtractive clustering, yaitu untuk membentuk sistem penalaran fuzzy dengan menggunakan model fuzzy Takagi-Sugeno orde satu. Selanjutnya, metode pengelompokan fuzzy subtractive clustering diterapkan dalam memodelkan masalah dibidang pemasaran, yaitu untuk memprediksi permintaan pasar terhadap suatu produk susu. Aplikasi ini dibangun menggunakan Borland Delphi 6.0. Dari hasil pengujian diperoleh tingkat error prediksi terkecil yaitu dengan Error Average 0.08%.
Purwarupa Sistem Pakar dengan Mamdani Product untuk Menentukan Menu Harian Penderita DM
Authors: Hasanah Nur , Wardoyo Retantyo
Published: August 2020

AbstrakPada 2025 diperkirakan 12,4 juta orang yang mengidap Diabetes Melitus (DM) di Indonesia. Perencanaan makan merupakan salah satu pilar dalam pengelolaan DM. Sistem pakar dapat berfungsi sebagai konsultan yang memberi saran kepada pengguna sekaligus sebagai asisten bagi pakar. Logika fuzzy fleksibel, memiliki kemampuan dalam proses penalaran secara bahasa dan memodelkan fungsi-fungsi matematika yang kompleks. Penelitian ini bertujuan menerapkan metode ketidakpastian logika fuzzy pada purwarupa sistem pakar untuk menentukan menu harian. Manfaat penelitian ini adalah untuk mengetahui keakuratan mesin inferensi Mamdani Product.            Pendekatan basis pengetahuan yang digunakan pada sistem pakar ini adalah dengan Rule-Based Reasoning. Proses inferensi pada sistem pakar menggunakan logika fuzzy dengan mesin inferensi Mamdani Product. Fuzzifier yang digunakan adalah Singleton sedangkan defuzzifier yang digunakan adalah Rata-Rata Terpusat. Penggunaan kombinasi Singleton fuzzifier, mesin inferensi Product dan defuzzifier Rata-Rata Terpusat yang digunakan pada sistem pakar dapat diterapkan untuk domain permasalahan yang dibahas. Meskipun demikian, terdapat kemungkinan Singleton fuzzifier tidak dapat memicu beberapa atau semua aturan. Jika semua aturan tidak dapat dipicu maka tidak dapat disimpulkan kebutuhan kalori hariannya. Kata kunci— sistem pakar, logika fuzzy, mamdani product, diabetes, menu  AbstractIt is predicted that 12.4 million people will suffer from Diabetes Mellitus (DM) in Indonesia in 2025. Menu planning is one of the important aspects in DM management. Expert system can be used as a consultant that gives suggestion to users as well as an assistant for experts. Fuzzy logic is flexible, has the ability in linguistic reasoning and can model complex mathemathical functions. This research aims to implement fuzzy logic uncertainty method into expert sistem prototype to determine diabetic daily menu. The advantage is to find out the accuracy of Mamdani Product inference engine. The knowledge-based approach in this expert system uses Rule-Based Reasoning. The inference process employs fuzzy logic making use of Mamdani Product inference engine. The fuzzifier used is Singleton while defuzzifier is Center Average.            The combination of Singleton fuzzifier, Mamdani Product inference engine and Center Average defuzzifier that is used can be applied in the domain of the problem under discussion. In spite of the case, there is possibility that Singleton fuzzifier can’t trigger some or all of the rules. If all of the rules can’t be triggered then the diabetic daily menu can’t be concluded. Keyword— expert system, fuzzy logic, mamdani product, diabetes, menu
Aplikasi Metode Fuzzy Multi-Attribute Decision Making Berbasis Web dalam Pemilihan Calon Kepala Daerah di Indonesia
Authors: Munawar Yusro Muhamad , Wardoyo Retantyo
Published: August 2020

AbstrakSejak tahun 2005 di Indonesia sudah dilaksanakan pemilihan kepala daerah (pilkada) secara langsung mulai dari pemilihan kepala desa, bupati, walikota sampai dengan gubernur. Majalah SwaSembada menyebutkan ada pemilihan langsung untuk 500 anggota DPR; 33 gubernur, serta sekitar 460 pemilihan untuk jabatan bupati dan wali kota. Dalam penelitian ini dibuat sebuah aplikasi yang mampu mensimulasikan suatu bentuk aplikasi pengambilan keputusan kasus Penentuan Pilihan Calon Kepala Daerah di Indonesia menggunakan metode Fuzzy MADM yang dikembangkan oleh Moon Hyun Joo dan Chang Sun Kang. Sistem ini mempunyai kemampuan menampung input kriteria yang diinginkan dari pengguna, alternatif pasangan calon, dan pada akhirnya mampu memberikan tampilan visual berupa himpunan solusi terbaik dari beberapa alternatif yang diberikan menggunakan metode perangkingan Nilai Total integral. Dari dua kasus pemilihan bupati yang diujikan ternyata hasil perangkingan tidak selalu sama tergantung dari tingkat keoptimisan (a) yang dipakai. Kata kunci— fuzzy, fmadm, pemilihan kepala daerah AbstractSince 2005, in Indonesia the election of regional leader (pilkada) has been held directly start from election of countryside head, regent, mayor up to governor. SwaSembada Magazine mentioned that there are direct elections to elect 500 members of DPR; 33 governors, and also about 460 elections for the occupation of lord mayor and regent. The aim of this research is to create an application which is capable to simulate a Decision Making System in the case of Determination the Choice in the Election of Regional Leader in Indonesia using the Fuzzy MADM method developed by Moon Hyun Joo and Chang Sun Kang. This system is able to accomodate the criterion input as the consumer want, alternative of candidate couple, and finally can give the visual appearance in the form of best solution gathering from some given alternatives using the Nilai Total integral sort method. This system has been implemented in two elections of Regional Leader, and from the test can be concluded that the result of the sort is not always the same. It depends on the optimism storey level (a) that used in the system. Keywords— fuzzy, fmadm, election of regional leader
Simulasi Antrian Jaringan Multi Server Menggunakan Metode Open Jackson
Authors: Supriana I Wayan , Subanar Subanar
Published: August 2020

AbstrakAntrian paket data pada jaringan komputer memiliki model antrian jaringan, dimana proses transmisi yang rumit sehingga tidak dapat diselesaikan secara analitik. Pemodelan dan simulasi diperlukan untuk menyelesaikan masalah antrian jaringan. Model antrian dalam penelitian ini adalah jaringan terbuka dengan analisis paket data menggunakan model server tunggal. Waktu pelayanan paket memiliki distribusi Eksponensial dan distribusi Erlang yang digunakan sebagai pembanding. Jika waktu pelayanan paket data menggunakan distribusi Eksponensial maka model menjadi M/M/1, sedangkan waktu pelayanan paket data menggunakan distribusi Erlang dengan parameter m dan µ, maka model menjadi M/E[m]/1. Penelitian ini menggunakan metode open Jackson untuk melakukan simulasi antrian jaringan guna menghitung nilai karakteristik jaringan. Pengujian sistem simulasi menggunakan packet switching network pada server jaringan komputer Jurusan Ilmu Komputer Universitas Udayana untuk mengetahui performansi sistem yang menggunakan distribusi waktu pelayanan berbeda. Hasil pengujian menunjukkan bahwa waktu pelayanan distribusi Eksponensial memiliki karakteristik yang lebih baik dari distribusi Erlang pada parameter m-Erlang ≥ 2.  Kata kunci— antrian jaringan, distribusi,sistem performansi, multi server.  AbstractQueue data packet at computer network having a network queueing model, with complicated transmission process so that it can not be solved analytically. Modeling and simulation are needed to resolve the issue queue network. Queueing model in this research is an open network with the analysis of data packet using a single server model. Service time packet has Exponential distribution and Erlang used as comparison. If the service time of data packet using the Exponential distribution, then the model become M/M/1, whereas the service time using the Erlang distribution with parameter m and µ, then the model becomes M/E[m]/1. This research uses an open Jackson method to perform queueing network simulations to calculate the characteristics of network queueing system. Examination of simulation system uses data packets on a computer network server of Department Computer Science University of Udayana to determine system performance using with different service time distribution. The result of examination indicate that service time of Exponential distribution has better characteristic then Erlang distribution at parameter m-Erlang ≥2. Keywords— queueing network, distribution, system performance, multiple server
Penyembunyian Data pada File Video Menggunakan Metode LSB dan DCT
Authors: Yunus Mahmuddin , Harjoko Agus
Published: August 2020

AbstrakPenyembunyian data pada file video dikenal dengan istilah steganografi video. Metode steganografi yang dikenal diantaranya metode Least Significant Bit (LSB) dan Discrete Cosine Transform (DCT). Dalam penelitian ini dilakukan penyembunyian data pada file video dengan menggunakan metode LSB, metode DCT, dan gabungan metode LSB-DCT. Sedangkan kualitas file video yang dihasilkan setelah penyisipan dihitung dengan menggunakan Mean Square Error (MSE) dan Peak Signal to Noise Ratio (PSNR).Uji eksperimen dilakukan berdasarkan ukuran file video, ukuran file berkas rahasia yang disisipkan, dan resolusi video.Hasil pengujian menunjukkan tingkat keberhasilan steganografi video dengan menggunakan metode LSB adalah 38%, metode DCT adalah 90%, dan gabungan metode LSB-DCT adalah 64%. Sedangkan hasil perhitungan MSE, nilai MSE metode DCT paling rendah dibandingkan metode LSB dan gabungan metode LSB-DCT. Sedangkan metode LSB-DCT mempunyai nilai yang lebih kecil dibandingkan metode LSB. Pada pengujian PSNR diperoleh databahwa nilai PSNR metode DCTlebih tinggi dibandingkan metode LSB dan gabungan metode LSB-DCT. Sedangkan nilai PSNR metode gabungan LSB-DCT lebih tinggi dibandingkan metode LSB.  Kata Kunci—Steganografi, Video, Least Significant Bit (LSB), Discrete Cosine Transform (DCT), Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR)                           AbstractHiding data in video files is known as video steganography. Some of the well known steganography methods areLeast Significant Bit (LSB) and Discrete Cosine Transform (DCT) method. In this research, data will be hidden on the video file with LSB method, DCT method, and the combined method of LSB-DCT. While the quality result of video file after insertion is calculated using the Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR). The experiments were conducted based on the size of the video file, the file size of the inserted secret files, and video resolution.The test results showed that the success rate of the video steganography using LSB method was 38%, DCT method was 90%, and the combined method of LSB-DCT was 64%. While the calculation of MSE, the MSE method DCT lower than the combined method of LSB and LSB-DCT method. While LSB-DCT method has asmaller value than the LSB method. The PNSR experiment showed that the DCT method PSNR value is higher than the combined method of LSB and LSB-DCT method. While PSNR combined method LSB-DCT higher compared LSB method.  Keywords—Steganography, Video, Least Significant Bit (LSB), Discrete Cosine Transform (DCT), Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR)
Penapisan Derau Gaussian, Speckle dan Salt&Pepper Pada Citra Warna
Authors: Purwanti Ningrum Ika , Eko Putra Agfianto , Nursantika Dian
Published: August 2020

Quality of digital image can decrease becouse some noises. Noise can come from lower quality of image recorder, disturb when transmission data process and weather. Noise filtering can make image better becouse will filtering that noise from the image and can improve quality of digital image. This research have aim to improve color image quality with filtering noise. Noise (Gaussian, Speckle, Salt&Pepper) will apply to original image, noise from image will filtering use Bilateral Filter method, Median Filter method and Average Filter method so can improve color image quality. To know how well this research do, we use PSNR (Peak Signal to Noise Ratio) criteria with compared original image and filtering image (image after using noise and filtering noise).This research result with noise filtering Gaussian (variance = 0.5), highest PSNR value found in the Bilateral Filter method is 27.69. Noise filtering Speckle (variance = 0.5), highest PSNR value found in the Average Filter method is 34.12. Noise filtering Salt&Pepper (variance = 0.5), highest PSNR value found in the Median Filter method is 31.27. Keywords— Bilateral Filter, image restoration, derau Gaussian, Speckle dan Salt&Pepper
HOG Feature Extraction and KNN Classification for Detecting Vehicle in The Highway
Authors: Achyunda Putra Firnanda Al Islama , Utaminingrum Fitri , Mahmudy Wayan Firdaus
Published: August 2020

Autonomous car is a vehicle that can guide itself without human intervention. Various types of rudderless vehicles are being developed. Future systems where computers take over the art of driving. The problem is prior to being attention in an autonomous car for obtaining the high safety. Autonomous car need early warning system to avoid accidents in front of the car, especially the system can be used in the Highway location. In this paper, we propose a vision-based vehicle detection system for Autonomous car. Our detection algorithm consists of three main components: HOG feature extraction, KNN classifier, and vehicle detection. Feature extraction has been used to recognize an object such as cars. In this case, we use HOG feature extraction to detect as a car or non-car. We use the KNN algorithm to classify. KNN Classification in previous studies had quite good results. Car detected by matching about trining data with testing data. Trining data created by extract HOG feature from image 304 x 240 pixels. The system will produce a classification between car or non-car.
Multithreading Application for Counting Vehicle by Using Background Subtraction Method
Authors: Pratama Yohanssen , Ratno Puspoko Ponco
Published: August 2020

Image and video processing has become important part in intelligent transportation system (ITS) application, especially for collecting road traffic data. Pictures that already collected by a charged coupled device (CCD) camera usually being processed by several image processing algorithms and the application’s code will be executed in a large number of iteration because many algorithms are getting involved in processing the frame which captured by the camera. Typical application will process the first frame until finish and then continue to the next frame, so the application must wait until the first frame being processed. If the algorithms that executed quite complex and have a significant running time there will be a dropped frame and the time difference between data acquisition and real time video is divided by large margin. We proposed an implementation of multithreading to boost the application performance so the data can be acquire in real time and every new frame could be processed in short time. The application performance before and after using a multithreading is known by comparing the data acquisition time that stored in the database. The application effectiveness could define by running a multiple video streaming in same resolution.
Determining Community Structure and Modularity in Social Network using Genetic Algorithm
Authors: Dwi Putra Aditama Taufan Bagus , SN Azhari
Published: August 2020

Research on determining community structure in complex networks has attracted a lot of attention in various applications, such as email networks and social networks. The popularity determines the structure of a community because it can analyze the structure.Meanwhile, to determine the structure of the community by maximizing the value of modularity is difficult. Therefore, a lot of research introduces new algorithms to solve problems in determining community structure and maximizing the value of modularity. Genetic Algorithm can provide effective solutions by combining exploration and exploitation.This study focuses on the Genetic Algorithm which added a cleanup feature in the process. The final results of this study are the results of a comparison of modularity values based on the determination of the community structure of the Genetic Algorithm, Girvan and Newman Algorithm, and the Louvain Algorithm. The best modularity values were obtained using the Genetic Algorithm which obtained 0.6833 results for Zachary's karate club dataset, 0.7446 for the Bottlenose dolphins dataset, 0.7242 for the American college football dataset, and 0.5892 for the Books about US politics dataset.