bluuebunny/crossref_metadata_2025_split huggingface dataset:
GDSS Penentuan Lokasi Shelter Baru Transjogja Menggunakan Metode Brown-Gibson dan Borda
Authors: Susilo Bhakti , SN Azhari 
Published: August 2020

AbstrakTujuan didirikannya armada bus Transjogja adalah untuk mengurai permasalahan kemacetan, polusi dan transportasi umum yang memadai. Untuk memberikan layanan yang terbaik, salah satu hal yang diusahakan adalah menempatkan shelter pada posisi yang tepat. Dinas perhubungan bekerja sama dengan instansi lain dalam pengumpulan aspirasi eksekutif untuk penentuan lokasi shelter baru.Kombinasi Metode Brown-Gibson dan Borda memungkinkan digunakan untuk pemilihan lokasi secara kelompok. Metode ini digunakan untuk memilih alternatif lokasi berdasarkan ukuran preferensi tertentu (preference measurement) dengan mempertimbangkan faktor obyektif dan faktor subyektifnya. Faktor obyektif berupa efektifitas biaya yaitu jumlah total biaya yang dikeluarkan untuk satu alternatif lokasi. Faktor subyektif berupa pembobotan para pengambil keputusan terhadap kriteria-kriteria yang disyaratkan dalam penentuan lokasi shelter baru. Kriteria tersebut antara lain lahan, posisi, akses ruang, persaingan, transportasi dan keamanan. Dalam penilaian faktor subyektif menggunakan model AHP.Hasil dari penelitian ini adalah GDSS dengan menggunakan metode Brown-Gibson dan borda terbukti dapat mengakomodasi preferensi dari banyak pembuat keputusan. Dengan keluaran berupa nilai preferensi lokasi dan rangking memudahkan DM menentukan pemilihan lokasi. Lokasi yang paling banyak memiliki rangking tertinggi lebih berpotensi sebagai lokasi shelter baru.Kata kunci— Lokasi, Brown-Gibson, Borda AbstractThe purpose of establishment of the Transjogja bus fleet is to solve the problems of congestion, pollution and adequate public transport. To provide the best service, one thing is to place the shelter afforded in the right position. Department of Communication, cooperate with other agencies in the collection of executive aspirations, for the determination of the location of the new shelter.The combinations of Brown-Gibson and Borda methods, possible used for site selection as a group. This method is used to select an alternative location based on the size of a particular preference (preference measurement) taking into account the objective factors and subjective factors. Objective factor in the form of cost effectiveness is the total amount of expenses incurred for an alternative location. Subjective weighting factor of the decision makers of the criteria required in determining the location of the new shelter. These criteria include land, position, and access to space, competition, transportation and security. In the assessment of subjective factors is using the AHP model.The result of this study is to GDSS using the Brown-Gibson method and Borda shown to accommodate the preferences of many decision makers. With the output of the value location preference and rankings, it facilitated DM to determine new location. Location that has the highest ranking is more potent as a location for a new shelter.Keywords— Location, Brown-Gibson, Borda
Sistem Evaluasi Kelayakan Mahasiswa MagangMenggunakan Elman Recurrent Neural Network
Authors: Jiwa Permana Agus Aan , Prijodiprodjo Widodo 
Published: August 2020

AbstrakJaringan Syaraf Tiruan (JST) dapat digunakan untuk memecahkan permasalahan tertentu seperti prediksi, klasifikasi, pengolahan data, dan robotik.Berdasarkan paparan tersebut, sehingga dalam penelitian ini mencoba menerapkan JST untuk menangani permasalahan dalam program magang yang sedang dihadapi dalam upaya untuk meningkatkan kompetensi, pengalaman, serta melatih softskill mahasiswa.Sistem yang dikembangkan dapat digunakan untuk mengevaluasi kelayakan mahasiswa dalam program magang ke luar daerah dengan menerapkan Elman Recurrent Neural Network (ERNN), sehingga dapat memberikan informasi yang akurat kepada pihak jurusan untuk menentukan keputusan yang tepat.Struktur Elman dipilih karena dapat membuat iterasi jauh lebih cepat sehingga memudahkan proses konvergensi. Adapun metode pembelajaran yang digunakan adalah Backpropagation ThroughTime dengan model epochwise training mode. Sistem diimplementasikan dengan menggunakan bahasa pemrograman C# dengan basis data MySQL. Vektor input yang digunakan terdiri dari 11 variabel. Hasil penelitian menunjukkan bahwa sistem yang dikembangkan akan cepat mengalami konvergen dan mampu mencapai nilai error paling optimal (minimum error) apabila menggunakan 1 hidden layer dengan jumlah neuron 20 unit. Akurasi terbaik dapat diperoleh dengan menggunakan LR sebesar 0.01 dan momentum 0.85 dimana akurasi rata-rata dalam pengujian mencapai 87.50%. Kata kunci—Evaluasi, Kelayakan, Jaringan Syaraf Tiruan (JST), Elman Recurrent Neural Network, Magang Abstract Artificial Neural Network (ANN) can be used to solve specific problems such as prediction, classification, data processing, and robotics. Based on the exposure, so in this study tried to apply neural networks to handle problems in apprentice program facing in an effort to increase the competence, experience and soft skills training students. The system developed can be used to evaluate the students in the apprentice program to other regions by applying the Elman Recurrent Neural Network (ERNN), so it can provide accurate information to the department to determine appropriate decisions. Elman structure was chosen because it can be create much more rapidly iterations so as to facilitate the convergence process. The learning method used is Backpropagation Through Time with model epochwise training mode. The system is implemented using the C # programming language with a MySQL database. Input vector used consists of 11 variables. The results showed that the developed system will rapidly converge and can reach optimal error value (minimum error) when using one hidden layer with 20 units number of neurons. Best accuracy can be obtained using the LR of 0.01 and momentum 0.85 which average accuracy reaches 87.50% in testing. Keywords—Evaluation, Feasibility, Artificial Neural Network (ANN), Elman Recurrent Neural Network, Apprenticeship
Klasifikasi Varietas Tanaman Kelengkeng Berdasarkan Morfologi Daun Menggunakan Backpropagation Neural Network dan Probabilistic Neural Network
Authors: Syahputra Hermawan , Harjoko Agus 
Published: August 2020

Pengenalan daun memainkan peran penting dalam klasifikasi tanaman dan isu utamanya terletak pada apakah fitur yang dipilih stabil dan memiliki kemampuan yang baik untuk membedakan berbagai jenis daun. Pengenalan tanaman berbantuan komputer merupakan tugas yang masih sangat menantang dalam visi komputer karena kurangnya model atau skema representasi yang tepat. Fokus komputerisasi pengenalan tanaman hidup adalah untuk mengukur bentuk geometris berbasis morfologi daun. Informasi ini memainkan peran penting dalam mengidentifikasi berbagai kelas tanaman. Pada penelitian ini dilakukan pengenalan jenis tanaman berdasarkan fitur yang menonjol dari daun seperti fisiologis panjang (physiological length), lebar (physiological width), diameter, keliling (leaf perimeter), luas (leaf area), faktor mulus (narrow factor), rasio aspek (aspect ratio), factor bentuk (form factor), rectangularity, rasio perimeter terhadap diameter, rasio perimeter panjang fisiologi dan lebar fisiologi yang dapat digunakan untuk membedakan satu sama lain. Berdasarkan hasil pengujian, ditunjukkan bahwa hasil pencocokkan daun kelengkeng dengan menggunakan neural network lebih baik dibandingkan dengan hasil pencocokkan daun kelengkeng dengan menggunakan probabilistic neural network. Akan tetapi ekstraksi fitur dengan menggunakan morfologi belum dapat memberikan informasi pembeda yang signifikan bagi pengenalan tanaman varitas kelengkeng berdasarkan daunnya.Keywords— klasifikasi, morfologi daun, neural network, probabilistic neural network
PENDEKATAN ALGORITMA GENETIKA DALAM MENYELESAIKAN PERMASALAHAN FUZZY LINEAR PROGRAMMING
Authors: Dewi Lestari Siska , Subanar Subanar 
Published: August 2020

Fuzzy linear programming is one of the linear programming developments which able to accommodate uncertainty in the real world. Genetic algorithm approach in solving linear programming problems with fuzzy constraints has been introduced by Lin (2008) by providing a case which consists of two decision variables and three constraint functions. Other linear programming problem arise with the presence of some coefficients which are fuzzy in linear programming problems, such as the coefficient of the objective function, the coefficient of constraint functions, and right-hand side coefficients constraint functions. In this study, the problem studied is to explain the genetic algorithm approach to solve linear programming problems where the objective function coefficients and right-hand sides are fuzzy constraint functions.PT Dakota Furniture study case provides a linear programming formulation with a given objective function coefficients and right-hand side coefficients are fuzzy constraint functions. This study describes the use of genetic algorithm approach to solve the problem of linear programming of PT Dakota to maximize the mean income. The genetic algorithm approach is done by simulate every fuzzy number and each fuzzy numbers by distributing them on certain partition points. Then genetic algorithm is used to evaluate the value for each partition point. As a result, the Final Value represents the coefficient of fuzzy number. Fitness function is done by calculating the value of the objective function of linear programming problems. Empirical results indicated that the genetic algorithm approach can provide a very good solution by giving some limitations on each fuzzy coefficient.Genetic algorithm approach can be extended not only to resolve the case of PT Dakota Furniture, but can also be used to solve other linear programming case with some coefficients in the objective function and constraint functions are fuzzy.Keywords : Genetic Algorithm, Fuzzy Linear Programming, Linear Programming, Two-Phase Simplex Method
PENERAPAN SISTIM PENDUKUNG KEPUTUSAN DALAM SISTEM PENGUJIAN COMPUTERIZED ADAPTIVE TESTING
Authors: Rukli Rukli , Hartati Sri 
Published: August 2020

This study aims to make design decision support system adaptive to examinee ability to go to college.Decision support systems are made using one parameter logistic model by taking into account the difficulty level of questions adapted to the ability of the examinee. Questions are selected so that the items follow the ability of examinee more accurate assessment of ability with a lesser number of items.CAT a web-based applications require lesser number of items in determining the ability of examinee. College can determine the appropriate characteristics of the ability of examinee acceptance criteria for each department with domain weighting, and then determine the minimum level of capability that will be received and an appropriate amount to be received. Key word: Decision Support System, Computerized Adaptive Testing
A HYBRID Approach for Determine the Location of Stand Establishment at Batik Hatta Semarang
Authors: Cholil Saifur Rohman , Pertiwi Leatitia Daphne Adhisti Putri 
Published: August 2020

Semarang has various types of business. One of them is Batik Hatta Boutique, a small and medium business under the guidance of the Bank of Central Java that deals specifically in the world of batik art. This business develops and maintains its existence by participating in various exhibitions in several shopping centers as a media product promotion. To minimize losses, it needs accurate calculation in making decision of determining the location of establishment. It is reviewed by rental cost, location, layout, profit, and security. However, that calculation is still manual so it is inefficient and susceptible to error. Therefore, Decision Support System (DSS) is made to help in getting recommended location of best establishment at the Butik Batik Hatta. The method used in this research is the HYBRID MCDM AHP-TOPSIS Method. Validation process of this research has been done by using comparison of actual data and its result is 0.90 in the Sparman Correlation Coefficient. The conclusion is that the AHP-TOPSIS HYBRID MCDM method can be used in determining the location of establishment stand at the Batik Hatta Boutique.
Klasifikasi Lagu Berdasarkan Genre pada Format WAV
Authors: Tamatjita Nurmiyati , Harjoko Agus 
Published: August 2020

AbstrakDalam dunia yang berkembang pesat, media audio semakin komplek. Karena itulah diperlukan sebuah mekanisme penentuan jenis lagu (genre) yang tepat secara efektif dan efisien. Pencarian secara manual sudah tidak efektif dan efisien lagi karena banyaknya data yang tersimpan. Zero Crossing Rate (ZCR), Average Energy (E) dan Silent Ratio (SR) adalah 3 Feature Extraction yang digunakan untuk klasifikasi pencarian 12 genre.Tiga dimensi adalah bentuk visualisasi pengukuran tingkat kemiripan sebuah data berdasarkan hasil klasifikasi yang diinput oleh user. Dalam penelitian ini pengujian klasifikasi menggunakan metode 3, 6, 9 dan 12 genre melalui jarak terdekat (Euclidean Distance). Hasil pengujian yaitu menunjukkan bahwa 3 genre yaitu Balada, Blues dan Classic menunjukkan = 96,67%, 6 genre yaitu Balada, Blues, Classic, Harmony, Hip Jop dan Jazz menunjukkan = 70% dan 9 genre yaitu Balada, Blues, Classic, Harmony, Hip Hop, Jazz, Keroncong, Latin dan Pop menunjukkan = 53,33% serta 12 genre = 33,33% Kata Kunci— Zero Crossing Rate (ZCR), Average Energy (E), Silent Ratio (SR), Euclidean Distance Abstract Music genre is getting complex from time to time. As the size of digital media grows along with amount of data, manual search of digital audio files according to its genre is considered impractical and inefficient; therefore a classification mechanism is needed to improve searching. Zero Crossing Rate (ZCR), Average Energy (E) and Silent Ratio (SR) are a few of features that can be extracted from digital audio files to classify its genre. This research conducted to classify digital audio (songs) into 12 genres: Ballad, Blues, Classic, Harmony, Hip Hop, Jazz, Keroncong, Latin, Pop, Electronic, Reggae and Rock using above mentioned features, extracted from WAV audio files. Classification is performed several times using selected 3, 6, 9 and 12 genres respectively. The result shows that classification of 3 music genres (Ballad, Blues, Classic) has the highest accuracy (96.67%), followed by 6 genres (Ballad, Blues, Classic, Harmony, Hip Hop, Jazz) with 70%, and 9 genres (Ballad, Blues, Classic, Harmony, Hip Hop, Jazz, Keroncong, Latin, Pop) with 53.33% accuracy. Classification of all 12 music genres yields the lowest accuracy of 33.33%. Keywords— Zero Crossing Rate (ZCR), Average Energy (E), Silent Ratio (SR), Euclidean Distance
Analisis Tekstur untuk Klasifikasi Motif Kain (Studi Kasus Kain Tenun Nusa Tenggara Timur)
Authors: Setiohardjo Nicodemus Mardanus , Harjoko Agus 
Published: August 2020

AbstrakIndonesia memiliki banyak kekayaan budaya dalam bentuk kain tradisional, salah satunya kain tenun dari Nusa Tenggara Timur (NTT). Kain tenun dari tiap etnik di NTT memiliki cirikhas motif masing-masing yang merupakan manifestasi kehidupan sehari-hari, kebudayaan dan kepercayaan masyarakat setempat. Di mata pemerhati kain tenun NTT, asal kain tenun dapat diketahui dari motifnya. Tidak semua orang dapat membedakan asal daerah dari motif kain tenun tertentu dikarenakan sulitnya mendefinisikan karakteristik motif kain tenun suatu daerah dan beragamnya motif kain tenun yang ada dan komposisi warna yang beragam pula.Analisis tekstur adalah teknik analisis citra berdasarkan anggapan bahwa citra dibentuk oleh variasi intensitas piksel, baik citra keabuan maupun warna. Motif kain tenun terbentuk dari variasi intensitas warna sehingga dapat dipandang sebagai tekstur berwarna dari kain tenun. Penelitian ini bertujuan untuk mengetahui diantara pendekatan analisis tekstur menggunakan Gray Level Co-occurrence Matrix (GLCM) yang dikombinasikan dengan momen warna dan pendekatan analisis tekstur menggunakan Color Co-occurrence Matrix (CCM), metode manakah yang memberikan hasil lebih baik untuk klasifikasi motif kain tenun NTT.Hasil penelitian menunjukkan bahwa untuk klasifikasi motif kain tenun NTT, pendekatan analisis tekstur menggunakan metode CCM memberikan hasil lebih baik dibandingkan pendekatan analisis tekstur menggunakan GLCM yang dikombinasikan dengan momen warna. Kata kunci—klasifikasi citra, GLCM, CCM, momen warna, motif kain tenun NTT AbstractIndonesia have many culture in the form of traditional fabrics, one of them is woven fabric from Nusa Tenggara Timur (NTT). Each NTT ethnic has motif characteristic which ismanifestation of daily life, culture and the faith of local people. For a NTT woven fabric observer, the origin of a woven fabric can be known from the motif. But its difficult to recognising the origin of a woven fabrics because it is hard to define the characteristics of woven fabric motif from a region and wide variety of existing woven fabric motifs and also color composition.Texture analysis is image analysis technique based on assumption that an image formed by the variation of pixels intensity, both gray and color image. Woven fabric motif formed by the variation of color intensity that can be seen as color texture of the woven fabric. This study aims to determine between texture analysis using GLCM combined with color moment and texture analysis using CCM, which method gives better results for the NTT woven fabric motif classification.The results showed that for the NTT woven fabric motif classification, texture analysis using CCM gives better results than the texture analysis using GLCM combined with color moment. Keywords— image classification, GLCM, CCM, color moment, NTT woven fabric motif
Health benefits and economic advantages associated with increased utilization of a smoking cessation program
Authors: Datta Santanu K , Dennis Paul A , Davis James M 
Published: August 2020

Rationale, aim & objective:The goal of this study was to examine the health and economic impacts related to increased utilization of the Duke Smoking Cessation Program resulting from the addition of two relatively new referral methods – Best Practice Advisory and Population Outreach.Materials & methods:In a companion paper ‘Comparison of Referral Methods into a Smoking Cessation Program’, we report results from a retrospective, observational, comparative effectiveness study comparing the impact of three referral methods – Traditional Referral, Best Practice Advisory and Population Outreach on utilization of the Duke Smoking Cessation Program. In this paper we take the next step in this comparative assessment by developing a Markov model to estimate the improvement in health and economic outcomes when two referral methods – Best Practice Advisory and Population Outreach – are added to Traditional Referral. Data used in this analysis were collected from Duke Primary Care and Disadvantaged Care clinics over a 1-year period (1 October 2017–30 September 2018).Results:The addition of two new referral methods – Best Practice Advisory and Population Outreach – to Traditional Referral increased the utilization of the Duke Smoking Cessation Program in Primary Care clinics from 129 to 329 smokers and in Disadvantaged Care clinics from 206 to 401 smokers. The addition of these referral methods was estimated to result in 967 life-years gained, 408 discounted quality-adjusted life-years saved and total discounted lifetime direct healthcare cost savings of US$46,376,285.Conclusion:Health systems may achieve increased patient health and decreased healthcare costs by adding Best Practice Advisory and Population Outreach strategies to refer patients to smoking cessation services.
Burn Wound Healing Activity of Ethanolic Extract of Acalypha indica in Oinment Formulated against Rabbits (Ocyctagus caniculus)
Authors: Fitri Khairani , Khairani Tetty Noverita , Sinaga Fajar Apollo , Talunohi Amenia Gracia 
Published: August 2020

Objectives: The purpose of this study was to determine burn wound healing activity of Acalypha indica L. in oinment formulated.
Design: This study uses an experimental laboratory design. This study used rabbits as test animals induced by burns with hot iron plates on the back. Extract ointment applied to the wound then observed the development of healing.
Interventions: The extract was formulated in ointments with concentrations of 3, 5 and 7%. positive control used was ointment containing sesame oil and negative control used is an ointment base.
Main outcome measure: The results showed a concentration of 3% had a slow and low effect, at a concentration of 5% it had a moderate healing phase, and a concentration of 7% had a good healing phase.
Conclusion: The ointments containing Acalypha indica leaf extracts have good activity in healing burns in rabbits.
A Review on 2019-nCoV (SARS-CoV-2) in India
Authors: Mahawar Pawan Kumar , Sharma Abhay 
Published: August 2020

Background: The outbreak of the novel coronavirus, COVID-19, has been declared a pandemic by the WHO on March 11th of 2020. Novel Coronavirus infection mediated pandemic started in China in December 2019 and is still killing 1000s of people throughout the world. The second most populous country, India too is fighting against this infectious disease. The country is taking effective measures to curb the pandemic by exerting extensive campaigning on sanitation and strict social distancing measures to quell the explosion of the infection rate.
Treatment: No drugs are currently approved for Coronavirus Disease-2019 (COVID-19), although some have been tried. In view of recent studies and discussion on tested drugs on COVID-19 patients of India, I aimed to review existing literature and relevant websites regarding these drugs used in India including allopathic, plasma therapy,Ayurvedic and homeopathic medication.
Protective Effect of N-Acetyl Cysteine on Moringa Oleifera Aqueous Leaf Extract-Induced Hepatic Toxicity in Wistar Albino Rats
Authors: Agnes Namaganda , Josephine Kasolo N , Godfrey Bbosa S. , Robert Lukande , Ivan Kimuli , Godfrey Katamba , Haruna Muwonge , Isaac Okullo , Joshua Nfambi 
Published: August 2020

Background: Moringa oleifera (M. oleifera) is a commonly used medicinal and nutritive plant. The aqueous leaf extract from this plant contains a high concentration of alkaloids and they are toxic to body organs especially the liver leading to hepatotoxicity after long term exposure. However, if N-Acetyl cysteine (NAC) is administered together with M. oleifera extract, it may have a hepatotoxic protective effect.
Objective: To establish the protective effect of N-Acetyl cysteine against M. oleifera aqueous leaf extract-induced hepatotoxicity in the Wistar albino rats.
Methods: An experimental laboratory-based study conducted at department of Physiology Makerere University, College of Health Sciences. Three treatment groups of six Wistar albino rats each, were dosed intragastrically once a day for 28 days. Group I; negative control, received 8.05g/kg bwt of M. oleifera extract plus 1ml of normal saline (NS), Group II; test group, received 8.05g/kg bwt of M. oleifera extract plus 50mg/kg of NAC. Group III; positive control, received 750mg/kg bwt of Paracetamol plus 50mg/kg of NAC. On the 14th and 29th day, three animals selected randomly from each group were sacrificed; blood samples were collected, the liver was harvested for histopathological analysis. Serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), bilirubin and total protein levels were determined.
Results: There was an increase in serum ALT, AST and ALP levels in the M. oleifera extract plus NS group which was a sign of hepatotoxicity. The M. oleifera extract plus NAC group showed normal serum ALT, AST and ALP levels with no significant changes in the bilirubin (P-value = 0.9089) and total protein levels (P-value = 0.8858).
Conclusion: The results have provided evidence that NAC administration with M. oleifera extract effectively prevents the occurrence of M. oleifera leaves xtract- induced hepatotoxicity.