bluuebunny/crossref_metadata_2025_split huggingface dataset:
GENERALIZED PARETO DISTRIBUTION UNTUK PENGUKURAN VALUE AT RISK PADA PORTOFOLIO SAHAM SYARIAH DAN APLIKASINYA MENGGUNAKAN GUI MATLAB
Authors: Rahma Desi Nur , Maruddani Di Asih I , Tarno Tarno 
Published: September 2020

The capital market is one of long-term investment alternative. One of the traded products is stock, including sharia stock. The risk measurement is an important thing for investor in other that can decrease investment loss. One of the popular methods now is Value at Risk (VaR). There are many financial data that have heavy tailed, because of extreme values, so Value at Risk Generalized Pareto Distribution is used for this case. This research also result a Matlab GUI programming application that can help users to measure the VaR. The purpose of this research is to analyze VaR with GPD approach with GUI Matlab for helping the computation in sharia stock. The data that is used in this case are PT XL Axiata Tbk, PT Waskita Karya (Persero) Tbk, dan PT Charoen Pokphand Indonesia Tbk on January, 2nd 2017 until May, 31st 2017. The results of VaRGPD are: EXCL single stock VaR 8,76% of investment, WSKT single stock VaR 4% of investment, CPIN single stock VaR 5,86% of investment, 2 assets portfolio (EXCL and WSKT) 4,09% of investment, 2 assets portfolio (EXCL and CPIN) 5,28% of investment, 2 assets portfolio (WSKT and CPIN) 3,68% of investment, and 3 assets portfolio (EXCL, WSKT, and CPIN) 3,75% of investment. It can be concluded that the portfolios more and more, the risk is smaller. It is because the possibility of all stocks of the company dropped together is small. Keywords: Generalized Pareto Distribution, Value at Risk, Graphical User Interface, sharia stock
PEMODELAN REGRESI RIDGE ROBUST-MM DALAM PENANGANAN MULTIKOLINIERITAS DAN PENCILAN (Studi Kasus : Faktor-Faktor yang Mempengaruhi AKB di Jawa Tengah Tahun 2017)
Authors: Destiyani Eka , Rahmawati Rita , Suparti Suparti 
Published: September 2020

The Ordinary Least Squares (OLS) is one of the most commonly used method to estimate linear regression parameters. If multicollinearity is exist within predictor variables especially coupled with the outliers, then regression analysis with OLS is no longer used. One method that can be used to solve a multicollinearity and outliers problems is Ridge Robust-MM Regression. Ridge Robust-MM Regression is a modification of the Ridge Regression method based on the MM-estimator of Robust Regression. The case study in this research is AKB in Central Java 2017 influenced by population dencity, the precentage of households behaving in a clean and healthy life, the number of low-weighted baby born, the number of babies who are given exclusive breastfeeding, the number of babies that receiving a neonatal visit once, and the number of babies who get health services. The result of estimation using OLS show that there is violation of multicollinearity and also the presence of outliers. Applied ridge robust-MM regression to case study proves ridge robust regression can improve parameter estimation. Based on t test at 5% significance level most of predictor variables have significant effect to variable AKB. The influence value of predictor variables to AKB is 47.68% and MSE value is 0.01538.Keywords: Ordinary Least Squares (OLS), Multicollinearity, Outliers, RidgeRegression, Robust Regression, AKB.
PERAMALAN PRODUK DOMESTIK BRUTO (PDB) SEKTOR PERTANIAN, KEHUTANAN, DAN ‎PERIKANAN MENGGUNAKAN SINGULAR SPECTRUM ANALYSIS (SSA)
Authors: Hardi Desy Tresnowati , Safitri Diah , Rusgiyono Agus 
Published: September 2020

Forecasting is the process of estimating conditions in the future by testing conditions from the past. One of the forecasting methods is Singular Spectrum Analysis (SSA) which aim of SSA is to make a decomposition of the original series into the sum of a small number of independent and interpretable components such as a slowly varying trend, oscillatory components and a structureless noise. Gross Domestic Product data in the agriculture, forestry, and fisheries sector are time series data with trend and seasonal pattern so that it can be processed using the SSA method. The forecasting process of SSA method uses the main parameter (L) of 21 obtained by the Blind Source Separation (BSS) method. From forecasting, acquired group of 3 groups. Forecasting resulted the value of Mean Absolute Percentage Error (MAPE) is 1.59% and the value of tracking signal is 2.50, which indicates that the results of forecasting is accurate. Keywords: Forecasting, Gross Domestic Product in the agriculture, forestry, and fisheries sector, Singular Spectrum Analysis (SSA)
Pencarian Jalur Terpendek Menggunakan Metode Algoritma “Ant Colony Optimization” Pada GUI Matlab (Studi Kasus: PT Distriversa Buana Mas cabang Purwokerto)
Authors: Risqiyanti Via , Yasin Hasbi , Santoso Rukun 
Published: September 2020

For company, shortest distribution route is an important thing to be developed in order to obtain effectiveness in the distribution of products to consumers. One way of development is to find the shortest route with Ant Colony Optimization algorithm. This algorithm is inspired by the behavior of ant colonies that can find the shortest path from the nest to the food source. One example of a distribution company is PT Distriversa Buana Mas, also known as DBM. DBM is a physical distribution company covering the entire Indonesian archipelago specialized in the distribution of pharmaceuticals and consumer goods such as personal care, cosmetic and food products. DBM uses land transportation in 18 brances spread across Indonesia. One branch of DBM is in the Purwokerto region that distributes products to 29 stores in the Purbalingga region. This research is done with the help of GUI as a computation tool. Based on test results, the GUI system that has been built able to simplify and speed up the selection process of finding the shortest route for distribute product of DBM in the Purbalingga region. Keywords: Travelling Salesman Problem, Distriversa Buana Mas, Algorithm, Ant Colony Optimization, GUI
PENENTUAN FAKTOR-FAKTOR YANG MEMPENGARUHI INTENSITAS CURAH HUJAN DENGAN ANALISIS DISKRIMINAN GANDA DAN REGRESI LOGISTIK MULTINOMIAL (Studi Kasus: Data Curah Hujan Kota Semarang dari Stasiun Meteorologi Maritim Tanjung Emas Periode Oktober 2018 – Maret 2019)
Authors: Rohmana Shella Faiz , Rusgiyono Agus , Sugito Sugito 
Published: September 2020

Meteorologist develop rainfall forecasting methods to obtain better and more accurate rainfall information. One of them is the research of grid data and the method of grouping rainfall. According to BMKG, rainfall is classified into light, medium, and heavy rain. This study aims to determine the factors that influencing rainfall grouping using multiple discriminant analysis with a stepwise selection method. This study uses the daily climate data of Semarang City for period of October 2018 to March 2019. Based on its partial F value, the wind speed variable is eliminated so the significant variable on rainfall grouping are air temperature, air humidity, and wind direction. This analysis produces discriminant scores obtained from linear combinations between discriminant weights and observation values of significant independent variable. The classification procedure is based on the discriminant score each observations compared to cutting score resulted in classification accuracy of 62.89%. Multinomial logistic regression analysis is used to determine the effect of independent variables on rainfall intensity using the odds ratio. This analysis produces an estimate of the conditional probability of each group using significant independent variables are air temperature, air humidity, wind speed, and wind direction. The classification procedure is based on the largest conditional probability value between rainfall groups resulted in classification accuracy of 69.80%. Keywords: multiple discriminant analysis, multinomial logistic regresion, classification accuracy, rainfall
PEMODELAN KECEPATAN ANGIN DI KOTA SEMARANG MENGGUNAKAN ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (ANFIS)
Authors: Zahlevi Alifah , Prahutama Alan , Hoyyi Abdul 
Published: September 2020

Semarang city is the one of the strategic areas located in the middle of the north coast of Java that has a tropical climate with the high humidity and temperature, so it often causes a high rainfall and strong wind. So that is way Semarang city is ever sustained the extreme weather like a Tropical Storm. Since January 2016 until 2017 there are 34 cases of Tornado and 24 incidents of fallen trees because of the gale. For helping the people to be allert the effect of the strong winds can be done by predicting the average of wind velocity by using Adaptive Neuro-Fuzzy Inference System (ANFIS) method which can predict the climate change that do not require the assumption of white noise and normal residual distribution. In addition ANFIS is a group of neural network with input that has been fuzzied on the first or second layer, but the weight of the artificial neural is not fuzzied. The identification result of stationaries obtained the plot of PACF on the first and second lag, with the result that these lag which will be a input variable on ANFIS model. The result of ANFIS by using cluster FCM, the third total membership show the smallest percentage of RMSE in-sample is 0,0048 on the first lag, and the smallest percentage of RMSE out-sample is 0,008 on the ANFIS model with the input lag 1 and three cluster. Keywords : the average of wind velocity, ANFIS, RMSE
PERAMALAN MENGGUNAKAN METODE WEIGHTED FUZZY INTEGRATED TIME SERIES (Studi Kasus: Harga Beras di Indonesia Bulan Januari 2011 s/d Desember 2017)
Authors: Rahmawan Setya Adi , Safitri Diah , Widiharih Tatik 
Published: September 2020

Fuzzy Time Series (FTS) is a time series data forecasting technique that uses fuzzy theory concepts. Forecasting systems using FTS are useful for capturing patterns of past data and then to using it to produce information in the future. Initially in the FTS each pattern of relations formed was considered to have the same weight besides using only the first order. In its development the Weighted Fuzzy Integrated Time Series (WFITS) which gave a difference in the weight of each relation and high order usage has been appeared. Measuring the accuracy of forecasting results is used the value of Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). In this study both the first-order and high-order WFITS methods were applied to forecast rice prices in Indonesia based on data from January 2011 to December 2017. In this regard, the results of the analysis obtained data forecasting using Lee's high-order model WFITS algorithm (1,2,3) giving the value of RMSE and MAPE on the data testing in a row as many as 69,898 and 0.47% while for the RMSE and MAPE on the training data is as many as 70.4039 and 0.54%. Keywords: Fuzzy Time Series, Weighted Fuzzy Integrated Time Series, RMSE, MAPE, High-Order, Rice Prices
PERBANDINGAN NILAI KORELASI PADA KANONIK ROBUST (METODE MINIMUM COVARIANCE DETERMINANT) DAN KANONIK KLASIK (Studi Kasus Data Struktur Ekonomi dan Kesejahteraan Rakyat di Jawa Barat 2016)
Authors: Rahayu Widi , Sudarno Sudarno , Prahutama Alan 
Published: September 2020

Canonical correlation analysis is a multivariate statistical analysis that aims to examine the correlation between two groups of variabels in a way to maximize the value of correlation between variabels. The outlier in the data affect the covariance matrix is generated, So that use robust multivarat. There is robust multivariate approach to the analysis of canonical robust with MCD method (Minimum Covariance Determinant). This final project aims to determine comparison between correlation value of robust canonical with MCD and canonical classical methods. With a data theres containing of outliers in the case studies of people's welfare and economic structures in West Java in 2016. Used a set of variabels welfare of people consist of 6 variabel (Y) and a set of variabels economic structure which consists of four variabels (X). Based on the analysis results obtained that robust canonical correlation values better explain the correlation between two sets of variabels, the correlation value 0.99552, =0.91228, =0.71529, =0.63174, While the correlation value on classical canonical are 0.931489, 0.538672, 0.387099, 0.259318, Canonical robust can be interpreted more because it meets the test of significance are partially and directly, while the classical canon can not be interpreted further because it does not meet the test of the significance of the function. Keywords : Classical canonical correlation, canonical correlation robust correlation value, Minimum Covariance Determinant (MCD)
Focal areas of a high rate of fragile X in Indonesia: a long term follow up
Authors: Faradz Sultana MH , Winarni Tri Indah 
Published: September 2020

Fragile X syndrome (FXS) is the most common cause of inherited intellectual disability (ID) and a leading cause of autism spectrum disorder (ASD). FXS is caused by an expansion of CGG repeats >200 in the 5′ untranslated region of the promotor region fragile X mental retardation 1 gene (FMR1), which is located on Xq27.3. The abnormal CGG expansion leads to methylation and transcriptional silencing of the FMR1 gene, resulting in a reduction or loss of fragile X mental retardation 1 protein (FMRP) and causes long, thin, and immature dendritic spines, which lead to deficits in cognitive function, behavioral problems, and learning ability
Randomized Controlled Trial of Tranexamic Acid’s Effect on Bleeding Length: A Study on DMPA Users with Abnormal Uterine Bleeding Who Receive Low-Dose Oral Contraceptive Pill
Authors: Adawiyah Rabiah , Mulyantoro Inu , Dewantiningrum Julian , Pramono Noor 
Published: September 2020

ABSTRACTBackground: Contraceptive injection is the most common contraception used in Indonesia. Among the contraceptive injections, depomedroxy progesterone acetate (DMPA) is the most effective method with pregnancy rate of 0,3 pregnancy in 100 women annually. Abnormal uterine bleeding (AUB) is a common side effect occurred in DMPA users which leads to the discontinuation of contraception.Objective: To explore the effect of tranexamic acid on bleeding length for DMPA users with AUB who receive low dose Oral Contraceptive Pills (OCP).Methods: We performed double blind randomized control trial between two groups to investigate the effect of tranexamic in managing AUB in DMPA users who receive low dose OCP. This study was performed in Dr. Kariadi Hospital Semarang, Indonesia. Forty-four subjects were divided into two groups, equally. Group 1 received 250 mg tranexamic acid four times a day for 5 days and OCP once a day for 28 days, while Group 2 received placebo four times a day for 5 days and OCP once a day for 28 days. Both groups were evaluated for bleeding length during treatment and were analyzed using Mann Whitney for post treatment with tranexamic acid.Results: The mean bleeding length was 5.2±3.62 days and 9.2±6.16 days in group 1 and 2 respectively. These bleeding lengths were significantly different between both groups (p=0.018). The precentage of subjects in whom bleeding was stopped during the first week after initial treatment was significantly higher in group 1 than group 2 (77,3 % vs 45,5 %, p<0,030).Conclusion: Tranexamic acid significantly reduced the bleeding length in DMPA users who use OCP.
Knowing When and How to Fight: COVID-19 Between Viral Clearance and Immune Tolerance
Authors: Utomo Ahmad 
Published: September 2020

ABSTRACTCOVID-19 is a complex disease involving immunological, vascular, and metabolic pathology caused by and consequences of beta-coronavirus SARS-CoV-2 infection. One may use Sun Tzu analogy of war to fight COVID-19 and to survive infection. When enemy has not reached the shore, gathering much intelligence is key to know how the enemy moves and who would be the most vulnerable targets of enemy attacks. Physical distancing, massive nucleic acid testing, and identification of comorbidity may prepare for the incoming enemies. Physical distancing has helped to limit transmission of the virus that mainly due to close contacts with droplets coughed off infected individuals. Moreover, aerosolized virus particles may also contribute to spreading. Nucleic acid testing using real time PCR platform has been a diagnostic gold standard to identify infected individuals during early stage of infection. On the other hand, serological test to capture antibody against SARS-CoV-2 may be useful for immunosurveillance. Discovery of human ACE2 (angiotensin converting enzyme) protein as an obligate partner of SARS-CoV-2 viral entry has provided insights to mechanisms of serious post-infection ramifications to individuals having comorbidities such as hypertension, diabetes or heart conditions. When the enemy reaches ashore, thorough profiling of biomarkers involved in inflammation and coagulation (IL-6, lymphopenia, ground glass opacity, d-dimers, thrombocytopenia) may help predict disease progression and guide treatment strategy. While estimated 80% of infected individuals may recover on their own, the remaining 20% may require hospitalization and serious therapeutic intervention. Several clinical trials are underway such as repurposing existing drugs and evaluating efficacy of convalescence plasma therapy. Finally, vaccine development using genetic engineering may also help control the global spread if it is proven effective.
PENGARUH KEDALAMAN DAN JARAK DARI PANTAI TERHADAP KELIMPAHAN DAN POLA SEBARAN SAND DOLLAR DI PANTAI BARAKUDA PULAU KEMUJAN TAMAN NASIONAL KARIMUNJAWA
Authors: Afian Adhe Nur , Supriharyono - , Purwanti Frida 
Published: September 2020

Sand dollar merupakan kelas Echinoidea dari filum Echinodermata yang memiliki bentuk tubuh irregular yaitu bentuk tubuh bilateral dan pipih atau oval tanpa lengan, duri-duri menutup tubuh. Habitatnya di dasar perairan yang berpasir atau daerah berlumpur.Pantai Barakuda merupakan salah satu pantai di pulau Kemujan yang mempunyai daerah rataan pasir yang luas. Tujuan dari penelitian ini adalah untuk mengetahui komposisi jenis, kelimpahan dan pola sebaran sand dollar di Pantai Barakuda, untuk mengetahui variabel yang paling dominan antara kedalaman, jarak atau keduanya. Penelitian ini dilaksanakan pada bulan Juni 2013di Pantai Barakuda Pulau Kemujan Taman Nasional Karimunjawa, Kabupaten Jepara, Jawa Tengah.Metode penelitian yang digunakan adalah survei lapangan yang bersifat deskriptif, pengambilan data dilakukan menggunakan line transek sepanjang 50 m dan kuadran transek 1x1 m. Pengamatan dilakukan dengan mengambil 2 stasiun, stasiun A yaitu dengan berjarak 20 meter dari tepi pantai dan stasiun B dengan berjarak berkisar 70 meter dari tepi pantai. Setiap stasiun ditarik 3 line transek yang sejajar dengan pantai sepanjang 50 meter, dengan jarak 10 meter antar line transek. Pengambilan sand dollar didalam kuadran dilakukan pada tiap meter dengan melihat jenis dan jumlahnya. Data yang diperoleh dianalisa menggunakan analisa regresi berganda.Hasil penelitian menunjukkan di pantai Barakuda terdapat 14 corak jenis sand dollar (Laganum sp). Pengamatan dan perhitungan yang dilakukan, didapatkan jumlah Laganum sp di stasiun A sebanyak 351 individu, sedangkan pada stasiun B sebanyak 779 individu. Kelimpahan relatifnya terbesar yang didapatkan di pantai Barakuda pada corak jenis corak 1 dan corak 5 sedangkan kelimpahan relatif terkecil adalah corak 12 dan corak 14. Pola sebarannya sebagian besar termasuk mengelompok (clumped) dan beberapa termasuk seragam (uniform). Kelimpahan dan pola sebaran dipengaruhi oleh kedalaman dan jarak.
PENGARUH PENGELOLAAN KUALITAS AIR TERHADAP TINGKAT KELULUSHIDUPAN DAN LAJU PERTUMBUHAN UDANG VANAME (Litopenaeus vannamei) DI PT. INDOKOR BANGUN DESA, YOGYAKARTA
Authors: Fuady Muhammad Faiz , Haeruddin - , Nitisupardjo Mustofa 
Published: September 2020

Adanya pengelolaan kualitas air yang baik dapat menjaga kualitas air agar sesuai dengan baku mutu dan dapat meningkatkan produktivitas tambak. Penelitian ini bertujuan untuk mengetahui efektivitas pengelolaan kualitas air pada proses budidaya udang vaname yang di lakukan oleh PT. Indokor dan mengetahui pengaruh pengelolaan kualitas air terhadap laju pertumbuhan dan tingkat kelulushidupan udang vaname . Penelitian ini dilaksanakan pada bulan September - November 2012. Hasil yang diperoleh melalui pengukuran kualitas air pada budidaya intensif adalah kadar oksigen terlarut berkisar antara 3,9 - 7,8 mg/l, kadar karbondioksida bebas berkisar antara 2,6 − 5,1 mg/l, nilai pH berkisar antara 6,47 – 7,65, nilai suhu berkisar antara 24 0C − 29 0C, nilai kecerahan berkisar antara 20 − 39 cm, nilai salinitas berkisar 15 − 19 ppt, nilai kandungan nitrit berkisar 0,010 – 0,052 mg/l, dan nilai kandungan amonia berkisar 0,006 – 0,017 mg/l. Kemudian rata-rata nilai laju pertumbuhan udang adalah 0,24 gram/hari dan tingkat kelulushidupan sebesar 84 %. Sedangkan pada budidaya semi intensif di peroleh kadar oksigen terlarut berkisar antara 1,8 – 3,5 mg/l, kadar karbondioksida bebas berkisar antara 4,9 – 6,6 mg/l, nilai pH berkisar antara 5,63 – 6,64, nilai suhu berkisar antara 26 0C − 29 0C, nilai kecerahan berkisar antara 15 − 39 cm, nilai salinitas berkisar 16 − 18 ppt. Kemudian rata-rata nilai laju pertumbuhan udang adalah 0,18 gram/hari dan tingkat kelulushidupan sebesar 75 %. Dari hasil penelitian menunjukkan bahwa dengan adanya pengelolaan kualitas air yang baik pada budidaya intensif di PT. Indokor dapat meningkatkan nilai paramater kualitas air, laju pertumbuhan serta tingkat kelulushidupan udang vaname (Litopenaeus vannamei).
HUBUNGAN KERAPATAN RUMPUT LAUT DENGAN SUBSTRAT DASAR BERBEDA DI PERAIRAN PANTAI BANDENGAN, JEPARA
Authors: Ain Nur , Ruswahyuni - , Widyorini Niniek 
Published: September 2020

Pantai Bandengan adalah salah satu pantai pesisir utara Jawa yang terletak di Kabupaten Jepara, Jawa Tengah. Kabupaten Jepara memiliki potensi sumberdaya pesisir yang besar ditinjau dari keberadaan garis pantainya lebih dari 72 Km. Pantai Bandengan ini juga sebagai habitat rumput lautyang merupakan tumbuhan laut dasar perairan (fitobentos), makroalga, dan termasuk Thallophyta. Rumput laut tergolong tanaman yang hidupnya melekat pada substrat, seperti karang, lumpur, pasir, batu, dan benda keras lainnya atau bahkan melekat pada tumbuhan lain secara epifitik.Penelitian ini bertujuan mengetahui hubungan kerapatan rumput laut dengan substrat dasar berbeda di perairan Pantai Bandengan. Metode yang digunakan dalam penelitian ini deskriptif menggunakan line transek sepanjang 100 meter dan kuadran transek 1x1 meter dengan tiga kali pengambilan. Setiap kuadran transek dilakukan pengukuran parameter fisika dan kimia meliputi kedalaman, kecerahan, kecepatan arus, suhu air, dan pH (untuk mendukung hasil data sampling).Hasil yang didapatkan pada penelitian ini adalah sembilan jenis rumput laut yaitu Halimeda opuntia; Halimeda descoides; Halimeda macroloba; Chordoria flagelliformis; Padina crassa; Sargassum yendoi; Sargassum piluliferum; Sargassum confusum; dan Sargassum duplicatum. Kerapatan tertinggi ditemukan pada Halimeda opuntia (18,19%) atau total 103 individu dengan penutupan substrat (12,54 m2, terbanyak pada substrat pecahan karang). Sedangkan penutupan tertinggi terdapat pada jenis Sargassum duplicatum yaitu 15 m2. Berdasarkan hasil analisa data Chi Kuadrat didapatkan nilai X2 hitung sebesar 72,00 dan nilai X2 tabel sebesar 21,026. Hal tersebut dapat dinyatakan ada hubungan kerapatan rumput laut terhadap substrat dasar karena X2 hitung ≥ X2 tabel yang menyatakan terima H1 tolak H0.