bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analog nature of quantum adiabatic unstructured search
Authors: Slutskii Mikhail , Albash Tameem , Barash Lev , Hen Itay 
Published: October 2019

Abstract
The quantum adiabatic unstructured search algorithm is one of only a handful of quantum adiabatic optimization algorithms to exhibit provable speedups over their classical counterparts. With no fault tolerance theorems to guarantee the resilience of such algorithms against errors, understanding the impact of imperfections on their performance is of both scientific and practical significance. We study the robustness of the algorithm against various types of imperfections: limited control over the interpolating schedule, Hamiltonian misspecification, and interactions with a thermal environment. We find that the unstructured search algorithm’s quadratic speedup is generally not robust to the presence of any one of the above non-idealities, and in some cases we find that it imposes unrealistic conditions on how the strength of these noise sources must scale to maintain the quadratic speedup.
Invariants of motion with stochastic resetting and space-time coupled returns
Authors: Pal Arnab , Kuśmierz Łukasz , Reuveni Shlomi 
Published: October 2019

Abstract
Motion under stochastic resetting serves to model a myriad of processes in physics and beyond, but in most cases studied to date resetting to the origin was assumed to take zero time or a time decoupled from the spatial position at the resetting moment. However, in our world, getting from one place to another always takes time and places that are further away take more time to be reached. We thus set off to extend the theory of stochastic resetting such that it would account for this inherent spatio-temporal coupling. We consider a particle that starts at the origin and follows a certain law of stochastic motion until it is interrupted at some random time. The particle then returns to the origin via a prescribed protocol. We study this model and surprisingly discover that the shape of the steady-state distribution which governs the stochastic motion phase does not depend on the return protocol. This shape invariance then gives rise to a simple, and generic, recipe for the computation of the full steady state distribution. Several case studies are analyzed and a class of processes whose steady state is completely invariant with respect to the speed of return is highlighted. For processes in this class we recover the same steady-state obtained for resetting with instantaneous returns—irrespective of whether the actual return speed is high or low. Our work significantly extends previous results on motion with stochastic resetting and is expected to find various applications in statistical, chemical, and biological physics.
Asymmetric twin-field quantum key distribution
Authors: Grasselli Federico , Navarrete Álvaro , Curty Marcos 
Published: October 2019

Abstract
Twin-Field (TF) quantum key distribution (QKD) is a major candidate to be the new benchmark for far-distance QKD implementations, since its secret key rate can overcome the repeaterless bound by means of a simple interferometric measurement. Many variants of the original protocol have been recently proven to be secure. Here, we focus on the TF-QKD type protocol proposed by Curty et al (2019 NPJ Quantum Inf.
5 64), which can provide a high secret key rate and whose practical feasibility has been demonstrated in various recent experiments. The security of this protocol relies on the estimation of certain detection probabilities (yields) through the decoy-state technique. Analytical bounds on the relevant yields have been recently derived assuming that both parties use the same set of decoy intensities, thus providing sub-optimal key rates in asymmetric-loss scenarios. Here we derive new analytical bounds when the parties use either two, three or four independent decoy intensity settings each. With the new bounds we optimize the protocol’s performance in asymmetric-loss scenarios and show that the protocol is robust against uncorrelated intensity fluctuations affecting the parties’ lasers.
Design a fuzzy inference system to determining superior commodities for create a village medium-term development plan
Authors: Anissudin W , Arkeman Y , Hermadi I , Sjaf S 
Published: October 2019

Abstract
The Village RPJM, also known as the Village Medium Term Development Plan, is something that must be prepared very carefully. The Village RPJM, especially the Sukadamai village, currently uses intuition alone, even the data held by the village head is still not updated. So that the Village RPJM does not provide maximum results. Therefore, it is necessary to make an intelligent system that can help the village head in determining the potential commodities in Sukadamai village. The latest data with high precision was obtained with the help of the IPB PSP3 using drones and participant assistance. This intelligent system uses a Fuzzy Inference System (FIS) to determine the commodities that have potential in the town of Sukadamai. The input variables used in this study are 10. For the potential of the land and market potential, each of the 27 rules and for the potential of the citizens to produce 64 rules. In the next FIS process, it produces 27 rules to get a potential commodity, so the total rules obtained are 145 rules. Hopes that with this intelligent system, in making the Village RPJM, the village government can be more focused on developing superior commodities in the Sukadamai village.
Implementation of hybrid sampling technique for predicting active compound and protein interaction in unbalanced dataset
Authors: Kusuma W A , Rahmi A S , Heryanto R 
Published: October 2019

Abstract
Indonesia Jamu Herbs (Ijah) web server aims to predict Jamu efficacy based on interaction between active compound and disease’s protein. However, the interaction between compound and protein data is unbalance since there are many unknown interactions between active compounds and protein target. Thus, the prediction result is still not optimal. In this research, the hybrid sampling technique, combining complementary fuzzy support vector machine (CMTFSVM) and synthetic minority oversampling technique (SMOTE) was used to handle imbalanced data interaction between active compound and protein for Ijah, web server to predict candidate Jamu formula for certain disease. Performance was measured using geometric mean (Gmean), area under curve (AUC), and accuracy. The evaluation results showed that the hybrid sampling technique could increase the instance of minority class three times. Moreover, the prediction model could obtain the value of 0.8346, 0.6812, and 0.5319 for accuracy, Gmean, and AUC, respectively.
Analysis of farming efficiency and smart farming system development in supporting garlic self-sufficiency: A concept
Authors: Waryanto B , Agustina T , Tjiptodharmono D 
Published: October 2019

Abstract
In Indonesia, the agricultural sector has a strategic role in sustaining the national economy. Various policies have been made with the aim of increasing the strategic role, both in the form of policies to achieve food self-sufficiency, reduce imports and even policies to encourage exports. One of the important commodities in the agricultural sector is garlic. This commodity is the government’s priority to be managed and targeted for self-sufficiency by 2021. This paper tries to trace the success of garlic farming through data studies and related literature. The review of existing data shows that over the past four years (2014 to 2017) the ratio of garlic production to imports was very small just only 4.15%, indicating that Indonesia still depends on imported garlic. Amount of imported garlic grew 5.09% per year, but on the other hand, domestic production grew negatively -1.73%, meaning that domestic production is still not enough for domestic consumption. As a discouraging form towards the achievement of self-sufficiency, this paper also reviewed the literature on the efficiency concept of garlic farming at the farm level through the approach of econometric models, as well as the concept of developing smart farming systems used for product tracking functions to the consumer level, on the contrary can be traced back to products produced by farmers. Through the offering of these two thought concepts, it is expected to be contribute in supporting the government program to achieve garlic self-sufficiency.
Spatial model for predicting sugarcane crop productivity using support vector regression
Authors: Gaffar A W M , Sitanggang I S 
Published: October 2019

Abstract
Sugarcane which is the main ingredient of sugar production has a very high production demand so it must have a balance with the level of productivity. Sugarcane productivity in Indonesia can only reach 5.8 tons/ha which is still relatively low. In recent years sugarcane farmers have felt the decline in sugarcane production due to climate change which has affected the success of sugarcane planting so that sugar production has not been in line with national needs. This study aims to build a prediction model for the productivity of sugarcane crops in each area of Java Island based on climatic factors. The climate data used are collected from Indonesian Agency for Meteorology, Climatology, and Geophysics from 2006 to 2015. The method used is Support Vector Regression (SVR) using a radial base kernel function with a generalized neighbourhood matrix as a spatial model. The prediction model has RMSE of 0.1203954 and correlation of 0.9459743. The results of visualization of sugarcane productivity mapping show that areas in East Java have a higher value of productivity increase than areas in other provinces. Based on the results obtained, the model used has a quite good performance in predicting the productivity of sugarcane.
Operational risk evaluation and mitigation for palm oil supply chain: a case study at x co.
Authors: Safriyana  , Marimin  , Anggraeni E , Sailah I 
Published: October 2019

Abstract
Risk analysis in the palm oil suppy chain is essential to achieve the optimum efficiency and effectiveness of the supply chain flow. One of the most common types of risk found in the palm oil supply chain is operational risk. The objectives of the research were to model palm oil supply chain risk identification and to model its risk mitigation. Measurement of operational risk required in an effort to improve the performance of the palm oil supply chain, the method used in the assessment of this type of risk is Failure Mode and Effect Analysis-House of Risk (FMEA-HOR) through two stages of modelling, the analysis and evaluation stages used to know the risk event and risk agent known as HOR 1. Meanwhile the stages of risk mitigation measures applied to handle the potential risk types known as HOR 2. Based on the results of operational risk identification in the palm oil supply chain, 31 types of risk events and 20 risk agents were obtained. Furthermore, risk mitigation measures were based on the potential risk agents generated, converged into 8 risk proactive actions that are prioritized based on costs and resources effectiveness. The results of priorities proactive actions show that 1) maintenance’s labor training, 2) committing routine preventive and predictive maintenance, and 3) preparing alternate stand by equipment and machine units were necessary mitigation actions to be done.
A design of competitive cocoa agro-industry supply chain system in Putat village, Gunung Kidul district
Authors: Turnip D M S , Arkeman Y , Muslich  
Published: October 2019

Abstract
Inconsistency quality and availability of cocoa beans become a serious problem for cocoa agro-industry. In general, we can not trace whose cacao beans are processed in the industry. This is due to the lack of integrated supply chain consisting of farmer, collector, trader, exporter and industry. This study aimed to produce a design of competitive cocoa agro-industry supply chain system with dynamic system approach. Integrated partnership between Sidodadi farmer’s group in Putat village, Patuk subdistrict, Gunung Kidul district with TTP Nglanggeran, Cokelat nDalem and local collector give a competitive value for cocoa agro-industry supply chain. Through this, fermented beans directly distributed to industry and processed. Cocoa supply in scenario increase 2.61% from existing, decreasing the balance of cocoa beans supply demand up to 0.7%, raising the first level of cocoa beans quality up by 2022, and lifting the accumulation of Farmers group’s profit up to 29.31%. The design of this system is expected to inform cacao stakeholders about the importance of partnerships to improve cocoa agro-industry competitiveness.
Quality characteristic determination of red dragon fruit noodle with Kano Model and QFD Method
Authors: Isharyani M E , Wijaya Y , Sitania F D 
Published: October 2019

Abstract
Red dragon fruit noodles in Samarinda, East Kalimantan have quality attributes that differ from other food commercial products. Therefore, the determination of quality attribute of red dragon fruit noodles need to be investigated. This paper discusses the use of Kano model and Quality Function Deployment (QFD) method for determining the quality parameters of red dragon fruit noodles. Kano questionnaire and Voice of Customer (VOC) questionnaire were used to categorize consumer-defined attributes and the level of importance of consumer defined attributes. The result obtained that 14 attributes are in One Dimensional category, 1 attributes in Must Be category and 13 attributes in Indifferent category. It is finally concluded that the consumer prefer red dragon fruit noodles with soft texture, thoroughly cooked, easily carried, fast and practical served and served in hot temperature. Technical parameters that need to be exist are technical presentation and the amount of wheat flour.
Tracer study of CO2 enrichment for shallot growth in mini plant factory with CFD approach
Authors: Niam A G , Widodo S , Solahudin M , Sucahyo L , Nurjanah S 
Published: October 2019

Abstract
It has been proven that the effect of CO2 enrichment leads to faster growth and higher yields. Using environmental parameters controlling based on needs, responses, and performance of crops, CO2 level from 800 to 1500 ppm were able to accelerate the growth of shallot in mini plan factory. Therefore, CFD simulation was conducted to simulate and trace the distribution of CO2 with varying airflow inlet. Airflow inlet is two wall air conditioners (ACs) with the 2 pk specification. Both of ACs was attached at opposite walls. There were two combinations of ACs position, which are top-top (both of ACs were positioned approximately 10 cm below the ceiling) and top-center (an AC positioned approximately 10 cm below the ceiling and another positioned 60 cm below the ceiling). In the simulation, CO2 gas was injected into the inlet from 0.5 l min−1
to 2 l min−1
. The simulation was used for tracing CO2 injection and position that has the highest uniformity coefficient at the CO2 levels of around 800 ppm. It is proven through a numerical approach, the best ACs position is a top-top combination, with CO2 injected, is 2 l min−1
.
RiTx; Integrating among Field Monitoring System (FMS), Internet of Things (IOT) and agriculture for precision agriculture
Authors: Nugroho B D A , Aliwarga H K 
Published: October 2019

Abstract
As developing country with industrial revolution 4.0, agro-technology, Internet of Things (IoT), E-Commerce and logistics technology is an important point in Indonesia. Although there has been many agro-knowledge and information systems for famers, but a little information in integrating among agriculture, IoT and field monitoring systems (FMS) technology for farmers in Indonesia. RiTx or Agricultural Technology is one of application for farmers with integrating among agriculture, IoT and field monitoring system technology. RiTx provides realtime, localized soil and weather data and field-level agronomic intelligence, which support farmers to decide their decisions during planting until harvesting, so failure during planting season can be eliminated. The province of East Nusa Tenggara (NTT) is cluster of islands located in the south – eastern part of Indonesia. The monsoon season stretches from October to March each year. Outside of the monsoon season, the climate of NTT is relatively dry. This study focuses on applying FMS technology with IoT for agricultural precision. For this study, field monitoring system was set up in the field since 26 July 2017 in Kupang, NTT Province that is consisted of three main components, i.e., FieldRouter, Datalogger and the sensors. Here, there are several sensors that have been installed in the field, e.g., solar radiation, rain-gauge and soil moisture. As the results, the IT field monitoring system showed good performance and reliable for precision agriculture. The actual field conditions were monitored well in term of image, numeric, and graphical data acquisition. Based on monitored data, plant growth can be well monitored. In addition, dynamic changes of environmental parameters can be monitored as well. Finally, it can help farmers in the future, not only in Indonesia or South-East Asia but also in the world, so prosperity for farmers can be granted.
Land priority determination for paddy field extensification in Subang Regency - Indonesia
Authors: Santoso P B K , Widiatmaka  , Sabiham S , Machfud  , Rusastra I W 
Published: October 2019

Abstract
Extensification efforts in agriculture to increase paddy production can be done through the selection of land for the development of paddy fields from available land. Every inch of land has different characteristics, which can be used for the selection of land suitable for a use, including for paddy fields. This study aims to delineate available land and set priorities for the development of paddy fields in Subang Regency. The main methodology used is a multicriteria-based land evaluation. The land attribute is weighted using the AHP technique from the assessment of 8 experts. Land availability was obtained from a combination of Weighted Linear Combination method and Geographic Information System. The results of the study found suitable land for paddy field extensification. Prioritization results showed that 76,115 hectares of land had high priority, 7,165 hectares had moderate priority, 55,280 hectares had low priority, and an area of 19,561 hectares is land that is not recommended for use. The land available for extensification of paddy fields from suitable land is 9,885 hectares with a composition of 73.24% (7,240 hectares) high priority, 21.20% (2,096 hectares) moderate priority, 3.36% (530 hectares) low priority, and 0.19% (19 hectares) are not recommended for paddy field extensification.
Executive information system lecturer mobility and scientific reputation of higher education
Authors: Indriani Y D , Seminar K B , Sukoco H 
Published: October 2019

Abstract
Lecturer mobility and scientific reputation is one of the key indicators for the establishment of world class university. The total number of papers published in the academic journals indexed by Elsevier’s Scopus database per scholar, and scholarly publications are one of the parameters for universities in the world are ranked. Those are challenges for the Executives Boards in universities to develop strategies of the existing conditions in order to plan programs to support the vision of universities. Executive Information System is required to display information strategically based on the existing data conditions. The present research identified a web-based Executive Information Systems called SIMORI. It is the system development method using System Development Life Cycle (SDLC) approach through system investigation step with feasibility study, system analysis, design analysis, and implementation. Critical factors for the success of the system are good data governance, while the data currently displayed still need to be completed and improved. The strategy to be developed will be managing mobility data of scientific reputation by involving all Faculties and the Departments of university to up-date data through Academic Management Information System, to be verified by the executive and will be presented as strategic information for the university communities.
Design for improvement of sugar factory performance based on statistical thinking
Authors: Kustiyo A , Arkeman Y 
Published: October 2019

Abstract
The amount of sugar production is determined, among others, by the quality of sugar cane and the performance of sugar factory equipment. The quality of sugar cane as an agricultural product is influenced by the quality of sugar cane seeds, soil conditions and climate. The differences in the factors affect the quality of sugarcane production. Sugarcane milling is not based on the quality of sugarcane but on the arrival time to the factory. Under this condition, different sugarcane qualities will be milled together. As a consequence, it may not yield the optimal sugar production. In the sugar production process, equipment performance must always be monitored. Equipment failure will reduce the amount of sugar produced. Therefore, efforts to increase sugar production must consider both factors, namely the variation of input quality and monitoring of equipment performance. One approach in solving this problem is statistical thinking approach. The purpose of the paper is to design the performance improvement of sugar factory based on statistical thinking. The improving activity based on statistical thinking will concentrate on manufacturing process enhancement and problem breaking that rely on realizing and degrading variation. The study shows that the statistical thinking approach potentially able to increase sugar production using process enhancement framework and overcome factory equipment failure using problem breaking framework.
Management of demersal fish of Kotania Bay, Western Part of Seram, Maluku Province, Indonesia
Authors: Huliselan N.V. , Wawo M. , Tuapattinaja M. A. , Sahetapy D. 
Published: October 2019

Abstract
Research to study demersal fish in Kotania Bay was conducted from June 2017 to August 2018. The results showed that demersal fish species fished in Kotania Bay consisted of 99 species from 6 families namely Serranidae, Lutjanidae, Scaridae, Lethrinidae, Mullidae and Labridae. The most abundant species groups were species of family Serranidae and Lutjanidae (35 and 25 numbers of species respectively). Demersal fish species are mainly used for human consumption and the caught tend to have high value, therefore, fishers in Kotania Bay exploited the demersal fish intensively. Several important species of family Serranidae and family Lutjanidae are the most abundant fish species in the caught, but some of demersal fish in Kotania Bay are now overexploited, this trend has appeared since the year 2000’s. Low fish catch and income of most fishers along coast of Kotania Bay and in addition to their reliance on fishing as a livelihood, has contributed to continued overexploitation. Fishing activities of demersal fish in Kotania Bay depend on monsoon, and the high catch of fish was in January, February, and March (4,560, 4,200 and 3840 kg respectively). Regarding to the overfished of demersal fish in Kotania Bay, therefore, are recommended some forms and regulations of management for demersal fisheries recovery and sustainability, such as restrictions fishing gears, collaboration stakeholders between levels of management, control of demersal fish utilization, alternative livelihood for fishers, protection habitat of fish through conservation and rehabilitation program, and encouraging co-management.