Productivity of Peanut at Abandoned Pumice Mining Land in West Nusa Tenggara, Indonesia

Four packages of peanut technologies, PTB1 (soil tillage, certified seed, dibbling with 40cmx10cm and 2 seeds/hole, seeds treatment, fertilizer 200 kg/ha Phonska (NPK fertilizer), and pests control with IPM methods), PTB2 (similar to PTB1 except for no seed treatment and fertilizer of urea for 50 and SP36 for 100 kg/ha), PTB3 (similar to PTB2 except for 40x15cm spacing and fertilizer of urea 50 kg/ha), and PTP (famer practice, uncertified seeds, irregular spacing, no seed treatment, no fertilizer, and no pest control) were examined the agronomic adaptability and economy value in pumice stone mining land at the Akar-akar Village of North Lombok District. Each package that was applied on an area of 0.5 ha was repeated three times at different farmers group. Economic analysis was performed to obtain revenue over variable costs (RAVC) and marginal benefit cost ratio (MBCR). The results showed that the highest fresh pod yield (4.50 t/ha) and the highest dry pod yields (2.30 t/ha) were observed for PTB1. These values, however, did not significantly different from those of other PTP treatments. The lowest fresh and dry pod yields were observed for at PTP treatment and these were significantly different from all PTB treatments. The highest of net income of farmers from the application of package of technologies was obtained from the PTB1 (Rp 8.970.00), while the highest MBCR value was obtained from the PTB3 (5.51). This indicated that the PTB3 was the promising peanut package of technology that may be applied on abandoned pumice stone mining land

Penerapan Metode Drill Untuk Meningkatkan Aktivitas Belajar Dan Kemampuan Mengurus Diri Sendiri Bagi Anak Tunagrahita

The purpose of this research is to improve learning activity and self-help ability in handicapped children in self-help learning grade D3 in SLB C Negeri Singaraja academic year of 2012/2013 through drill method implementation. This research is an action research administered in SLB C Negeri Singaraja. Subject in this research was six students grade D3 SLB C. Data of learning activity dan self-help ability were collected by using observation sheet and analyzed descriptively. Result for the cycle I shows that two students (33,33%) have passed the learning activity criterion (criterion good) and one student (16,67%) have passed the self-help ability criterion (criterion good). The point emphasized in implementation cycle I was intensifying the drill learning method. The result in cycle II shows that all students (100%) have passed the learning activity criterion and self-help ability criterion with the category of very good

Predictive Monitoring of Business Processes

Modern information systems that support complex business processes generally maintain significant amounts of process execution data, particularly records of events corresponding to the execution of activities (event logs). In this paper, we present an approach to analyze such event logs in order to predictively monitor business goals during business process execution. At any point during an execution of a process, the user can define business goals in the form of linear temporal logic rules. When an activity is being executed, the framework identifies input data values that are more (or less) likely to lead to the achievement of each business goal. Unlike reactive compliance monitoring approaches that detect violations only after they have occurred, our predictive monitoring approach provides early advice so that users can steer ongoing process executions towards the achievement of business goals. In other words, violations are predicted (and potentially prevented) rather than merely detected. The approach has been implemented in the ProM process mining toolset and validated on a real-life log pertaining to the treatment of cancer patients in a large hospital

A Method to Improve the Early Stages of the Robotic Process Automation Lifecycle

The robotic automation of processes is of much interest to organizations. A common use case is to automate the repetitive manual tasks (or processes) that are currently done by back-office staff through some information system (IS). The lifecycle of any Robotic Process Automation (RPA) project starts with the analysis of the process to automate. This is a very time-consuming phase, which in practical settings often relies on the study of process documentation. Such documentation is typically incomplete or inaccurate, e.g., some documented cases never occur, occurring cases are not documented, or documented cases differ from reality. To deploy robots in a production environment that are designed on such a shaky basis entails a high risk. This paper describes and evaluates a new proposal for the early stages of an RPA project: the analysis of a process and its subsequent design. The idea is to leverage the knowledge of back-office staff, which starts by monitoring them in a non-invasive manner. This is done through a screen-mousekey- logger, i.e., a sequence of images, mouse actions, and key actions are stored along with their timestamps. The log which is obtained in this way is transformed into a UI log through image-analysis techniques (e.g., fingerprinting or OCR) and then transformed into a process model by the use of process discovery algorithms. We evaluated this method for two real-life, industrial cases. The evaluation shows clear and substantial benefits in terms of accuracy and speed. This paper presents the method, along with a number of limitations that need to be addressed such that it can be applied in wider contexts.Ministerio de Economía y Competitividad TIN2016-76956-C3-2-

Survei Malariometrik di Kecamatan Sindue dan Ampibabo, Kebupaten Donggala, Propinsi Sulawesi Tengah

Malaria is still a serious public health problem in Central Sulawesi. Only some parts of Donggala regency which it consists of the west and east coast areas have been included in malaria control programme with house spraying. To obtain the appropriate malaria control method in these areas, the malariometric survey was conducted in Sindue and Ampibabo subdistricts on May 1995. The objectives of this survey were to assess the endemicity and malaria parasite rate, and to identify the species of Plasmodium in those subdistricts. The malariometric survey was carried out on all children aged 0-9 year and clinical malaria patients from the 6 villages of Sindue subdistrict and another 6 villages of Ampibabo subdistrict. Physical examination included spleen examination by the Hackett method and malarial peripheral blood examination stained by Giemsa were performed. Clinical malaria and positive malaria patients were treated with chloroquine and primaquine regimen based on the Ministry of Health guidance. In Sindue and Ampibabo subdistrict, the SR (2-9 year), AES (2-9 year), CPR (0-9 year), IPR (0-11 mo), PR (2-9 year), FF (Pf and mixed) and SFR (Pf and mixed) were 26.9-53.4% and 21.5-64.3%, 1.9-2.5 and 1.9-2.4, 6.6-34.3% and 1.5-17.9%, 0-33.3% and 0-6.7%, 6.8-35.4% and 1.8-18.5%, 25.7-90.9% and 50.0-90.0%, 5.0-13.8% and 1.0-14.0% respectively. In Sindue subdistrict, there were falciparum malaria, vivax malaria, malariae malaria and mixed malaria infected by P. falciparum and P. vivax. However, in Ampibabo subdistrict there were only falciparum and vivax malaria.Sindue subdistrict is a mesoendemic-hyperendemic malaria area, high prevalence area, mainly infected by P. falciparum and there is active transmission. Ampibabo subdistrict is also a mesoendemic-hyperendemic malaria area, high prevalence area in several villages, mainly infected by P. falciparum and there is active transmission. The appropriate malaria control programme which could be implemented in Sumari, Taripa and Saloya villages are prompt treatment and distribution of bed nets. While in the other villages malaria control could also be implemented by house spraying especially in the villages with IPR >0% and mainly infected by P. falciparu

Discovering Business Area Effects to Process Mining Analysis Using Clustering and Influence Analysis

A common challenge for improving business processes in large organizations is that business people in charge of the operations are lacking a fact-based understanding of the execution details, process variants, and exceptions taking place in business operations. While existing process mining methodologies can discover these details based on event logs, it is challenging to communicate the process mining findings to business people. In this paper, we present a novel methodology for discovering business areas that have a significant effect on the process execution details. Our method uses clustering to group similar cases based on process flow characteristics and then influence analysis for detecting those business areas that correlate most with the discovered clusters. Our analysis serves as a bridge between BPM people and business, people facilitating the knowledge sharing between these groups. We also present an example analysis based on publicly available real-life purchase order process data.Comment: 12 pages. Paper accepted in 23rd International Conference on Business Information Systems (BIS 2020) to be published in a proceedings edition of the Lecture Notes in Business Information Processin

Business process variant analysis based on mutual fingerprints of event logs

Comparing business process variants using event logs is a common use case in process mining. Existing techniques for process variant analysis detect statistically-significant differences between variants at the level of individual entities (such as process activities) and their relationships (e.g. directly-follows relations between activities). This may lead to a proliferation of differences due to the low level of granularity in which such differences are captured. This paper presents a novel approach to detect statistically-significant differences between variants at the level of entire process traces (i.e. sequences of directly-follows relations). The cornerstone of this approach is a technique to learn a directly-follows graph called mutual fingerprint from the event logs of the two variants. A mutual fingerprint is a lossless encoding of a set of traces and their duration using discrete wavelet transformation. This structure facilitates the understanding of statistical differences along the control-flow and performance dimensions. The approach has been evaluated using real-life event logs against two baselines. The results show that at a trace level, the baselines cannot always reveal the differences discovered by our approach, or can detect spurious differences.This research is partly funded by the Australian Research Council (DP180102839) and Spanish funds MINECO and FEDER (TIN2017-86727-C2-1-R).Peer ReviewedPostprint (author's final draft

VISUAL PPINOT: A Graphical Notation for Process Performance Indicators

Process performance indicators (PPIs) allow the quantitative evaluation of business processes, providing essential information for decision making. It is common practice today that business processes and PPIs are usually modelled separately using graphical notations for the former and natural language for the latter. This approach makes PPI definitions simple to read and write, but it hinders maintenance consistency between business processes and PPIs. It also requires their manual translation into lower-level implementation languages for their operationalisation, which is a time-consuming, error-prone task because of the ambiguities inherent to natural language definitions. In this article, Visual ppinot, a graphical notation for defining PPIs together with business process models, is presented. Its underlying formal metamodel allows the automated processing of PPIs. Furthermore, it improves current state-of-the-art proposals in terms of expressiveness and in terms of providing an explicit visualisation of the link between PPIs and business processes, which avoids inconsistencies and promotes their co-evolution. The reference implementation, developed as a complete tool suite, has allowed its validation in a multiple-case study, in which five dimensions of Visual ppinot were studied: expressiveness, precision, automation, understandability, and traceability