Dwi Sunaryono

Decision mining for multi choice workflow patterns

Decision mining is combination of process mining and machine learning technique to retrieve information about how an attribute in a business process affects a cases route choice. It identifies decision point by looking for XOR-splits in petri-net workflow model and analyzing rules for each choice based on available attributes using decision tree. Problem emerges when decision mining technique is used on a workflow that does not use either XOR or AND splits, for example OR-split gateway logic. OR-split does not have explicit representation in petri nets and it makes decision mining algorithm cannot find its decision point. Workflow pattern that uses OR-split as its splitting logic is multi choice. Multi choice does not have its own explicit representation in form of petri net and it is problematic to apply decision mining to this workflow pattern. To make multi choice can be analyzed by decision miner some modification needs to be applied to the petri net representation of this pattern. This paper proposes modification of OR-split gateway representation in petri net. The new representation of OR-split uses combination the existing XOR-split and AND-split to make the model easier to be analyzed using decision miner. The proposed modification do not affect the conformance of event log and process model, but will allow each choice branch to be checked by decision miner.

Clustering of ERP business process fragments

Business process management technology at present has been developed and applied both in small and in large scale. Many companies and organizations use, for instance, Enterprise Resource Planning (ERP) or other business process-oriented system. In this paper, a clustering method in business process model based on its similarity is proposed. This clustering aims to group some similar business processes to form a common business process. A new business process, as a result, can be composed based on similar common business process in order to increase reusability. It is done according to similarity value among business processes that is by calculating the similarity based upon structural and behavioral similarity method. Meanwhile, the clustering process uses a graph partition approach. This research then shows that the clustering result of business process is precise at certain threshold value.

Business process composition based on meta models

Nowadays, Business Process Management (BPM) technology has been developed and widely applied in small and large scale. There are many companies and organizations implemented business process oriented information systems. Therefore, the flexibility issues become very important in managing large quantity of business processes because business processes are always changing overtime. There is a need of flexible business process models so that every possible changes can be done easily every time. Flexible business process models are represented by a reconfigurable model. In this paper, we proposed a method to manage business process model variations in order to efficiently develop the business process repository. The variation management is done by storing the common business processes and its variation in the repository. Then, we also propose meta models which contain information about the models stored in the repository. The results show that the meta models support the composition process of a new business process based on the common business process. The variation management has achieved to reduce storage redundancy up to 82%.

Workflow common fragments extraction based on WSDL similarity and graph dependency

Business process management technology has been developing and growing. In the industry, business processes continue to change over time. Changes occur due to consumer demand, technological innovation, and policy changes. Therefore, existing business processes should be able to adapt to any changes. Currently, the design phase is always ignored as the focused point in the business process development. The development process has only focused on the implementation. Hence, in this paper, we propose a method to form a reconfigurable business process model. The method consist of a series of sequential process. The process started with calculating similarity value of business processes based on its structure. Then, we perform the clustering process to the models based on similarity values. From every cluster, we extract the common fragment using dependency graph calculation. The experimental result shows that the proposed method can produce common fragments or reconfigurable models which can be rearranged to its variations. The common fragment has high flexibility and granularity. Research on reconfigurable models of business processes are still limited, therefore the result of this research can be used to start other researches.

Poverty classification using Analytic Hierarchy Process and k-means clustering

The successfulness of poverty alleviation programs depends on the accuracy of poverty data. The government needs to collect poverty data and analyze them to determine which poverty alleviation programs should be delivered to. A data collection process is often done by conducting a survey that consists of 14 survey variables. However, raw data collected from surveys are not useful if they are presented as is. These survey data need to be processed further to support decision making. This paper presents a method to process survey data into categories using Analytic Hierarchy Process (AHP) and k-means clustering method. The categories consist of three poverty levels, such as near poor, poor, and very poor. We also present a workflow of survey and a implementation of this method to collect and process poverty data.

Sales forecasting using Holt-Winters in Enterprise Resource Planning at sales and distribution module

Enterprise Resource Planning is a system used for managing all of the resources owned by the company, business activities, and information used to make a good business process. One of the modules in the ERP is sales and distribution. Sales and distribution is a module that handles the sale and delivery goods to customers to achieve their business objective. The use sales and distribution module is intended to simplify the process of selling to customers in accordance with the interests of customers for goods and services, makes it easy to check the sale of goods and delivery of goods, and facilitate the collection of customers who make a purchase of goods or services provided by the company, determines the appropriate services to customers, and forecast the amount of demand for goods desired by the customer. Sales forecasting is calculating the expected sales of a specific product and predicting future sales of the product. It helps in making informed business decisions. In this article some several of sales forecasting methods used, Holt-Winters Additive Method, and Holt-Winters Multiplicative Method applied in ERP. The implementation of sales forecasting using Holt-Winters method in the ERP can make the system more accurate and efficient in the determination of the amount of goods demanded by customers.

Intelligent Method for Dipstick Urinalysis Using Smartphone Camera

This paper introduces an intelligent method for helping people to maintain their healthy by doing a self urinalysis utilising a smartphone camera. A color sensing method using a smartphone camera is designed to determine the value of a reagent strip in a urinalysis dipstick. In the dipstick urinalysis, a color change in each reagent strip is examined. This color change is a result of the reaction of dipstick to the chemical contents of urine including pH, Protein, Glucose, Ketones, Leucocyte, Nitrite, Bilirubine, and Urobilinogen. Performing disptick urinalysis can be done in almost any places even on the very remote area where medical laboratory cannot be found, and it is much easier and cheaper than medical lab visit.

Rancang Bangun Web Kustom Menggunakan Open Graph Protokol pada Studi Kasus Web Jurusan Teknik Informatika

Pengenalan institusi melalui media internet seperti situs web dan sudah menjadi hal yang penting pada zaman ini. Informasi yang disampaikan melalui situs web lebih lengkap dan efisien dibanding media lain seperti televisi, radio, majalah, atau koran. Bahkan, saat ini hampir setiap orang dapat terhubung dengan media internet. Situs web jurusan Teknik Informatika sudah berjalan selama bertahun-tahun, namun terdapat beberapa hal yang perlu diperbaiki. Hal pertama yaitu performa kecepatan. Situs web perlu cepat agar pembaca tidak menunggu lama untuk mendapat informasi. Hal kedua yaitu banyaknya pembaca. Konten situs web yang bagus tidak akan berguna tanpa adanya pembaca. Salah satu cara untuk menjangkau pembaca yang lebih banyak adalah dengan membagikannya di media sosial seperti Facebook dan Twitter yang memiliki banyak pengguna. Dalam pembagiannya, sekadar mencantumkan link menuju situs web saja tidak cukup. Optimasi representasi situs web di media sosial diperlukan agar pengguna tertarik untuk mengunjungi link situs web tersebut. Hal ketiga yaitu kemudahan pembuatan artikel. Artikel seperti info lomba dan beasiswa membutuhkan penerbitan yang cepat. Hasil yang diharapkan dari pengerjaan penelitian ini adalah berupa aplikasi situs web kustom jurusan Teknik Informatika yang cepat, memudahkan penulis dalam menyalurkan artikel dan menerapkan Open Graph Protocol untuk memperbaiki representasi konten situs web di media social.

Determining bonus in Enterprise Resource Planning at Human Resource Management module using Key Performance Indicator

Bonus is a reward from company for an employee who gave the best work to the company. Reward is important to get the employees loyalty. Basically employee want to be appreciate what they do and Company want employees loyalty. There must be ‘win win’ solution between them. Then this paper explain how to determine bonus in Enterprise Resource Planning at Human Resource Management module based Key Performance Indicator on. There are several ways to determine bonus. the bonus is determined by how long the employee has worked at the company. It makes some disadvantages for the company, it caused no efficient human resource. The company has to give them a bonus based on years of service, not experience and skill. There is no guarantee if an employee has more years of service, then more profit the company gained. Furthermore, it can impact customer loyalty.

Mining decision to discover the relation of rules among decision points in a non-free choice construct

Decision mining is a combination of process mining and machine learning algorithms to retrieve information on how data attributes in a business process affect routing of a case. It analyzes decision point by looking for XOR-splits in petri-net workflow model and examining rules for each choice based on available attributes using decision tree. The rules for each decision point are based on the attributes influence to the case. Meanwhile, a non-free choice construct is a mixture of choice and synchronization, which will create limited choices in the workflow. The limitation of choice will then affect the rules found in non-free choice construct using decision mining technique. Limitation of rules makes it possible to examine the relation among rules in the workflow. The relation of these rules will emerge a certain property of a non-free choice construct. Rules for two decision points within a non-free choice construct will have similarities. Regarding to this, when the same rule is found during a decision mining process, we can determine that the decision points have a non-free choice relationship.