An Analysis and Design of Mobile Business Intelligence System for Productivity Measurement and Evaluation in Tire Curing Production Line

AbstractBusiness intelligence (BI) system as an architecture of competencies, processes, technologies, applications and practices to support productivity measurement. It obviously needs a BI that support organization to declare any production constraints that currently or already occurred in such as tire curing industry. Overall Equipment Effectiveness (OEE) is used as a quantitative productivity measurement and become the base of company continuous improvement and evaluation. The objectives of this study are to identify critical parameters of production line in effectiveness measurement and machine utilization, analyze the requirement of information system as an Android based mobile BI System and to integrate the design into a mobile system. System requirement analyzed each interdependent measure in the real world of complexity by using BPMN 2.0. These measures are part of dashboard components in the proposed BI. The acquired data from a National forefront tire industry shows the OEE in three ratio measurement of availability, performance, and quality with 78%, 82.5% and 99.8% of scorecard respectively. In order to determine the status of production, the deployment of k-nearest neighbour (k-NN) gives 67.5% of accuracy rate. The critical parameters identification results to 8 (eight) significant constraints, which calculated using distance-based RELIEF attribute selection. Eventually this approach results big four constraints to be noted: (a) mold repair, (b) mold setting, (c) green tire shortage and (d) defect cure

Integration of Sustainable Value Stream Mapping (Sus. VSM) and Life-Cycle Assessment (LCA) to Improve Sustainability Performance

Sustainable manufacturing concept is adopted by many stakeholders for its framework, on considering environmental, social, and economic aspect, called as triple-bottom-line (TBL). It concerns the future of manufacturing review on sustainability and requires deeper evaluation on TBL and product life cycle as well as to see the environmental impact at process stage. In this  work, a proposed Sustainable Value Stream Mapping (Sus-VSM) as an extended traditional VSM   considers integration with Life-Cycle Assessment (LCA) to assess current condition in addition to analyze future sustainability improvement at a food based manufacturing. The current state presented all metrics associated with the TBL of manufacturing metrics. Calculation of critical metrics using the Borda Count Method (BCM) showed that speed-loss, total defect product, and heat loss were critical and chosen for further analysis. Analysis using 5 Whys analysis showed that the problems were mainly caused by the unstable material condition, the problem of filling area machinery, and operator disciplinary. Process life-cycle assessment was performed using Simapro v. 8.0 with  single score cooking and cleaning. It obtained 60 700 Pt and 108 Pt. Future improvement using Failure Mode and Effect Analysis (FMEA) proposed and could reduce lead time from 4967.46 seconds to 4759.17 seconds, cleaning time from 2.8 hours to 2.14 hours, and total defect product from 4.85/batch to 2.82 kg/batch. Future improvement on steam performance proposed and could reduce the total single score of cooking and cleaning to 59 500 Pt and 102 Pt

A Sentiment Knowledge Discovery Model in Twitter’s TV Content Using Stochastic Gradient Descent Algorithm

The use of social media that the explosive can be a rich source for data mining. Meanwhile, the development of television programs become increased and varied so motivate people to make comments on it’s via social media. Social network contains abundant information which is unstructured, heterogeneous, high dimensional and incremental in nature. Abundant data can be a rich source of information but it is difficult to identify manually. The contributions of this research are to perform preprocessing to address unstructured data, a lot of noise and heterogeneous; find patterns of information and knowledge of social media user activities in the form of positive and negative sentiment on twitter TV content. Some methodologies and techniques are used to perform preprocessing. They are eliminates punctuation and symbols, eliminates number, replace numbers into letters, translation of Alay words, eliminate stop word and Stemming Porter Algorithm. Methodology of this study was used Stochastic Gradient Descent (SGD).The text that has been through preprocessing produces a more structured text, reducing noise and reducing the diversity of text. So, preprocessing affect to the correctly classified istances and processing time. The experiment results reveal that the use of SGD for discovery of the positive and negative sentiment tends to be faster for large data or stream data. Correctly classified instance with a maximum of 88%

Production System Design bio-oil of Microalgae with POME as Raw Material For Media Cultivation

Palm Oil Mill Effluent (POME) produced by the Palm Oil Mill as a waste is now being used as a medium for cultivating microalgae for bio-oil raw materials. However, the bio-oil production process from POME raw materials is still limited to lab scale. Therefore, in this project, the analysis of bio-oil production system from microalgae for the development of existing production system. In this paper, the optimization model of bio-oil production from microalgae biomass is simulated into Digital Business Ecosystem (DBE) concept then analyzed to related stakeholders in system and interaction of each process or between fellow stakeholders. And the results are defined in the form of Information Communication and Technology (ICT). The method used for this DBE concept is Unified Modeling Language (UML) which is use case diagram and Business Process Model and Notations (BPMN) diagram. And to predict an increase in yield by using ARM (Association Rule Mining). The results of this study are shown in the use case diagram and BPMN consisting of five communities, namely raw materials community, cultivation community, harvesting community, extraction community and quality control (QC). The process of production and storage of the resulting data is illustrated in the BPMN diagram. In this paper the association rule is used to explore the relationship pattern between Cell Density attributes, Lipid Content and Light Intensity. The integration of association rule with a priori paradigm has succeeded in finding 34 rules with 11 valid rules top rank which have lift > 1 of relation between attribute

Pengukuran Kinerja Peneliti Badan Litbang Pertanian dengan Metode Data Mining dan Balance Scorecard

Tulisan ini membahas metode penilaian kinerja untuk penelitian di Badan Litbang Pertanian yang bertujuan untuk mendapatkan gambaran kinerja peneliti. Kinerja peneliti diukur dengan menggunakan metode balanced scorecard dan data mining . Balanced scorecard digunakan sebagai metode untuk menentukan atribut atau parameter yang dapat mempengaruhi kinerja peneliti. Data mining digunakan untuk mengolah data peneliti. Atribut yang dipilih adalah jenis kelamin, usia, pendidikan, jenjang jabatan peneliti, DP3, publikasi dan kegiatan penelitian. Hasil dari pengolahan data tersebut yaitu atribut publikasi merupakan simpul awal dengan nilai entropi 0.000 yang berarti bahwa atribut tersebut sangat berpengaruh terhadap kinerja peneliti. Kemudian diikuti atribut kegiatan dengan nilai entropi 0.001, atribut penghargaan dengan nilai entropi 0.003 dan atribut umur dengan nilai entropi 0.007. Atribut terpilih tersebut diklasifikasi dengan menggunakan metode pohon keputusan ( decision tree ). Decision tree merupakan model prediksi menggunakan struktur pohon atau struktur berhierarki. Setiap percabangan ( root ) menyatakan kondisi yang harus dipenuhi dan setiap ujung pohon menyatakan kelas data. Dalam root publikasi diperoleh class target yang dominan yaitu cukup, artinya bahwa peneliti Badan Litbang Pertanian sebagian besar mempunyai kinerja yang cukup baik

PEMODELAN FIXED TIME PERIOD UNTUK SISTEM PENGENDALIAN PERSEDIAAN PADA GUDANG REGIONAL

Inventory control modelling is utilized to optimize warehousing cost and the availability of product and raw material while keeping customer satisfaction level. A formulation of fuzzy time series based on raw material planning for  fixed-time period safety stock model was proposed to enhance forecasting accuracy in limited  data availability.  Safety stock levels were computed in monthly fashion to optimizing the most appropriate capacity in each regional warehouse. Forecasting accuracy was based on MAPE indicator. By deploying forecasted data,  the   calculation of product quantity and capacity level were set to correspond  with the target of product box quantity to produce. The result showed that the forecasting of six products in four regions showed the range of  MAPE values with  minimum at 0.29% and maximum at 1.94% level. The implementation of formula on a real field application had increased the  data flow transaction and mobility amount among stakeholders. Keywords: formulation, fuzzy tim series forecasting, inventory control, modelling, MAP

Rancangan Model Performansi Risiko Rantai Pasok Agroindustri Susu dengan Menggunakan Pendekatan Logika Fuzzy

Titik kritis dari performansi dan risiko rantai pasok agroindustri susu terletak pada karakteristik produknya yang mudah rusak. Risiko tertinggi yang teridentifikasi pada rantai ini adalah risiko susu terkontaminasi bakteri dan antibiotik. Risiko ini muncul dari rangkaian aktivitas yang terjadi mulai dari peternakan, koperasi dan Industri Pengolahan Susu (IPS) yang akan mempengaruhi performasi rantai pasok keseluruhan. Paper ini bertujuan untuk merancang model performansi dan risiko rantai pasok agroindustri susu dengan menggunakan pendekatan Fuzzy Assosiated Memories (FAMs). Logika fuzzy digunakan untuk menerjemahkan suatu besaran yang diekspresikan menggunakan bahasa (linguistic). Secara umum dalam sistem logika fuzzy terdapat empat buah elemen dasar, yaitu: basis kaidah (rule base), mekanisme pengambilan keputusan (inference engine), proses fuzzifikasi (fuzzification) dan proses defuzzifikasi (defuzzification). Ada tiga komponen yang dipertimbangkan dalam rancangan model yaitu profil performansi, profil risiko dan eksposur risiko dalam ukuran waktu, biaya dan kualitas. Tahap pertama dimulai dengan menganalisis eksposur risiko yang tidak terhindarkan yang meliputi analisis karakteristik lingkungan dan konfigurasi serta karakteristik rantai pasok agroindustri susu. Tahap kedua adalah menganalisis eksposure risiko yang dapat dihindari. Tahap ketiga adalah mengubah eksposur risiko ke dalam ukuran performansi waktu, biaya dan kualitas. Pada tahap kedua dihasilkan magnitude risiko, yang merupakan fungsi dari nilai probabilitas dan severity yang dilakukan dengan menggunakan Fuzzy Assosiated Memories (FAMs).Dengan model ini diharapkan dampak kerusakan dari risiko yang muncul pada rantai pasok agroindustri susu dapat terukur dan dapat diminimasi sehingga dapat meningkatkan ketangguhan (robustnes) dari rantai pasok

Sentiment Mining of Community Development Program Evaluation Based on Social Media

It is crucial to support community-oriented services for youth awareness in the social media with knowledge extraction, which would be useful for both government agencies and community group of interest for program evaluation. This work provided to formulate effective evaluation on community development program and addressing them to a correct action. By using classification based SVM, evaluation of the achievement level conducted in both quantitative and qualitative analysis, particularly to conclude which activities has high success rate. By using social media based activities, this study searched the sentiment analysis from every activities comments based on their tweet. First, we kicked off preprocessing stage, reducing feature space by using principle of component analysis and estimate parameters for classification purposes. Second, we modeled activity classification by using support vector machine. At last, set term score by calculating term frequency, which combined with term sentiment scores based on lexicon.The result shows that models provided sentiment summarization that point out the success level of positive sentiment

The Evaluation of Customer Satisfaction Survey Follow-Up in LPPOM MUI

Customer satisfaction survey is a standard method used by service providers in order to obtain feedback from the customer as well as close the gap between customer expectation and perception of service quality. Feedback from customers can make them possible to define the level of quality of service by themselves. If a service provider can satisfy its customers, it means that it will retain its customers. LPPOM MUI, as an authorized halal certifying body in Indonesia, has conducted a customer satisfaction survey three times from 2015 up to 2017. After conducting the survey, LPPOM also performed a follow-up based on the result of the survey. The purposes of this research are (1) to get to know about the follow-up of customer satisfaction evaluation of LPPOM MUI, (2) to analyze the impact of the follow-up implementation progress versus re-evaluation by LPPOM MUI’s customer group on the follow-up, (3) to provide recommendation(s) if the customers perceive the follow-up implementation still does not fulfill their service quality expectation. The methods used were a qualitative analysis based on the follow-up of LPPOM MUI’s customer satisfaction survey versus re-evaluation on LPPOM MUI’s seven customer groups on the follow-up. The result shows that all quality service attributes need improvement to meet customer expectations. They are namely 1) the ease of contacting the Call Center 14056 or LPPOM MUI, 2a) The availability of notification if any change or dysfunction of CEROL SS-23000 and 2b) replying time to customer email (3a) Dealing time to halal certification process (3b) dealing time to post-audit stage (3c) Dealing time to LPPOM MUI approval of new material of the company. Keywords: service quality, customer satisfaction survey, follow-up, LPPOM MUI, re-evaluatio