Browsing by Author "Laksana, Eka Angga"

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    HEALTH SERVICE PROCESS : LEAN SIX SIGMA CONCEPT FOR HOSPITALS (CASEMIX HOSPITALS)
    (International Journal of Psychosocial Rehabilitation, Vol.24, Issue 01, 2020) Sudarwan; Nurohim, Achmad; Hadi, Dominicus Sutrisno; Syah, Tantri Yanuar Rahmat; Laksana, Eka Angga
    Background-National Health Insurance, whose implementation began in January 2014, made a change in the payment system from the Retrospective Payment System to the Prospective Payment System in INA-CBG rates. The difference in INA-CBG rates and hospital rates is a fundamental problem so hospitals must make efforts to achieve quality and cost control. The purpose of this study was to determine the efforts taken by hospitals related to differences in hospital outpatient service fees and inpatient service rates to INA-CBG's rates. Method-The research method was carried out quantitatively. Lean consumption is used to analyze the manufacturing sector, namely lean manufacturing rather than industrial processes. In addition, the development of lean consumption in the hospital sector is the right choice to improve the quality of hospital services. Thus, this aims to test the Lean Hospital algorithm by defining, measuring,analyzing, improving, and controlling DMAIC (Define, Measure, Analyze, Improve, Control) and the LCM (Lean Consumption Map) method through hospital services. By using a comparison of the completion time of outpatient and inpatient operational activities. The results showed that the hospital Lean algorithm successfully assessed the comparison method with the Lean Consumption Map and Value Added Assessment. In this study, we used qualitative research methods and interviews with internal and external correspondence, respectively. Result-We found that the DMAIC application and the Lean Consumption Map in the Lean Hospital algorithm will increase document completion times and service processes at the Hospital.
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    INTEGRATED MODEL DEVELOPMENT OF HORTICULTURE AND FORECAST COMMODITY USING WEB BASED GEOGRAPHIC INFORMATION SYSTEM AND SMS GATEWAY TECHNOLOGY
    (The 4th International Conference on Information Technology for Cyber and IT Service Management (CITSM), Sunan Gunung Djati State Islamic University, 26 - 28 April, 2016) Sulianta, Feri; Rosita, Ai; Laksana, Eka Angga
    Agro industries are the industry's most promising and holds great promise for farmers in Indonesia. However, there is a pile of problems in the agricultural industry in Indonesia, namely fluctuations in prices when the implementation of the harvest. These constraints caused by increased yields while consumer demand has not changed, as a result of certain commodity farmers suffered losses. The major causes of products instability is because lack of information for the amount of the supply needs of the crop for farmers. For this reason, information management of agriculture (E-Agriculture) utilizing simulation production forecasts by combining GIS technology and SMS Gateway will be modeled as a basis to solve the problems of agriculture in province of West Java, especially in the district of Bandung and Garut in regulating the balance of plant production horticulture.Simulation web based Geographic Information System (GIS) is developed by considering simulation components, GIS and SMS Gateway Technology, and Spatial Data Layer.
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    MINING TRANSACTIONAL DATA TO PRODUCE EXTENDED ASSOCIATION RULES USING COLLABORATIVE APRIORI, FSA-RED AND M5P PREDICTIVE ALGORITHM AS A BASIS OF BUSINESS ACTIONS
    (8th Widyatama International Seminar on Sustainability (WISS 2016), Widyatama University, 5 - 8, 2016) Sulianta, Feri; Laksana, Eka Angga; Liong, Thee Houw
    There are large amounts of transactional data which showed consumer shopping cart at a store that sells more than 150 types of products. In this case, the company is utilizing these data in making business action. In previous studies, the data that has a lot of attributes and record data reduction algorithms handled by the FSA Red (Feature Selection for Association Rules) are then mined using Apriori algorithm. The resulting association rules have high levels of accuracy and excellent test results, which rely more than 90%. In this study, the association rules generated in previous research will be updated by using prediction algorithms M5P, so that the reliability of association rules can be updated for the next day forward. Furthermore, some data mining technique such as: clustering and time series pattern will be implemented to examine the truth and to extend the validity of association rules which were built. It can be concluded that the association rules were established after will generate strong association rules with confidence equal or higher than 70% and the truth of the rules can be seen from the time series pattern on each group of goods which are then used as the basis of business actions.
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    PHP CRUD Generator Menggunakan Twig Template Engine dan Framework Codeigniter
    (Konferensi Nasional Informatika (KNIF),Kelompok Keilmuan Informatika Institut Teknologi Bandung, 2015-10-22) Laksana, Eka Angga
    Membuat aplikasi berbasis web dengan menggunakan bahasa pemrograman PHP dan MySQL memakan waktu yang cukup lama. Kondisi ini berdampak buruk pada pengerjaan proyek perangkat lunak di mana ketepatan waktu juga menunjukan kualitas sebuah perangkat lunak. PHP CRUD generator merupakan sebuah perangkat lunak yang berfungsi untuk menghasilkan file php, html dan css. File ini merupakan elemen dasar antar muka aplikasi dimana pengguna dapat melakukan manipulasi terhadap basis data berupa menambah, mengubah dan menghapus data (CRUD). File yang dihasilkan kemudian dapat diubah mengikuti alur bisnis proses. Penelitian ini menghasilkan alat berupa PHP CRUD generator, dengan mengambil konsep bahwa beberapa kode dalam sebuah aplikasi selalu dituliskan secara berulang-ulang. Perulangan ini memungkinkan dibuatnya sebuah template yang di dalamnya code dapat diubah secara dinamis, diatur menggunakan variable nama table basis data dan kolom terkait.
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    TIME SERIES PREDICTION ON MOVIE RATING DATA
    (International Journal of Psychosocial Rehabilitation, Vol.24, Issue 02, 2020) Laksana, Eka Angga; Murnawan
    Time series is known as method to make prediction based on series of data. It has some benefit in a lot of research domain including marketing, sport and education area. Movie is popular entertainment part which has a great number of fans. People choose movie with specific genre and has share some similar interest. This research use Movielens dataset as input for time series processing. This dataset contains historical data about user, ratings and datetime. This research implements timeseries on the Movielens dataset to make prediction on rating value by using fbprophet library. The experiment shows that the algorithm can predict the future rating which approximately will be chosen by users. Then the objective of this research is to create recommendation based on predicted rating for whatever movie on the next choice.