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"A study has been done on the potential integration of Demand Side Management (DSM) to the reduction of electric power peak load forecasting in the Indonesian electric system by using the indonesia Energy Outlook by .System Dynamic (INOSYD) model and Artificial Neural Network (ANN) method, within the study period of 2005-202l. DSM is the process of managing the consumption of energy. generally to optimize availability and development plan of energy resources. DSM application in this research refers to actions taken on the customer 's side of the matter to change the amount or timing of energy consumption, therefore it influences the reduction of the long-range forecasting of electricity peak load In this paper, the lang-term load forecasting is studied by using INOSYD model, JS T method and Model for Analysis of Energy Demand (MAED) as comparison, where the calculation results of average annual load growth rate are around 4.60% (DVOSYD) ; 7.l6% (ISD and 6.87% (MAED) respectively. Afterwards, the influence of DSM by an effort to reduce energy consumption of residential sector by an amount of 5% and l0% respectively, with the respect to the lang-term load forecasting by using INOSYD model and ANN method is performed The study results show that DSM application at residential (household sector at an amount of 5% and l 0% by using lNOS}'D model will reduce the average long-term load forecasting by about 4.95% and 9.90% respectively, meanwhile ANN method will reduce the average long-term load forecasting by about 2.74 and 5.36% respectively."

"Pertumbuhan ekonomi dan populasi menyebabkan peningkatan konsumsi energi listrik. Oleh karena itu, konsumsi energi dan penyediaan daya di masa mendatang perlu diprakirakan sejak dini. Terdapat beberapa metode yang telah diterapkan, namun dalam hal ini penulis melakukan peramalan kebutuhan energi menggunakan metode Neural Network (NN) berdasarkan data-data meliputi rasio elektrifikasi, energi terjual pelanggan, PDRB (Produk Domestik Regional Bruto) serta jumlah penduduk pada wilayah Jamali (Jawa Madura Bali). Adapun simulasi NN dilakukan pada software Matlab. Walaupun demikian, peramalan kebutuhan energi kali ini hanya dapat dilakukan pada waktu yang terbatas, karena tingkat kepercayaan ramalan menurun mengikuti kenaikan tahun dimana tingkat kepercayaan maksimum R2 = 0,9852 diperoleh pada peramalan kebutuhan energi selama 6 tahun ke depan.

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Economic and population growth led to increased consumption of electrical energy. Therefore, energy consumption and power supply in the future need to be predicted early on. There are several methods that can be applied, but this study will use artificial Neural Network (ANN) for demand forecasting based on data that consist of electrification ratio, energy-sold customers, GDP (Gross Domestic Product) and the number of residents in the area of Jamali. The simulation is done by using Matlab. However, the peak demand forecasting can only be done in a limited time, because the confidence level forecast to decline following the year in which the increase in the maximum confidence level R2 = 0.9852 is obtained on demand forecasting for the next 6 years."

"In this study, based on the typical binary mixtures (ammonia/water) low temperature thermal power generation cycle, a new method for the potential analysis of hot spring additional power generation is proposed. The calculation model is built with Kalina cycle technology for the power generation potential analysis. According to the characteristics of the cycle, the verification items are given to verify the correctness of the calculation model. It is proved that the model is correct by sampling check a set of calculation data. And then, a case study is carried out in Hokkaido since it has the largest number of hot spring resorts in Japan. Results show that the hot spring additional power generation capability in Hokkaido is about 9828.0 kilowatts. And it can bring additional earnings about 2.781 billion Yen for Hokkaido every year."

"Permasalahan yang banyak dihadapi oleh perusahaaan Iistrik di dunia saat ini (tak teikecuali juga oleh PT PLN) di dalam upaya untuk memenuhi permintaan tenaga listrik adalah : 1) terbatasnya dana untuk membangun sarana penyediaan tenaga Iistrik, mengingat usaha kelistrikan merupakan usaha yang sifatnya padat modal; 2) semakin menipisnya sumber daya alam sebagai sumber energi primer untuk membangkitkan tenaga listrik; dan 3) munculnya kesadaran masyarakat akan pembangunan yang berwawasan lingkungan. Salah satu alternatif untuk mengatasi kendala-kendala tersebut adalah dengan cara memasukkan atau mempertimbangkan potensi penghematan (MW maupun MWh) yang ada pada sisi pemakai melalui aktifitas Manajemen Sisi Kebutuhan (Demand Side Management-DSM) ke dalam Perencanaan. Pengembangan Sistem Kelistrikan. Pola ini merupakan pola panyediaan tenaga Iistrik yang baru yang dikenal sebagai Perencanaan Sumber Daya Terpadu (integrated Resources Planning-|F~lP), yang tetap didasarkan pada biaya termurah. DSM yang dirancang untuk mempengaruhi pola konsumsi (waktu dan intensitas) penggunaan tenaga iistrik oleh pelanggan, akan berdampak terhadap berubahnya bentuk kurva beban sistem, dan dengan berubahnya bentuk kurva beban sistem ini maka akan berakibat terhadap perubah an lingkat keandalan sistem (1). Adanya perubahan terhadap tingkat keanclalan sistem ini yang diiadikan sebagai dasar untuk menentukan besarnya Capacity Benefit (MW) untuk membedakannya dengan pengertian ?Peak Reduction" yang biasa digunakan untuk menyatakan potensi penurunan beban puncak sistem sebagai dampak dari aktifitas program DSM. Perhitungan Capacity Benefit ini dimungkinkan setelah ditemukannya suatu model kurva beban yang dikenal sebagai "VPI Load Model""2' yang merupakan fungsi dari beban puncak, beban dasar dan total konsumsi energi, sehingga ia dapat menam pung setiap perubahan bentuk kurva beban sistem yang sering terjadi karena adanya aktilitas DSM. Dalam thesis ini, penulis akan melakukan analisa Capacity Benefit terhadap sasaran program DSM di dalam Sistem Keiistrikan .Jawa-Bali, yang dikaitkan dengan Perencanaan pengembangan Sistem Kelistrikan Secara Terpadu. Selain itu, akan dihitung pula besarnya Avoided Cost berkaitan dengan adanya penurunan beban puncak sistem dan total konsumsi energi Iistrik sebagai dampak dari program DSM tersebut.Most the electric power companies in the world (including PT PLN in Indonesia), are facing many problems in providing to meet the expected demand. Some of them are : 1) the limitation of budget to build infrastructure for providing electric power that needs capital intensive; 2) natural resources as primary energy source to generate electric power gradually reduce; 3) increasing of people awareness concerning their environmental conditions. One of the alternatives to solve those problems is by considering the potency of energy that can be saved by consumers (MW and MWh) through introduction and implementation Demand Side Management (DSM) activities in the Power System Planning. This methode in considered as a new concept for providing electric power and known as integrated Resources Planning (IBP). This concept is still based on lowest system cost. DSM that is designed to influence the consumption pattern (time and intensity) of customers' energy use, will change the shapes of load system curves, and the changes of the shapes of load system curves, will affect the level of generation system reliability "". Changing in the level of generation system reliability will be used as a basic calculation for the Capacity Benefit (MW). The term of Capacity Benefit isused to differentiate with the the term of 'Peak Reduction" which is often used to representate the potency of peak load system reduction as a result of implementing DSM program activities. Calculation of Capacity Benefit is enabled after a model of load curves known as ?VPI Load Model"?2' is found. This model is a function of peak load, base load and total energy consumption. This model can also accomodate every changing in the shapes of system load curves that often happens because of DSM activities. In this thesis, it will be conducted an analysis concerning a Capacity Benefit toward (objectives of the) DSM Program in The Java-Bali Power System, that will be related to (the integrated Power System Planning). Besides that, it will also be calculated Avoided Cost as due to of peak load system reduction and the total of electric energy consumption as impacts of implementing the DSM program."

"This book makes use of existing scenarios to sketch a new structure for Germany's and Europe's electricity system that will be able to cope simultaneously with the fundamental demands for economic efficiency, environmental sustainability and supply security. "

"Skripsi ini membahas tentang permintaan produk Packed Red Cell (PRC) di Unit Transfusi Darah Palang Merah Indonesia di DKI Jakarta yang diperkirakan akan membuat rencana produksi guna menurunkan tingkat keluarnya darah yang terjadi akibat jumlahnya. produksi yang melebihi jumlah penggunaan. Penelitian ini berbentuk studi kasus dengan tipe kuantitatif. Dalam peramalan, data time-series penggunaan PRC bulanan digunakan selama lima tahun terakhir yaitu 2014 hingga 2018 yang dihitung dengan menggunakan metode Autoregressive Integrated Moving Average (ARIMA) dan Holt-Winter Exponential Smoothing. Hasil perhitungan dengan menggunakan metode ARIMA memberikan hasil peramalan yang lebih baik sehingga dapat digunakan sebagai acuan dalam membuat perencanaan produksi produk RRT. Dari hasil perencanaan produksi tersebut disarankan agar PMI DKI Jakarta mengalihkan sebagian dari rencana kunjungannya dalam rangka pengambilan darah ke PMI lain di sekitar Jakarta dan juga dapat menyalurkan jumlah produksi darah berlebih ke Bank Darah Rumah Sakit ( BDRS) atau PMI lain yang masih kekurangan suplai darah.

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This thesis discusses the demand for Packed Red Cell (PRC) products at the Indonesian Red Cross Blood Transfusion Unit in DKI Jakarta, which is expected to make a production plan to reduce the rate of blood loss that occurs due to the amount. production that exceeds the amount of use. This research is in the form of a case study with a quantitative type. In forecasting, time-series data on the use of monthly PRC are used for the last five years, namely 2014 to 2018, which is calculated using the Autoregressive Integrated Moving Average (ARIMA) and Holt-Winter Exponential Smoothing methods. The results of calculations using the ARIMA method provide better forecasting results so that they can be used as a reference in planning the production of Chinese products. From the results of the production planning, it is suggested that PMI DKI Jakarta divert part of its planned visit in the context of taking blood to other PMIs around Jakarta and also be able to distribute the amount of excess blood production to Hospital Blood Banks (BDRS) or other PMIs that still lack blood supply."

"ABSTRAK

Persediaan merepresentasikan 20%-60% dari aset perusahaan, oleh karena itu pengelolaan persediaan menjadi aktivitas penting yang harus dilakukan setiap perusahaan. Penelitian ini bertujuan untuk mendapatkan tingkat persediaan optimum di pusat distribusi barang perusahaan furnitur lokal dengan menggunakan analisis ABC, peramalan permintaan untuk periode 2019 dan metode persediaan fixed-order quantity dengan model probabilistik agar dapat menggambarkan kondisi aktual di lapangan. Desain penelitian ini adalah kuantitatif deskriptif dan dilakukan dengan pendekatan studi kasus. Hasil penelitian menunjukkan bahwa terdapat 113 produk yang termasuk kedalam kategori A, dimana 29 produk diantaranya memiliki kontribusi gross margin sebesar 55%. Proyeksi tingkat permintaan untuk 29 produk tersebut secara keseluruhan pada bulan Januari sebesar 927 unit, bulan Februari sebesar 930 unit, bulan Maret sebesar 1149 unit, bulan April sebesar 1415 unit, bulan Mei sebesar 2203 unit, bulan Juni sebesar 1267 unit, bulan Juli sebesar 1215 unit, bulan Agustus sebesar 1357 unit, bulan September sebesar 1505 unit, bulan Oktober sebesar 2649 unit, bulan November sebesar 4034 unit dan bulan Desember sebesar 3857 unit. Tingkat persediaan optimum untuk 29 produk kategori A yang berkisar dari 40 sampai 100 unit terdiri dari 4 produk. Tingkat persediaan optimum yang berkisar dari 101 sampai 200 unit terdiri dari 11 produk, lalu tingkat persediaan optimum yang berkisar dari 201 sampai 400 unit terdiri dari 8 produk, dan tingkat persediaan optimum yang berkisar dari 401 sampai 600 unit terdiri dari 6 produk. Potensi penghematan biaya berdasarkan tingkat persediaan optimum sebesar 8,60% atau Rp845,921,774 dari total biaya persediaan.

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ABSTRACT

 

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Inventories represent 20%-60% of the company's assets, therefore inventory management is an important activity that must be done by every company. This study aims to obtain optimum inventory levels in the distribution center of local furniture companies using ABC analysis, demand forecasting for the 2019 period and fixed-order quantity inventory methods with probabilistic models in order to describe the actual conditions. The design of this study is quantitative descriptive and is carried out with a case study approach. The results showed that there are 113 products included in category A, which 29 of them had gross margin contribution of 55%. The overall demand level projection for 29 products in January is 927 units, February is 930 units, March is 1149 units, April is 1415 units, May is 2203 units, June is 1267 units, July is 1215 units. In August amounted to 1357 units, September is 1505 units, October is 2649 units, November is 4034 units and December is 3857 units. The optimum inventory level for 29 category A products ranging from 40 to 100 units consists of 4 products. Optimum inventory levels ranging from 101 to 200 units consist of 11 products, then optimum inventory levels ranging from 201 to 400 units consisting of 8 products, and optimum inventory levels ranging from 401 to 600 units consist of 6 products. The potential cost savings is 8.60% or Rp. 845,921,774 of total inventory costs.

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