bluuebunny/crossref_metadata_2025_split huggingface dataset:
PENUMBUHAN BUDI PEKERTI DI SEKOLAH MELALUI IMPLEMENTASI KURIKULUM 2013
Authors: Istianingsih Siti 
Published: November 2017

Tujuan dari penulisan ini adalah untuk mendeskripsikan program penumbuhan budi pekerti siswa sekolah melalui implementasi kurikulum 2013. Latar belakang dari program penumbuhan budi pekerti adalah masih terabaikannya implementasi nilai -nilai dasar kemanusiaan yang berakar dari Pancasila. Serta masih terbatas pemahaman nilai dalam tataran konseptual, belum terwujud menjadi nilai aktual dengan cara yang menyenangkan di lingkungan sekolah, keluarga dan masyarakat. Pada implementasi kurikulum 2013, penumbuhan budi pekerti pada siswa sekolah dapat dilaksanakan melalui kegiatan intrakurikuler, ekstrakulikuler dan nonkurikuler. Peranan guru dalam penumpuhan budi pekerti di sekolah sangat diharapkan sebagai contoh keteladanan siswa untuk membiasakan diri dalam bersikap dan berperilaku yang baik sesuai dengan tatanan dan nilai -nilai luhur budaya dan pancasila.
PENGARUH PENDIDIKAN KARAKTER ANTI KORUPSI DALAM KELUARGA TERHADAP KARAKTER ANTI KORUPSI PADA REMAJA
Authors: Utami Mega Novi , Hasanah Uswatun , Tarma Tarma 
Published: November 2017

Keluarga merupakan lingkungan yang paling utama untuk menentukan masa depan anak, demikian pula karakter anak yang baik dimulai dari keluarga. Keluarga yang bersikap permisif terhadap perilaku koruptif akan membuat anak memandang perilaku koruptif adalah sesuatu yang lumrah. Tujuan penelitian ini adalah untuk mengetahui dan menganalisis pengaruh pendidikan karakter anti korupsi dalam keluarga terhadap karakter anti korupsi pada remaja di SMA Negeri 53 Jakarta. Penelitian ini adalah penelitian kuantitatif dengan metode survey dan pendekatan korelasi bivariat. Populasi penelitian ini adalah seluruh siswa kelas X dan XI SMA Negeri 53 Jakarta dengan jumlah sampel penelitian sebanyak 224 responden. Data pengujian hipotesis menggunakan analisis parametrik yaitu uji Pearson Product Moment. Hasil perhitungan koefisien korelasi Pearson Product Moment menghasilkan rhitung sebesar 0,354 dan uji signifikansi korelasi menghasilkan thitung sebesar 5,642 lebih besar dari ttabel sebesar 1,971 (Î±=0,05; dk=222). Hal ini menjelaskan bahwa terdapat pengaruh yang positif dan signifikan antara pendidikan pendidikan karakter anti korupsi dalam keluarga terhadap karakter anti korupsi pada remaja. Hasil uji koefisien determinasi sebesar 12,5% yang menjelaskan besarnya pendidikan karakter anti korupsi dalam keluarga mempengaruhi karakter anti korupsi pada remaja dan sisanya 87,5% dipengaruhi oleh faktor lain yang tidak diteliti.
Hubungan Antara Faktor Risiko Eksternal Dengan Resiliensi Pada Siswa Smk Negeri 1 Jakarta
Authors: Aliefa Nugrahaeni , Hasanah Uswatun , Kenty Kenty 
Published: November 2017

Resiliensi dianggap sebagai kekuatan dasar yang menjadi fondasi dari semua karakter positif dalam membangun kekuatan emosional dan psikologis seseorang. Seberapa tinggi atau rendahnya tingkat resiliensi yang dimiliki seseorang akan mempengaruhi bagaimana individu tersebut bisa dengan baik menghadapi kesulitaan hidupnya. Sedangkan dalam penelitian ini data yang peneliti peroleh dari siswa kelas XI di SMK Negeri 1 Jakarta sebanyak 142 mahasiswa yang tercatat sebagai siswa di SMK Negeri 1 Jakarta pada periode tahun pengajaran 2015 - 2016. Dari jumlah tersebut banyak siswa yang memiliki faktor risiko yang sangat tinggi. Penelitian ini bertujuan untuk mengetahui Hubungan antara faktor risiko eksternal dengan resiliensi. Penelitian ini menggunakan metode survey dengan pendekatan korelasi yang dilakukan pada seluruh siswa kelas XI SMK Negeri 1 Jakarta. Penelitian ini menggunakan Metode Penelitian Kuantitatif. Populasi pada penelitian ini adalah seluruh siswa kelas XI Sampel yang digunakan dalam penelitian ini sebanyak 200 orang. Teknik sampling yang digunakan adalah Teknik Porposional cluster sampling. Hasil dari penelitian ini menunjukan bahwa adanya hubungan yang rendah antara Faktor Risiko Eksternal dengan Resiliensi pada siswa SMK Negeri 1 Jakarta. Kesimpulan dari penelitian ini adalah Ho diterima, yaitu adanya hubungan yang rendah antara faktor risiko ekternal dengan resiliensi pada siswa SMK Negeri 1 Jakarta. Dari hasil penelitian yang memiliki hubungan tersebut, Faktor Risiko di lingkungan teman sebaya memiliki presentasi yang tinggi dan menjadi salah satu penyebab tingginya faktor risiko dari pada resiliensi.
PENGARUH PERAN TEMAN SEBAYA TERHADAP TINGKAT KENAKALAN REMAJA DI LAPAS ANAK WANITA KELAS II B TANGERANG
Authors: Ummah Zuvin Natul , Nursetiawati Sitti , Gede Putri Vera Utami 
Published: November 2017

Masa remaja merupakan masa yang sangat rentan terhadap perilaku yang salah karena pengaruh negatif lingkungan sosial dan kurang pengawasan dari orang tua. Pada masa remaja komunikasi dan kepercayaan terhadap orang tua berkurang, dan beralih kepada teman sebaya untuk memenuhi kebutuhan akan kelekatan (attachment). Lingkungan teman sebaya yang negatif dapat mendorong terlibat dalam kenakalan remaja. Penelitian ini bertujuan untuk mengetahui pengaruh teman sebaya terhadap tingkat kenakalan remaja di Lapas Anak Wanita kelas IIB Tangerang. Populasi penelitian ini adalah warga binaan di Lapas Anak Wanita Tangerang yang berusia 17 hingga 21 tahun yang berjumlah 75 remaja. Teknik yang digunakan adalah teknik sampling jenuh. Berdasarkan penelitian yang telah dilakukan, diketahui nilai koefisien korelasi rxy= 0.235 dan thitung (2.00) > ttabel (1,99). Sehingga dapat disimpulkan bahwa terdapat pengaruh positif yang signifikan antara pergaulan teman sebaya terhadap tingkat kenakalan remaja. Pergaulan teman sebaya memiliki sumbangan sebesar 5,52% terhadap tingkat kenakalan remaja, sehingga semakin tinggi pergaulan teman sebaya maka semakin tinggi pula tingkat kenakalan remaja.
ANALISIS PENGELOLAAN KARTU JAKARTA PINTAR DALAM RANGKA MENINGKATKAN HASIL BELAJAR
Authors: Siringoringo Haryanto Pardamean , Hamiyati Hamiyati , Doriza Shinta 
Published: November 2017

Kartu Jakarta Pintar merupakan program sosial untuk masyarakat DKI Jakarta yang bertujuan untuk membantu masyarakat miskin khusus nya membantu biaya personal pendidikan siswa. Penelitian ini bertujuan untuk mengetahui bagaimana pengelolaan KJP oleh ibu untuk meningkatkan hasil belajar anak nya. Penelitian ini menggunakan pendekatan kualitatif deskriptif dan informan secara purposive sampling yang berarti secara disengaja dan ditentukan oleh penelitian. Informan yang menjadi sumber data adalah 4 orang. Penelitian ini dilakukan di SDN 09 Malaka Jaya. Teknik pengumpulan data dengan wawancara, observasi dan dokumentasi. Analisis data yang digunakan adalah analisis Miles & Huberman. Hasil penelitian menunjukan bahwa ibu hanya tahu secara umum KJP dan pengetahuan manajemen keuangan serta pengelolaan KJP yang dilakukan hanya sekadar memenuhi kebutuhan namun tidak berpengaruh banyak terhadap hasil belajar anak.
Perancangan Program Day Care Berbasis Experiential Learning di Prodi Pendidikan Kesejahteraan Keluarga
Authors: Muâ€™jizatin Nur , Jubaedah Yoyoh , Widiaty Isma 
Published: November 2017

Penelitian ini dilatarbelakangi belum adanya program day care berbasis experiential learning di laboratoruim Prodi PKK. Penelitian ini bertujuan untuk menganalisis kebutuhan perancangan program di day care, merancang program day care berbasis experiential learning, melaksanakan expert judgmant, dan menghasilkan program day care berbasis experiential learning. Penelitian ini menggunakan pendekatan ADDIE yang telah dimodifikasi oleh peneliti sesuai dengan kebutuhan, sehingga peneliti hanya melakukan empat tahapan yaitu meliputi Analysis, Design, Development, dan Evaluation. Sampel penelitian ini terdiri dari penggelola day care dan Ibu bekerja yang memiliki anak usia balita. Program day care yang dirancang terdiri dari profil lembaga,tujuan, komponen penyelenggaraan day care, interaksi dan komunikasi, proses pelaporan, dan pembelajaran berbasis experiential learning. Hasil expert judgmant mengenai program day care berbasis experiential learning berada pada kategori sangat layak. Ketercapaian kriteria tersebut tervalidasi oleh para ahli dan praktisi yang terdiri dari aspek profil lembaga,tujuan, komponen penyelenggaraan day care, interaksi dan komunikasi, proses pelaporan, dan pembelajaran berbasis experiential learning. Rekomendasi untuk pengelola day care agar dapat memfailitasi sarana dan prasarana untuk keberlangsungan program day care. Saran bagi orangtua untuk lebih selektif dalam memilih tempat day care. Bagi peneliti selanjutnya program day care dapat diuji coba dan diimplementasikan, dengan menyesuaikan karakteristik anak usia dini, sarana dan prasarana yang ada di day care. Program pembelajaran berbasis experiential learning dapat diterapkan di lembaga PAUD seperti Taman Kanak-Kanak, Kelompok Bermain, Tempat Penitipan Anak dan Sekolah PAUD Sejenis sebagai program pembelajaran untuk anak usia dini.
Research and Application of Electric Power Curve Inversing Dynamometer Diagram Technology Using Big Data Approach
Authors: Zhang Xishun , Shi Junfeng , Zhao Ruidong , Sun Dakui , Zhang Xin , Deng Feng , Peng Yi , Chen Shiwen , Chu Haoyuan , Dong Qing 
Published: November 2017

AbstractThe surface dynamometer diagram of a rod-pumped well is obtained by load sensor, from which oil well working conditions can be analyzed, oil well failures can be diagnosed, and oil production can be calculated. However, such problems as high cost, low popularity and susceptibility to drift and distortion existing with the way to obtain a dynamometer diagram have restricted the development of oil well digital management. Electric parameters are the most basic ones for oil well operation, which are characterized by high popularity, low acquisition cost and stable data. Electric parameters are applied to the dynamometer diagram conversion, analysis and metering, which can take place of the load sensor and realize low-cost and high-efficiency digital management of oil wells. In most cases, the application of electric parameters inversing dynamometer diagram is based on the torque factor method. The torque factor is zero when the polished rod is at the top and bottom dead centers. When this factor is used as a divisor, the calculated load will have no convergence. In this paper, an electric power curve inversion dynamometer diagram approach using big data technologies is proposed: Hadoop technology and Spark technology are utilized to establish a big data platform for electric power curve conversion dynamometer diagram, which collects more than 60,000 site power curve-dynamometer diagram sample data to set up an deep learning sample database. 144 points are selected from the power curve as eigenvalues. After filling the dynamometer diagram, 256 pixels are selected as eigenvalues. So, the eigenvalues are sufficient enough. Deep learning technologies such as Restricted Boltzmann Machine, Sparse AutoEncoder and Softmax Mapping are applied to training sample database, finding out the inter-relation between power curve and dynamometer diagram and obtaining the "power curve-dynamometer diagram conversion model" to realize power curve inversing dynamometer diagram. This technology has been applied in Jilin Oilfield for 350 wells. According to the comparison of a dynamometer diagram converted from power curve with one actually measured, the diagnosis accuracy of working conditions can reach 95.4%, the conformance rate of maximum load is 95%, and the conformance rate of minimum load is 93%. It is shown by field application that using big data technologies the deep learning model is accurate, the algorithm is highly stable, the inversion result is highly precise and the conformance rate is high, which is of great significance to the improvement of digital management level as well as the reduction of production cost. This technology has a promising prospect for popularization.
Increasing Production via Foam Assisted Gas Lift in a Mature Oil Well
Authors: Ahmad Siti Azlynda , McGregor Stuart , Ekol Dymphna@DJ , Sen Yong Min , Davoren Steven 
Published: November 2017

Abstract
Continuous Foam Injection is a proven deliquification technique in gas wells, but the technology typically struggles to perform in wells with high fractions of liquid hydrocarbons. For gas-lifted oil wells operating at high water cut, continuous downhole foam injection via the gas-lift system may prove feasible and open-up a whole new area of production enhancement.
To establish if this technique could deliver sustainable and cost effective production enhancement in the field, Shell Malaysia Exploration & Production (SMEP) successfully conducted a trial in October 2016 in a mature oil field where a liquid foamer was injected into the gas lift system of an oil well.
The project team took 10 months to conduct candidate well screening, comprehensive lab testing for chemical selection, well performance modelling, procurement, site visit, plant change requirements and finally site execution. Although the candidate well was located in an aging facility with limited production monitoring facilities, the available surface pressure/temperature transmitters and fluid sample points were sufficient to ensure a robust assessment of the trial results was possible. Over the trial period, a 22% increase in the gross production rate was seen in the candidate well, with downhole foamer and surface defoamer being applied on a continuous basis. Throughout the trial, the fluid properties were closely monitored to ensure secondary effects such as excessive surface foaming or untreatable emulsification did not occur and this strategy proved successful with the trial being completed without any downstream system upset.
The trial being described in this abstract was the first time a foamer had been applied in this manner in Shell Malaysia.
Decline Curve Analysis for Production Forecasting Based on Machine Learning
Authors: Li Yunan , Han Yifu 
Published: November 2017

Abstract
A new method is developed by using machine learning technique to forecast single well production in both conventional and unconventional reservoirs. Unlike investigating and analyzing existing wells production rate and decline curve, this method predicts new well production rate according to reservoir properties such as matrix permeability, porosity, formation pressure and temperature, as well as hydraulic fracture parameters including fracture half length, fracture width and fracture conductivity.
In this paper, an inversion scheme is coupled with decline curve model, Logistic Growth Model (LGM), to obtain a set of decline curve parameters by fitting with production data. Both the Principal Component Analysis (PCA) and sensitivity study are applied to analyze the variance and identify key factors that influence production rate from reservoir and hydraulic fracture parameters. The sensitivity analysis results and scree plot from PCA serve as references to select key factors. Lastly, Neural Network (NN) technology is applied to investigate the pattern and correlation of selected reservoir and hydraulic fracture parameters and decline curve parameters. Therefore, the NN model can be applied to forecast production rate for a new well according to given reservoir and hydraulic information.
There is a good agreement between the available production data and decline curve model predicated production data based on the inverted decline curve model parameters. The scree plot and bi-plot generated by PCA provide the weight percentage of each component and help to identify factors that should be considered. Field production data is used to verify the feasibility of this method. This field case study is conducted by fitting the predicted production data (decline curve) based on NN model with field production data. The Mean Squared Estimation (MSE) of NN model is 0.013 Mscf/D and the overall R value is 0.917. This indicates that NN model is reliable to study the dataset and provide proper production (decline curve) prediction. The results illustrate that the predicted production data (decline curve) has good accuracy.
This paper proposes a statistical way for production forecasting based on machine learning. Instead of forecasting future production of existing wells, it provides meaningful reference for the evaluation of a new well and decision making.
Reservoir Study for Shale Gas Horizontal Casing Completion Multi-Stage Frac Using Gas Tracer Technology
Authors: Miao Yun , Zeng Bo , Zhou Changlin , Wu Yaoguang , Shan Yongbin 
Published: November 2017

Abstract
Shale Gas development demands for reservoir study to horizontal casing completion wells. Stages production are crucial to understand reservoir characteristics related with stimulation design and production.
The objective of the research is to propose a new method to understand the reservoir characteristic relationship with stages production after multi-stage plug-n-perf and stage stimulation.
Chemical gas tracers were added to each stage during stimulation[1]. Tracers are unique, independent, non-reaction with each other. Samples of the produced gas are collected from the wellhead and analyzed for the presence and concentration of each tracer. A comparative analysis of the amount of tracer from each stage in the samples can then be related to the amount of gas produced from that stage. The more gas produced from that stage results in more tracer produced from the stage.
A new methodology is used in this paper to describe relationship between reservoir characteristics and production and stimulation. Analyzed data will be input into a CTTRIP interpretation system for in-depth interpretation. An IRA interrelation analysis based on CTTRIP data will reveal how reservoir characteristics corresponds to the production under in-situ stimulation.
Further analysis under big data will precisely evaluate the relationship between formation petro data and stages production under in-situ stimulation for certain tectonic structure and reservoir feature, which also helps to determine compartmentalization in a specific reservoir.
Effects of Selected Process Variables on the Stability of Petroleum Emulsions Co-Stabilized by Carbon Black and Surfactant
Authors: Umar Abubakar A. , Negash Berihun M. , Saaid Ismail M. , Sulaimon Aliyu A. , pilus Rashidah M. , Shahpin Hazri B. , Mohamed Anwarudin Saidu 
Published: November 2017

AbstractPetroleum emulsions formed in the oil industry are pricy problems both in terms of chemicals used and the production lost. These emulsions form when oil and brine come into contact with each other, with the influence of sufficient mixing, and in the presence of surface-active-agents (surfactants) or emulsifiers. Although, these emulsions might not form except in the presence of emulsifiers, the amount of agitation, residence time (ageing), among other variables are very critical to its formation and subsequent stabilization. The emulsions are treated to remove the dispersed water and associated inorganic salts to meet market specifications, transportation requirement and to reduce corrosion and catalyst poisoning in downstream processing. This study aims at investigating the effects of selected process variables; viz-aviz: Residence time, mixing rate, surfactant concentration (span 80)(v/v%), and carbon black concentrations (wt%) on the stability of petroleum emulsions. Crude oil from an offshore Malaysian oilfield was used as the oleic phase, and distilled water as the dispersed aqueous phase. Sequences of laboratory experiments as designed by the Response Surface Methodology (RSM) were conducted. The RSM helps to optimize the process, influenced by number of operating parameters with a minimum number of experiments as well as to evaluate the interaction between the parameters. Results showed that a Carbon Black (CB) and surfactants provide better and longer stability than either CB particles or Span80 alone. Also, mixing rate (agitation) and aging show direct proportion to stability of the studied emulsions.
Production and Cost Optimization in a Complex Onshore Operation Using Integrated Production Model
Authors: Hidayat Azis , Prakoso Noke Fajar , Sujai Ahmad , Medco PT 
Published: November 2017

Abstract
During this low oil price era, E&P operators are challenged to reduce operating costs by evaluating their production system. Integrated production model (IPM), which combined subsurface model and surface production system, is a tool that can be utilized to evaluate the existing production system and to arrange the upcoming production strategy. This paper focuses on Kaji-Semoga oil field which consists of three field processing stations, three compressor stations, 130 ESP and 63 gas lift (GL) wells.
The system evaluation started with evaluating the total GL injection required for all GL wells to observe the opportunity to increase the oil production or reduce the active compressor. This required gas lift performance curve for each wells with sensitivity to the various well head pressure. The ESP, as equipped with variable speed drive, can be optimized in accordance to the pump capacity and facility constraints. The artificial lift reliability was also evaluated to reduce the oil deferment and to foresee the next production strategy. The IPM for Kaji-Semoga was built to integrate those issues.
Based on the IPM, the total GL injection rate can be reduced by up to 17% while maintaining the total oil production. With the aim of cost optimization by saving the gas fuel and reducing compressor cost, then the gas lift compressors had been shut down and relocated to another asset. As the result, 24% of total annual compressors cost was saved. From the artificial lift reliability evaluation shows that GL system reliability was reduced along with the gas shortage, whereby contributed 71% of total oil deferment. The artificial lift conversion from GL to ESP then selected as a solution. The strategy for shutdown the next gas lift compressors was then generated in accordance with the artificial lift conversion schedule and the gas lift network distribution. To overcome the limitation of liquid handling capacity at the field stations due to the conversion project, the IPM could optimize the GL and ESP simultaneously thus total fluid production can be maintained at a minimum level by continuing to retain the oil production.
The paper describes some of lesson learned in constructing and utilizing the IPM as an effective tool, not only to optimize the existing production system, but also to generate the future production strategy, cost reduction opportunity and operation maneuver.
Improving Existing Perforation Efficiency via Thru-Tubing Dynamic Underbalance Application in Offshore Field, Malaysia
Authors: Michael Lester Tugung , Lajim-Sayung Colinus , A Maisarah Bt. , Ghazali Rohaizat , Gilbert Rayner , Sepulveda Willem , Busaidy Adil , Vaca Juan Cortez , Zubbir Ahmad Uzair 
Published: November 2017

Abstract
Perforation is a key component in a reservoir inflow to recover the most oil production from a reservoir. In Field S, perforating is typically conducted using the principle of overbalanced technique, which is commonly used in the oil and gas industry and is known to result in higher total skin. This paper discusses the first application of a thru-tubing stand-alone dynamic underbalance technique to clean up perforation tunnels in Field S, Malaysia. The dynamic underbalance(DUB) concept creates a rapid drawdown in front of existing perforation intervals to effectively clean up plugged perforation tunnels, thereby reducing perforation skin and increasing the productivity of the wellbore.
The plunge in the oil price in 2014 has led to a focus on cost reduction and opex optimizationin production enhancement initiativesin Field S from existing well stock inventory. Through this initiative, two strings (Well XS and XS) have been selectedto increase perforation efficiency via thru-tubing DUB application, as part of the cost optimization in our production enhancement portfolio. The project scope covers a full-cycle production enhancement initiative, starting from candidate selection to job design and preparation, job execution and post-job analysis.