Kehadiran seorang anak di tengah keluarga merupakan impian bagi setiap orangtua, namun rasa bahagia itu berubah menjadi kekecewaan ketika orangtua mengetahui bahwa anak mereka memiliki suatu hambatan tertentu. Berdasarkan hasil wawancara wawancara dengan beberapa orangtua dengan anak berkebutuhan khusus ditemukan bahwa mereka kurang mendapatkan informasi bagaimana mengasuh anak-anak mereka. Ketidaktahuan penanganan anak berkebutuhan khusus membuat beberapa orangtua mengalami stres dan frustasi ketika sedang berinteraksi dan mengasuh dengan anak-anak mereka. Tujuan dari pelatihan ini adalah untuk meningkatkan pengetahuan dan keterampilan orangtua dalam menemukenali kebutuhan anak dan menerapkan pengasuhan positif dalam keluarga. Metode pelatihan yang digunakan meliputi uji pre dan post tes pelatihan, sharing pengasuhan Anak Berkebutuhan Khusus (ABK), ceramah dan praktik cara mengenali kebutuhan dan pengasuhan positif, serta follow up penerapan metode pengasuhan positif di rumah selama satu minggu. Hasil pengabdian ada kenaikan pada tingkat pengetahuan orangtua tentang mengenali ciri-ciri ABK, mengenali perilaku dan kebutuhan ABK, serta pengasuhan positif pada ABK dibuktikan dengan kenaikan skor nilai pre-post tes sebanyak 5-30 poin. Peserta pelatihan sejumlah 15 orangtua yang memiliki anak ABK telah mampu mempraktikkan pengasuhan positif di rumah dengan benar selama satu minggu dan mencatatnya di jurnal harian agar dapat dievaluasi bersama dengan anggota keluarga lainnya.

PDAM Loa Kulu Branch still uses sticks or poles as an indicator of the water level in the reservoir. Reservoir is a place to store clean water production from PDAM, the weakness of using sticks or poles is when the operator does not monitor continuously causing air loss when production becomes large. The goal of the study was to design a water-level prototype to control excess water in the reservoir. The method used is a prototype with the stage of gathering information through interviewing PDAM staff, creating and repairing prototypes and testing prototypes. The test used hardware consisting of Arduino uno r3, ultrasonic sensor hc-sr04, flowmeter sensor yf-s201, 16 x 2 lcd, relay module, buzzer, solenoid valve 12 V_dc, pump 12 V_dc and display measurement results in the visual studio application 2019. Our findings are that the length of reservoir charging with an average input discharge of 3.6 liters / minute is 2.93 minutes. As for the length of emptying the reservoir with an average output discharge of 1.06 liters / minute is 12.10 minutes. The conclusion of this study is that the system can monitor the water level inside the reservoir automatically and know the time needed for the feeling and emptying process of the reservoir.

Gas classification techniques are often found in several applied fields such as, detection of leak gas in gas cylinders, monitoring the threshold of harmful pollutant gases in the air, health diagnostics, early detection of fire hazards, and others. This requires measurement techniques that are adaptive and robust that can dynamically capture information on changes in vapor or gas compounds contained in free air. This research has been conducted to analyze and identify the types of gas compounds, namely CO and petrodiesel fuel vapor (C14H30). The design of this tool uses the principle of spectrophotometry and the calculation of Backprogation Neural Networks. The working principle is that light radiation in the Light Emitting Diode (LED) series, which has a wavelength range of 385nm to 1720nm, is absorbed to penetrate CO gas or petrodiesel fuel vapor (C14H30) that you want to identify. Light radiation that has passed through the gas / vapor compound was captured by the photodiode sensor. The emission of LED series light radiation produces different wavelength absorption patterns that will be processed by the Backprogation Neural network as an input signal in the identification and learning process. The results of this experiment show the success rate of the Backpropagation neural network in identifying the type of CO gas and petrodiesel fuel vapor (C14H30) is 80%.

This paper presents analysis of Multi Zone Single Trip Gravel Pack (MZ-STGP) experience and performance in Total E&P Indonesie for more than decade in challenging field environment and global market condition. MZ-STGP has been utilized as a robust sand control completion methodology for sand prone reservoirs in Mahakam Delta since 2006. It enables saving of 3-6 days of rig time depending of well configuration compared to classic stack Gravel Pack (GP). More than 250 wells have been completed with satisfactory result and later drive the company business strategy. Since the downturn of oil and gas industry in year 2014, a "cost efficiency project" called 4C&D (Change Culture, Compete on Costs & Deliver) was launched by Total to targets sustainable culture change and reduction in cost. It involves all aspect in company activities included in scope all operating, whether Total operated or operated by others. This project comprises a number of action plans – "roadmaps", where MZ-STGP became part of it. The target was to have an approach to identify current MZ-STGP performance and understand how to improve it by utilizing certain methodologies and tools. The purpose of this paper is to provide the MZ-STGP practical steps implemented over the past few years using Technical Limit (TL) methodology. This methodology is expected to improve the efficiencies in whole aspects mainly related to performance monitoring as well as maintain low cost in order to have synergy with 4C&D spirit. The approach was influenced by comprehensive statistical data and ideas which resulting changes in the procedures as well as development in technology and equipment. As a result, a step change improvement in MZ-STGP completion performance was successfully achieved.

PDAM Loa Kulu Branch still uses sticks or poles as an indicator of the water level in the reservoir. Reservoir is a place to store clean water production from PDAM, the weakness of using sticks or poles is when the operator does not monitor continuously causing air loss when production becomes large. The goal of the study was to design a water-level prototype to control excess water in the reservoir. The method used is a prototype with the stage of gathering information through interviewing PDAM staff, creating and repairing prototypes and testing prototypes. The test used hardware consisting of Arduino uno r3, ultrasonic sensor hc-sr04, flowmeter sensor yf-s201, 16 x 2 lcd, relay module, buzzer, solenoid valve 12 V_dc, pump 12 V_dc and display measurement results in the visual studio application 2019. Our findings are that the length of reservoir charging with an average input discharge of 3.6 liters / minute is 2.93 minutes. As for the length of emptying the reservoir with an average output discharge of 1.06 liters / minute is 12.10 minutes. The conclusion of this study is that the system can monitor the water level inside the reservoir automatically and know the time needed for the feeling and emptying process of the reservoir.