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ANALISIS BI AYA DAN WAKTU DENGAN METODE EARNED VALUE CONCEPT PADA PROYEK BJDM AREA RL CONSTRUCTION AT WELL 3S-21B AREA 9 PT. ADHI KARYA CS WORK UNIT RATE PACKAGEA – DURI Fitra Ramdhani
Racic : Rab Construction Research Vol 1 No 01 (2016): Terbitan pertama Bulan Juni 2016
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1153.091 KB)

Abstract

Seiring dengan perkembangan sektor migas di Indonesia yang terus berkembang dan dituntut produksi yang tinggi tiap tahunnya, dibutuhkan perencanaan, pelaksanaan serta pengendalian proyek yang serius sehingga mendapatkan hasil yang diinginkan. Dalam pelaksanaan suatu proyek bisa mengalami keterlambatan, percepatan, ataupun tepat waktu sesuai jadwal rencana proyek. Dari segi biaya pelaksanaan suatu proyek bisa mengalami kerugian ataupun keuntungan. Di dalam Konsep Nilai Hasil (Earned Value Concept) akan dikaji untuk meramalkan apakah waktu penyelesaian proyek sesuai dengan rencana awal jadwal proyek dalam setiap periode pelaporan dan seberapa besar keuntungan ataupun kerugian di akhir proyek. Metode Konsep Nilai Hasil (Earned Value Concept) adalah suatu metode pengendalian yang digunakan untuk mengendalikan biaya dan jadwal proyek. Metode ini memberikan informasi Varian Biaya (Cost Varians), Varian Jadwal (Schedule Varians), Indeks Kinerja Biaya (Cost Performance Index), Indek Kinerja Jadwal (Schedule Performance Index) proyek pada suatu periode pelaporan. Dari metode ini didapatkan juga informasi prediksi besaran biaya dan lamanya waktu untuk penyelesaian seluruh pekerjaan berdasarkan indikator kinerja saat pelaporan. EVC (Earned Value Concept) dapat meramalkan biaya akhir dan waktu penyelesaian proyek lebih dini pada setiap periode waktu pelaporan. Pada Proyek Pembangunan Well Program ini, Selama pelaksanaan proyek dari minggu ke-1 sampai dengan minggu ke-16 tidak terjadi deviasi progress antara rencana jadwal proyek dengan pelaksanaan proyek (tepat waktu) Proyeksi akhir biaya mengalami keuntungan sebesar Rp. 134.724.718,.77 dan proyek akan selesai dalam 155 hari kalender, sehingga pelaksanaan pekerjaan ini sesuai jadwal yang telah ditentukan.
PENGELOMPOKAN PROVINSI DI INDONESIA BERDASARKAN KARAKTERISTIK KESEJAHTERAAN RAKYAT MENGGUNAKAN METODE K-MEANS CLUSTER Fitra Ramdhani; Abdul Hoyyi; Moch. Abdul Mukid
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (409.125 KB) | DOI: 10.14710/j.gauss.v4i4.10222

Abstract

Welfare have a relative explanation, dynamic, and quantitative. Quantitative formulation of welfare is never final because it will continue to evolve along with the development needs of human life. In 2011, the National Team for the Acceleration of Poverty Reduction (NTAPR) made priority sector that can serve as a benchmark the welfare in a region. From the priority sector will be made cluster or group which contains all 33 provinces based on the level of public welfare in the region uses data in 2012 were sourced from the Central Statistics Agency (CSA). The method that can be used to group the 33 provinces is K-Means Cluster method with number cluster as many as two, three, four, and five clusters. K-Means Cluster method is one of cluster analysis method who can partition the data into one or more clusters, so that the data with the same characteristics are grouped into the same cluster and data with different characteristics grouped into other clusters. To know the most optimal of the number of clusters we use Davies-Bouldin Index (DBI). We concluded that the optimal number of cluster is three with details the province in the first clusters have superiority in four sectors like net enrollment rate of primary school, net enrollment rate of junior high school, IMR (Infant Mortality Rate), and access to electricity. The province in the second clusters have superiority in one sector, that is open unemployment rate. The province in the third clusters have superiority in all sectors. Keywords: Welfare, NTAPR Priority Sector, K-Means Cluster Method, Davies-.Bouldin Index (DBI)
PENYULINGAN AIR BERSIH UNTUK MENINGKATKAN KUALITAS AIR BERSIH DI MUARA FAJAR BARAT Sukri Sukri; Fitra Ramdhani; Rizki Ramadhan Husaini; Siti Juariah
Jurnal Pengabdian Masyarakat Multidisiplin Vol 3 No 1 (2019): Oktober
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (254.218 KB) | DOI: 10.36341/jpm.v3i1.979

Abstract

Clean water is a need that must be met for everyday, both individual needs and the needs of household groups. The quality of water that is needed everyday is colorless, no smell and dirty, the village of estuary in the middle of the morning is an area close to oil wells and highlands that have very low levels of water cleanliness. Muara Fajar Barat village has high iron content so that it cannot be used for consumption and even for bathing. The West Dawn Estuary community must buy water for daily needs with costs incurred every 3 days reaching 50000 rupiah or an average of 13,000 every day. The economic conditions of the underprivileged people are added to the economic burden with daily expenses by issuing the clean water financing. With this condition there needs to be a solution offered in order to reduce economic burdens and environmental friendliness, for that we need an innovative water purifier tool with a distillation method using natural ingredients and a paralon pipe as a wrapper. The water filter that is made can meet the needs of every daily household by spending only 100,000 euros every 2 months. The decline in the burden of the eastern dawn estuary community could reach 140000 rupiahs every 2 months or 70000 rupiahs