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"ABSTRAK Kategori produk peralatan industri proses (process equipment) memberikankontribusi kerugian terbesar dari total kerugian proyek-proyek yang dijalankandan ditutup secara sistem dari tahun 2011 hingga Maret 2014 pada divisi fabrikasiPT X. Penelitian ini dilakukan untuk mengidentifikasi risiko apa saja yangmungkin timbul pada tahapan pelaksanaan proyek yang berpengaruh terhadapkinerja biaya, yaitu variabel-variabel yang menjadi penyebab terjadinya kerugian(cost overrun) pada tahap eksekusi proyek-proyek divisi fabrikasi PT X kategoriproduk peralatan industri proses (process equipment). Proses identifikasi risikodilakukan berdasarkan referensi tinjauan pustaka yang divalidasi oleh para pakaryang berpengalam dan pihak terkait (stakeholder) yang terlibat dalam pelaksanaanproyek-proyek fabrikasi atau proyek EPC di PT X. Analisis risiko kualitatifdilakukan menggunakan probability and impact matrix, analisis kuantitatifdilakukan menggunakan metode analytical hierarchy process (AHP) untukmendapatkan 10 variabel risiko dominan, dan analisis statistik dengan bantuanprogram SPSS versi 21 dilakukan untuk mendapatkan variabel risiko dominanyang paling berpengaruh terhadap kinerja biaya. Saran pengelolaan risikoterhadap 10 variabel risiko dominan terdiri atas tindakan preventif dan korektifyang terkait dengan aspek finansial, customer, proses internal, maupun sumberdaya manusia.

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ABSTRAK The process equipment product category contributed the biggest loss of totalprojects loss executed and closed by system from 2011 until March 2014 infabrication division of PT X. This study was conducted to identify any risks thatmay arise in project implementation stages that affect cost performance, ievariables that cause loss (overrun cost) in project implementation stages ofprocess equipment products category of PT X fabrication division. Riskidentification process is carried out by literature review and validated by expertsand related parties (stakeholders) who experienced and involved in fabrication orEPC project execution of PT X. Qualitative risk analysis was performed usingprobability and impact matrix, quantitative analysis was performed usinganalytical hierarchy process (AHP) methods to get top 10 dominant risk variables,and statistical analysis using SPSS version 21 is performed to get the mostdominant risk variables that affect to cost performance. Risk of the top 10dominant risk variables consist of preventive and corrective actions related to thefinancial, customer, internal processes, and human resources."

"Summary:Offers an accessible introduction to the topic of impact evaluation and its practice in development. While the book is geared principally towards development practitioners and policymakers designing prospective impact evaluations, it will also be a valuable resource for students and others interested in using impact evaluation"

"The rising food price has been signaling a crisis to food insecurity among the poor since the period of 2007/2008. The poor would be in a difficult situation to allocate the budget to meet the demand for food and nonfood in daily life as the real income changes. Food insecurity measured by Food Insecurity Experience Scale (FIES) is a most recent broadened concept of food insecurity considering the existence of anxiety to food access. This research aims to evaluate the causal inference of food price exposure to the FIES both on simple sum namely raw score and Rasch scale, a corrected measure which assuming the same latent traits among the households. The estimation used is Pooled Ordinary Least Square through the multilevel observations and Panel Regression for regional-level data. The main finding of this research is that the rising food price significantly affected the FIES, consistently on the raw score and Rasch scale, specifically to the vulnerable households defined by the bottom 40 percent in terms of their expenditure. The rising food price also increased the proportion of severely food insecure households at the regional level. As the heterogeneous effect through islands is also evaluated, it's concluded that the highest effect of the rising food price to experiencing the anxiety of food insecurity belongs households located in Bali and the lowest effect belongs to households located in Java Island. Decomposing food price into rice and nonrice is solving the puzzle where and who belongs the worse effect should be. The rising rice price is affecting worse to the households in Sumatera and Papua, but on the contrary, the households in Java, Nusa Tenggara, and Sulawesi were taking benefit amid the rising rice price. The result is also serving as a baseline in evaluating the impact of such an outbreak namely Covid-19 through the channel of compensating variations regarding food insecurity. "