Evaluasi Dampak Pembangunan Sosial, Bagi Kesejahteraan Masyarakat Kabupaten Purbalingga

This research evaluation is a part of activities development management is to know how the activities development works. Evaluation could be good or bad is depended on the inputs of the monitoring systems. This research is analysed by indicator descriptions. The conclusion shows that Purbalingga's PDRB in 2003 increase about 1.3%. In other side, the gaps among sectors are low enough. It means each sector works better and relatively will be spread evenly. That's why the policy of budget allocation is better to lead to have interrelatedness (backward and forward) for all sectors

Creative self-efficacy : a new approach to social support and creativity of SMEs’ owners

Small and Medium Enterprises (SMEs) have a very important role in the economic equality of the community and have a high employment rate. This study examines the direct and indirect effects of social support and creative self-efficacy on the creativity of SMEs’ owners in Banyumas, Indonesia. The sample consists of 119 respondents obtained from Small and Medium business owners in this region. They complement the measure of social support and creative self-efficacy towards the creativity of SME’ owners. Structural equation modeling is used to test the proposed relationship between variables using the maximum likelihood estimation of the sample covariance matrix. The results show that social support, significantly positively influences creative self-efficacy and owner creativity, creative self-efficacy significantly influences the creativity of the owner. The findings also reveal that creative self-efficacy can mediate the relationship of social support with owner creativity. The implications of this study are also discussed.peer-reviewe

Potensi Khamir sebagai Agens Pengendalian Hayati Colletotrichum capsici, Cendawan Penyebab Antraknosa pada Buah Cabai

ABSTRACTAntrachnose on chilli fruit caused by Colletotrichum capsici can reduce yield and quality of chilli fruit. Biological control agent can be used as an alternative to control C. capsici. Yeast is one of biological control agent which is potential to control the pathogen. This study was aimed at testing antagonistic potential of yeast on fruits and vegetables against C. capsici. Twenty two yeast isolates were isolated from banana, rambutan, red chilli, tomato, and eggplant fruits. Screening for antagonistic yeast using well test showed that 5 isolates of yeast (CMM-1, CMM-3, CMM-4, TMM-1, and EMM-11) completely inhibited the growth of C. capsici. Based on the result of biocontrol assay of the pathogen in vivo, four yeast isolates (CMM-3, CMM-4, TMM-1, and EMM-11) completely inhibited C. capsici in vivo. Identification using morphological and molecular characteristics showed that these four yeast isolates were Issatchenkia orientalis.Keywords: antagonistic yeast, antrachnose, biocontrol, Issatchenkia orientalis ABSTRAK Antraknosa pada buah cabai yang disebabkan oleh Colletotrichum capsici dapat menyebabkan penurunan produksi dan kualitas buah cabai. Penggunaan agens pengendalian hayati dapat menjadi salah satu alternatif untuk mengendalikan C. capsici. Khamir merupakan salah satu agens pengendalian hayati yang berpotensi mengendalikan C. capsici. Penelitian ini bertujuan menguji potensi antagonistik khamir pada buah-buahan dan sayuran terhadap C. capsici. Sebanyak 22 isolat khamir diisolasi dari buah rambutan, pisang, cabai merah besar, tomat, dan terung ungu. Seleksi khamir antagonis menggunakan uji sumur diperoleh sebanyak 5 isolat khamir, yaitu isolat CMM-1, CMM-3, CMM-4, TMM-1, dan EMM-11 menghambat total pertumbuhan C. capsici. Isolat CMM-3, CMM-4, TMM-1, dan EMM-11 menghambat total pertumbuhan C. capsici in vivo. Berdasarkan hasil identifikasi secara morfologi dan molekuler, isolat CMM-3, CMM-4, TMM-1, dan EMM-11 adalah Issatchenkia orientalis.Kata kunci: antraknosa, Issatchenkia orientalis, khamir antagonis, pengendalian hayat

Keragaman Genetik Rizobakteri Penghasil Asam Indol Asetat Berdasarkan 16S RRNA dan Amplified Ribosomal DNA Restriction Analysis

Asam indol asetat (AIA) dapat dihasilkan oleh bakteri rizosfer/rizobakteri pemacu pertumbuhan tanaman (PPT). Keragaman genetik isolat bakteri PPT indigenous Indonesia perlu diinvestigasi untuk mencari sumber potensial agen PPT dengan informasi kekerabatan intra dan interspesies yang jelas. Karena itu penelitian ini bertujuan mengetahui keragaman genetik rizobakteri penghasil AIA indigenous Indonesia dengan gen 16S rRNA, dilengkapi dengan ARDRA. Koleksi isolat bakteri BB Biogen diidentifikasi kandungan AIA-nya, morfologi secara makroskopis dan sekuensing pada sekuen 16S rRNA dan ARDRA. Total empat belas isolat rizobakteri memiliki kandungan AIA dalam kisaran 5,24-37,69 µg/ml dan tertinggi pada SM1. Karakteristik morfologi koloni rizobakteri mendukung variasi strain bakteri penghasil AIA. Delapan isolat terpilih diidentifikasi sebagai spesies Bacillus dengan homologi 96-99%. Lima isolat (SM1, JP4, KP3, MB2, dan CP3) diidentifikasikan sebagai B. subtilis, SC2 sebagai B. amyloliquefaciens, BL2 dekat dengan B. velezensis, dan JP3 memiliki homologi tinggi dengan Brevundimonas olei. Delapan isolat rizobakteri tersebut berkerabat dekat dengan strain bakteri referensi yang memiliki kesamaan spesies. Analisis ARDRA-RsaI menghasilkan lima filotipe dengan keunikan pola sidik jari. Isolat CP3, MB 2, dan KP 3 berada dalam satu filotipe. Kedekatan isolat dalam Bacillus sp. digambarkan oleh filotipe 5 (B. subtilis SM1 dan B. velezensis BL2) yang diduga jauh dari B. amyloliquefaciens SC2 (filotipe 4) dan JP 3 pada genus Brevundimonas (filotipe 3). Keragaman genetik isolat rizobakteri penghasil AIA terhitung rendah berdasarkan 16S-rRNA dan ARDRA-RsaI

Calibration of advanced Virgo and reconstruction of the detector strain h( t) during the observing run O3

The three advanced Virgo and LIGO gravitational wave detectors participated to the third observing run (O3) between 1 April 2019 15:00 UTC and 27 March 2020 17:00 UTC, leading to several gravitational wave detections per month. This paper describes the advanced Virgo detector calibration and the reconstruction of the detector strain h(t) during O3, as well as the estimation of the associated uncertainties. For the first time, the photon calibration technique as been used as reference for Virgo calibration, which allowed to cross-calibrate the strain amplitude of the Virgo and LIGO detectors. The previous reference, so-called free swinging Michelson technique, has still been used but as an independent cross-check. h(t) reconstruction and noise subtraction were processed online, with good enough quality to prevent the need for offline reprocessing, except for the two last weeks of September 2019. The uncertainties for the reconstructed h(t) strain, estimated in this paper in a 20-2000 Hz frequency band, are frequency independent: 5% in amplitude, 35 mrad in phase and 10 μs in timing, with the exception of larger uncertainties around 50 Hz

Virgo Detector Characterization and Data Quality during the O3 run

The Advanced Virgo detector has contributed with its data to the rapid growth of the number of detected gravitational-wave signals in the past few years, alongside the two LIGO instruments. First, during the last month of the Observation Run 2 (O2) in August 2017 (with, most notably, the compact binary mergers GW170814 and GW170817) and then during the full Observation Run 3 (O3): an 11 months data taking period, between April 2019 and March 2020, that led to the addition of about 80 events to the catalog of transient gravitational-wave sources maintained by LIGO, Virgo and KAGRA. These discoveries and the manifold exploitation of the detected waveforms require an accurate characterization of the quality of the data, such as continuous study and monitoring of the detector noise. These activities, collectively named {\em detector characterization} or {\em DetChar}, span the whole workflow of the Virgo data, from the instrument front-end to the final analysis. They are described in details in the following article, with a focus on the associated tools, the results achieved by the Virgo DetChar group during the O3 run and the main prospects for future data-taking periods with an improved detector.Comment: 86 pages, 33 figures. This paper has been divided into two articles which supercede it and have been posted to arXiv on October 2022. Please use these new preprints as references: arXiv:2210.15634 (tools and methods) and arXiv:2210.15633 (results from the O3 run

Virgo Detector Characterization and Data Quality: results from the O3 run

The Advanced Virgo detector has contributed with its data to the rapid growth of the number of detected gravitational-wave (GW) signals in the past few years, alongside the two Advanced LIGO instruments. First during the last month of the Observation Run 2 (O2) in August 2017 (with, most notably, the compact binary mergers GW170814 and GW170817), and then during the full Observation Run 3 (O3): an 11-months data taking period, between April 2019 and March 2020, that led to the addition of about 80 events to the catalog of transient GW sources maintained by LIGO, Virgo and now KAGRA. These discoveries and the manifold exploitation of the detected waveforms require an accurate characterization of the quality of the data, such as continuous study and monitoring of the detector noise sources. These activities, collectively named {\em detector characterization and data quality} or {\em DetChar}, span the whole workflow of the Virgo data, from the instrument front-end hardware to the final analyses. They are described in details in the following article, with a focus on the results achieved by the Virgo DetChar group during the O3 run. Concurrently, a companion article describes the tools that have been used by the Virgo DetChar group to perform this work.Comment: 57 pages, 18 figures. To be submitted to Class. and Quantum Grav. This is the "Results" part of preprint arXiv:2205.01555 [gr-qc] which has been split into two companion articles: one about the tools and methods, the other about the analyses of the O3 Virgo dat

Virgo Detector Characterization and Data Quality: tools

Detector characterization and data quality studies -- collectively referred to as {\em DetChar} activities in this article -- are paramount to the scientific exploitation of the joint dataset collected by the LIGO-Virgo-KAGRA global network of ground-based gravitational-wave (GW) detectors. They take place during each phase of the operation of the instruments (upgrade, tuning and optimization, data taking), are required at all steps of the dataflow (from data acquisition to the final list of GW events) and operate at various latencies (from near real-time to vet the public alerts to offline analyses). This work requires a wide set of tools which have been developed over the years to fulfill the requirements of the various DetChar studies: data access and bookkeeping; global monitoring of the instruments and of the different steps of the data processing; studies of the global properties of the noise at the detector outputs; identification and follow-up of noise peculiar features (whether they be transient or continuously present in the data); quick processing of the public alerts. The present article reviews all the tools used by the Virgo DetChar group during the third LIGO-Virgo Observation Run (O3, from April 2019 to March 2020), mainly to analyse the Virgo data acquired at EGO. Concurrently, a companion article focuses on the results achieved by the DetChar group during the O3 run using these tools.Comment: 44 pages, 16 figures. To be submitted to Class. and Quantum Grav. This is the "Tools" part of preprint arXiv:2205.01555 [gr-qc] which has been split into two companion articles: one about the tools and methods, the other about the analyses of the O3 Virgo dat