KIAT Journal of Multidisciplinary Vocational and Applied Research
https://kiatjcd.com/ojs/index.php/kjmvar
<div style="text-align: justify;"> <div style="text-align: justify;"><strong>KIAT Journal of Multidisciplinary Vocational and Applied Research</strong> is a research journal that contains the results of multidisciplinary research such as health, animal husbandry, agriculture, engineering, computer science, and other fields of science. This journal is managed & published by <strong>Yayasan Kiat Indonesia Maju, Jember, Jawa Timur, Indonesia.<br /><br />Journal Descriptions</strong></div> <div style="text-align: justify;"> <table class="data" width="100%" bgcolor="ffffe0"> <tbody> <tr valign="top"> <td width="30%"><strong>Journal title</strong></td> <td width="70%"> <strong><a href="https://kiatjcd.com/ojs/index.php/kjmvar" target="_blank" rel="noopener">KIAT Journal of Multidisciplinary Vocational and Applied Research</a></strong></td> </tr> <tr valign="top"> <td width="30%"><strong>Initials</strong></td> <td width="70%"> <strong>kjmvar</strong></td> </tr> <tr valign="top"> <td width="30%"><strong>Frequency</strong></td> <td width="70%"> <strong><a href="https://kiatjcd.com/ojs/index.php/kjmvar/issue/archive" target="_blank" rel="noopener">2 issues</a> per year</strong></td> </tr> <tr valign="top"> <td width="30%"><strong>Prefix DOI</strong></td> <td width="70%"> <a href="#" target="_blank" rel="noopener"><strong>10.XXXXX</strong></a></td> </tr> <tr valign="top"> <td width="30%"><strong>Online ISSN</strong></td> <td width="70%"> -</td> </tr> <tr valign="top"> <td width="30%"><strong>Editor In Chief</strong></td> <td width="70%"><strong><a> </a><a href="#" target="_blank" rel="noopener">Prof. Dr. Indarto, S.TP., DEA, IPU</a></strong></td> </tr> <tr valign="top"> <td width="30%"><strong>Publisher</strong></td> <td width="70%"><strong> <a href="#" target="_blank" rel="noopener">Yayasan Kiat Indonesia Maju</a></strong></td> </tr> </tbody> </table> </div> </div>en-USKIAT Journal of Multidisciplinary Vocational and Applied Research Analisis Perubahan Sedimentasi Total Suspended Solids (TSS) Menggunakan Citra Satelit Sentinel-2A
https://kiatjcd.com/ojs/index.php/kjmvar/article/view/12
<p>Wonorejo Reservoir is one of the reservoirs in Indonesia that is used as a supplier of raw water for PDAMs in the Surabaya area. The presence of sedimentation will reduce the volume of air that can be used. Wonorejo Reservoir has an area of 3,850 hectares, it will require energy and that is not small if done conventionally. Remote sensing technology with Sentinel 2A satellite imagery can be used as an alternative technology that is more efficient in monitoring sedimentation reservoirs. Monitoring of reservoir sedimentation can be observed from the development of the total suspension solid (TSS) value. This study aims to monitor sedimentation in the Wonorejo Reservoir for the 2016-2019 period. Sentinel image data taken in 2016, 2017, 2018, and 2019. The data used is data with a cloud cover level of less than 30%. The results of multitemporal TSS processing for the 2016-2019 period show the quality of the Wonorejo Reservoir TSS in general is starting to improve. The heavily polluted/sedimented TSS class decreased from 265.6 ha in 2016 to 0 ha in 2019.</p>Bowo Eko CahyonoAch. Fauzan Mas’udiAnila Kusuma Mawar Dhani Mutmainnah Mutmainnah
Copyright (c) 2022 Bowo Eko Cahyono, Ach. Fauzan Mas’udi, Anila Kusuma Mawar Dhani , Mutmainnah Mutmainnah
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2022-06-192022-06-191118Analisis Analisis Aliran Dasar (Base Flow) Menggunakan Metode Kille Pada 8 DAS di Wilayah UPT PSDA Madura
https://kiatjcd.com/ojs/index.php/kjmvar/article/view/20
<p>Baseflow is one of the critical components of the watershed that influences water availability during the dry season. The water availability information used for water resources management purposes. The aims of this research were: (1) calibrating Kille method parameters, (2) visualization Flow Duration Curve (FDC) at watersheds in UPT PSDA Madura. The methodology consists of: (1) inventory of rainfall and daily discharge data, (2) data preparation, (3) calibration, (4) visualization using FDC. The calibration processes using daily discharge data for each watershed. First, excel data was prepared for Kille 3.1 module on the top of Hydrooffice software package. The results show obtained values for the coefficient of determination (R<sup>2</sup>) = 0,97 (at Blega-Telok), 0,98 (at Kemuning), 0,92 (at Klampis), 0,94 (at Klampok-Ambuten), 0,98 (at Nipah-Tabanan), 0,91 (at Samiran-Propo, 0,97 (at Sampang), 0,97 (at Saroka-Lenteng), 0,96. The result of FDC visualization shows that the measured discharge line and both models (linear regression and exponential regression) almost coincide or approach the measured discharge line. This indicates that the kille method is good in modeling the base flow during the dry season.</p>Erwan Bagus SetiawanMoch Fawaid Fauzi Yaqub Indarto IndartoSri WahyuningsihBayu Taruna Widjaja PutraDian Purbasari
Copyright (c) 2022 Erwan Bagus Setiawan, Moch Fawaid Fauzi Yaqub , Indarto Indarto, Sri Wahyuningsih, Bayu Taruna Widjaja Putra, Dian Purbasari
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2022-06-192022-06-1911920Interpretasi Perubahan Tutupan Lahan di Kabupaten Situbondo Berbasis Citra Sentinel-2
https://kiatjcd.com/ojs/index.php/kjmvar/article/view/21
<p>Land cover is the physical form of the earth's surface, such as water bodies, rocks, built-up land, forests, and others, regardless of human activities. Observing land cover changes can be done by comparing two or more map editions. This study aims to obtain information on land cover and its changes by utilizing Sentinel-2 imagery in the Situbondo Regency (± 1651.35 km<sup>2</sup>). Two periods of image collections were used as the input (2015 and 2019). Ten land cover classes have been identified, i.e., (1) built-up land, (2) dry cropland, (3) paddy fields, (4) water bodies, (5) forest, (6) plantation, (7) shrubland, (8) ponds, (9) sand/barren land, and (10) clouds. The Kappa accuracy values for classified images indicate relevant results, 91.9% (2015) and 94.13% (2019). Significant changes occurred in the plantation and shrubland. There was an increase in the plantation by 5.11% (84.39 km<sup>2</sup>), while in the shrubland, there was a decrease of 5.52% (91.27 km<sup>2</sup>). Other classes that experienced expansion were built-up by 2.88% (47.64 km<sup>2</sup>), ponds by 0.09% (1.51 km<sup>2</sup>), and sand/barren land by 3.19% (52.81 km<sup>2</sup>). Conversely, the expansion has reduced dry cropland by 0.65% (10.76 km<sup>2</sup>), rice fields by 3.94% (65.12 km<sup>2</sup>), and forests by 1.53% (25.24 km<sup>2</sup>).</p>Farid Lukman HakimAngga Arya WijayaIndarto IndartoBambang MarhaenantoHeru Ernanda
Copyright (c) 2022 Farid Lukman Hakim, Angga Arya Wijaya, Indarto Indarto, Bambang Marhaenanto, Heru Ernanda
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2022-06-192022-06-19112132Pemisahan Aliran Dasar Menggunakan Master Kurva Resesi di DAS Brantas
https://kiatjcd.com/ojs/index.php/kjmvar/article/view/22
<p>Baseflow is the main component of water supply during the dry seasons. Baseflow contributes to water supply during the recession period and periods of no rain or little rain. This research aims to determine the coefficient during the recession periods of the hydrograph and separate the flow component to three-part i.e., quick, sub-surface and baseflow. Two sub-watersheds outlets at Ploso and Kertosono in the Brantas Watershed areas were chosen for this study. Research procedure concist of data preparation and treatment using microsoft excel, the recession coefficient analysis based on the Master Recession Curve (MRC), evaluation model performance using statistical test and visualisation separation performance using hydrograph. Calibration of MRC produce linear reservoir recession equation of Q = Q0. e–kt. The value of k is the recession coefficient for each flow component. The value of k for Ploso sub-watershed are (k1) =0,04 for baseflow, (k2) = 0,15 sub-surfaceflow and (k3) = 0,428 for quickflow. Rescpectively, for the Kertosono sub-watershed, (k1) =0,06 for baseflow, (k2) = 0,21 sub-surfaceflow and (k3) = 0,47 for quickflow. Stastitical analysis of model performance show the value of r2 = 0,988 and RMSE = 0,69 for Ploso and r2 = 0,976 and RMSE = 0,74 for Kertosono.</p>Mohamad Wawan SujarwoDavit SetiawanIndarto IndartoSri Wahyuningsih
Copyright (c) 2022 Mohamad Wawan Sujarwo, Davit Setiawan, Indarto Indarto, Sri Wahyuningsih
https://creativecommons.org/licenses/by-sa/4.0
2022-06-202022-06-20113342Analisis Kelayakan Pengembangan Agroindustri Tahu di UD. Jamhari Kabupaten Jember Dengan Menggunakan Decission Support System
https://kiatjcd.com/ojs/index.php/kjmvar/article/view/28
<p>One of the tofu processing agroindustry in Jember is UD. Jamhari. UD. Jamhari is located in Darwo Timur, Gebang, Jember. The purpose of this feasibility study and business development at UD. Jamhari is to determine the feasibility of financial aspects, legal aspects, marketing aspects, production aspects, HR aspects, and environmental aspects for business development. This study uses the Decission Support System software version 2.0. Based on the results of the analysis using DSS, all non-financial aspects are declared eligible with a moderate level of feasibility, which are marked with yellow illustrations. Financial analysis results obtained BEP quantity 50,126.58 products, BEP Sales as much as Rp. 303.652.713.74, BC Ratio 1.15, Pacyback Period 1.48, NPV Rp. 2.349.182.181.51, PI 9.85% and IRR 56, 23. So all financial and non-financial aspects lead to the conclusion that all aspects analyzed are in moderate feasibility and business development can be carried out.</p>Eva Nur IsnainiR. Abdoel Djamali
Copyright (c) 2022 Eva Nur Isnaini, R. Abdoel Djamali
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2022-06-202022-06-20114350Klasifikasi Pendapat Masyarakat Terhadap Penggunaan Vaksin Dalam Mengantisipasi Covid-19 Menggunakan Teknik Sentiment Analisis Berbasis Naïve Bayes
https://kiatjcd.com/ojs/index.php/kjmvar/article/view/30
<p>The Covid-19 pandemic is not over yet. Vaccinations that have been carried out so far are still getting pros and cons among the public. This study contains an analysis of public opinion on vaccination using the Naive Bayes-based method which was collected from the Twitter timeline from February 23 to March 9, 2021. The number of opinions that were successfully collected and used as data in this study were 1000 tweet data which were divided into 200 test data tweets. validation and 800 training data tweets. This study also uses Chi-Square as a feature selection method. The algorithms used in this research are Naive Bayes and Multinomial Naive Bayes. From the measurement results on the tests carried out, the Naive Bayes method obtained an accuracy value of 66%, precision of 79% and recall of 62%. While the Multinomial Naive Bayes method obtains an accuracy value of 71%, a precision of 81% and a recall of 68%. Based on the results obtained, the Multinomial Naive Bayes algorithm has a better performance than Naive Bayes.</p>Widya DamayantiBagus Setya RintyarnaWiwik Suharso
Copyright (c) 2022 Widya Damayanti, Bagus Setya Rintyarna, Wiwik Suharso
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2022-06-262022-06-26115158