Juridical Review of Minimum Service Standards at Manggarai Station
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Justice, Transitional, Concept
Abstract
Background. Manggarai Station is a large type A train station which is the busiest station. Manggarai Station is under construction and is divided into several stages. As a result of the change in the transit route, it causes passenger discomfort, which is poured on social media.
Purpose. This study aims to evaluate the station's performance on changes in the transit route for train travel via the Manggarai station for passengers by the provisions of the applicable regulations.
Method. The method used in this research is an empirical legal research study, which is a type of research study that seeks data directly from the field or looks at law in a real sense and studies how the law works in society.33 of 2011 Types, Classes, and Activities at Railway Stations and PM No 63 of 2019 concerning Minimum Service Standards for the Transport of People by Train.
Results. The results obtained based on previous research with Importance Performance Analysis still show passenger dissatisfaction, and according to laws and regulations, the public as users of transportation services have the right to submit input related to rail transportation so that PT KCI can provide minimum service standards at stations consisting of security and safety, accurate information, ticket sales services, good condition of station facilities, accessibility, assistance and complaint services.
Conclusion. In Ministerial Regulation No. 63 of 2019 concerning Minimum Service Standards for the Transport of People by Train, PT KCI is responsible for KRL passengers at the Manggarai train station and while traveling on the train. This research only discusses the responsibility of PT KCI in providing minimum service standards at manggarai station.
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References
Bojanic, D. C., & Warnick, R. B. (2020). The Relationship between a Country’s Level of Tourism and Environmental Performance. Journal of Travel Research, 59(2), 220–230. https://doi.org/10.1177/0047287519827394
Callhoff, J., Albrecht, K., Redeker, I., Lange, T., Goronzy, J., Günther, K., Zink, A., Schmitt, J., Saam, J., & Postler, A. (2020). Disease Burden of Patients With Osteoarthritis: Results of a Cross?Sectional Survey Linked to Claims Data. Arthritis Care & Research, 72(2), 193–200. https://doi.org/10.1002/acr.24058
Chandrasekar, R., Chandrasekhar, S., Sundari, K. K. S., & Ravi, P. (2020). Development and validation of a formula for objective assessment of cervical vertebral bone age. Progress in Orthodontics, 21(1), 38. https://doi.org/10.1186/s40510-020-00338-0
Coppola, L., Cianflone, A., Grimaldi, A. M., Incoronato, M., Bevilacqua, P., Messina, F., Baselice, S., Soricelli, A., Mirabelli, P., & Salvatore, M. (2019). Biobanking in health care: Evolution and future directions. Journal of Translational Medicine, 17(1), 172. https://doi.org/10.1186/s12967-019-1922-3
Di Vaio, A., Palladino, R., Hassan, R., & Escobar, O. (2020). Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review. Journal of Business Research, 121, 283–314. https://doi.org/10.1016/j.jbusres.2020.08.019
Elvén, M., Kerstis, B., Stier, J., Hellström, C., Von Heideken Wågert, P., Dahlen, M., & Lindberg, D. (2022). Changes in Physical Activity and Sedentary Behavior before and during the COVID-19 Pandemic: A Swedish Population Study. International Journal of Environmental Research and Public Health, 19(5), 2558. https://doi.org/10.3390/ijerph19052558
Karimi-Maleh, H., Darabi, R., Shabani-Nooshabadi, M., Baghayeri, M., Karimi, F., Rouhi, J., Alizadeh, M., Karaman, O., Vasseghian, Y., & Karaman, C. (2022). Determination of D&C Red 33 and Patent Blue V Azo dyes using an impressive electrochemical sensor based on carbon paste electrode modified with ZIF-8/g-C3N4/Co and ionic liquid in mouthwash and toothpaste as real samples. Food and Chemical Toxicology, 162, 112907. https://doi.org/10.1016/j.fct.2022.112907
Luque, A., Carrasco, A., Martín, A., & De Las Heras, A. (2019). The impact of class imbalance in classification performance metrics based on the binary confusion matrix. Pattern Recognition, 91, 216–231. https://doi.org/10.1016/j.patcog.2019.02.023
Makdessi, C. J., Day, C., & Chaar, B. B. (2019). Challenges faced with opioid prescriptions in the community setting – Australian pharmacists’ perspectives. Research in Social and Administrative Pharmacy, 15(8), 966–973. https://doi.org/10.1016/j.sapharm.2019.01.017
Mao, S.-J., Shen, J., Xu, F., & Zou, C.-C. (2019). Quality of life in caregivers of young children with Prader–Willi syndrome. World Journal of Pediatrics, 15(5), 506–510. https://doi.org/10.1007/s12519-019-00311-w
Morel, L., Yao, Z., Cladé, P., & Guellati-Khélifa, S. (2020). Determination of the fine-structure constant with an accuracy of 81 parts per trillion. Nature, 588(7836), 61–65. https://doi.org/10.1038/s41586-020-2964-7
Nosyk, B., Slaunwhite, A., Urbanoski, K., Hongdilokkul, N., Palis, H., Lock, K., Min, J. E., Zhao, B., Card, K. G., Barker, B., Meilleur, L., Burmeister, C., Thomson, E., Beck-McGreevy, P., & Pauly, B. (2021). Evaluation of risk mitigation measures for people with substance use disorders to address the dual public health crises of COVID-19 and overdose in British Columbia: A mixed-method study protocol. BMJ Open, 11(6), e048353. https://doi.org/10.1136/bmjopen-2020-048353
Paul, D., Sanap, G., Shenoy, S., Kalyane, D., Kalia, K., & Tekade, R. K. (2021). Artificial intelligence in drug discovery and development. Drug Discovery Today, 26(1), 80–93. https://doi.org/10.1016/j.drudis.2020.10.010
Pretorius, B., Ambuko, J., Papargyropoulou, E., & Schönfeldt, H. C. (2021). Guiding Nutritious Food Choices and Diets along Food Systems. Sustainability, 13(17), 9501. https://doi.org/10.3390/su13179501
Riess, A. G., Casertano, S., Yuan, W., Macri, L. M., & Scolnic, D. (2019). Large Magellanic Cloud Cepheid Standards Provide a 1% Foundation for the Determination of the Hubble Constant and Stronger Evidence for Physics beyond ?CDM. The Astrophysical Journal, 876(1), 85. https://doi.org/10.3847/1538-4357/ab1422
Scarabottolo, C. C., Tebar, W. R., Gobbo, L. A., Ohara, D., Ferreira, A. D., Da Silva Canhin, D., & Christofaro, D. G. D. (2022). Analysis of different domains of physical activity with health-related quality of life in adults: 2-year cohort. Health and Quality of Life Outcomes, 20(1), 71. https://doi.org/10.1186/s12955-022-01981-3
Stuart, T., Butler, A., Hoffman, P., Hafemeister, C., Papalexi, E., Mauck, W. M., Hao, Y., Stoeckius, M., Smibert, P., & Satija, R. (2019). Comprehensive Integration of Single-Cell Data. Cell, 177(7), 1888-1902.e21. https://doi.org/10.1016/j.cell.2019.05.031
Tambe, P., Cappelli, P., & Yakubovich, V. (2019). Artificial Intelligence in Human Resources Management: Challenges and a Path Forward. California Management Review, 61(4), 15–42. https://doi.org/10.1177/0008125619867910
Yang, W.-Y., Melgarejo, J. D., Thijs, L., Zhang, Z.-Y., Boggia, J., Wei, F.-F., Hansen, T. W., Asayama, K., Ohkubo, T., Jeppesen, J., Dolan, E., Stolarz-Skrzypek, K., Malyutina, S., Casiglia, E., Lind, L., Filipovský, J., Maestre, G. E., Li, Y., Wang, J.-G., … for The International Database on Ambulatory Blood Pressure in Relation to Cardiovascular Outcomes (IDACO) Investigators. (2019). Association of Office and Ambulatory Blood Pressure With Mortality and Cardiovascular Outcomes. JAMA, 322(5), 409. https://doi.org/10.1001/jama.2019.9811
Yang, Y., Gao, W., Guo, S., Mao, Y., & Yang, Y. (2019). Introduction to BeiDou?3 navigation satellite system. Navigation, 66(1), 7–18. https://doi.org/10.1002/navi.291
Zhang, S., Yao, L., Sun, A., & Tay, Y. (2020). Deep Learning Based Recommender System: A Survey and New Perspectives. ACM Computing Surveys, 52(1), 1–38. https://doi.org/10.1145/3285029
Abuhassna, H., Al-Rahmi, W. M., Yahya, N., Zakaria, M. A. Z. M., Kosnin, A. Bt. M., & Darwish, M. (2020). Development of a new model on utilizing online learning platforms to improve students’ academic achievements and satisfaction. International Journal of Educational Technology in Higher Education, 17(1), 38. https://doi.org/10.1186/s41239-020-00216-z
Adegbeye, M. J., Ravi Kanth Reddy, P., Obaisi, A. I., Elghandour, M. M. M. Y., Oyebamiji, K. J., Salem, A. Z. M., Morakinyo-Fasipe, O. T., Cipriano-Salazar, M., & Camacho-Díaz, L. M. (2020). Sustainable agriculture options for production, greenhouse gasses and pollution alleviation, and nutrient recycling in emerging and transitional nations—An overview. Journal of Cleaner Production, 242, 118319. https://doi.org/10.1016/j.jclepro.2019.118319
Ali, H., Khan, E., & Ilahi, I. (2019). Environmental Chemistry and Ecotoxicology of Hazardous Heavy Metals: Environmental Persistence, Toxicity, and Bioaccumulation. Journal of Chemistry, 2019, 1–14. https://doi.org/10.1155/2019/6730305
Carleo, G., Cirac, I., Cranmer, K., Daudet, L., Schuld, M., Tishby, N., Vogt-Maranto, L., & Zdeborová, L. (2019). Machine learning and the physical sciences. Reviews of Modern Physics, 91(4), 045002. https://doi.org/10.1103/RevModPhys.91.045002
Cheng, Y., Luo, R., Wang, K., Zhang, M., Wang, Z., Dong, L., Li, J., Yao, Y., Ge, S., & Xu, G. (2020). Kidney disease is associated with in-hospital death of patients with COVID-19. Kidney International, 97(5), 829–838. https://doi.org/10.1016/j.kint.2020.03.005
Glare, P., Aubrey, K. R., & Myles, P. S. (2019). Transition from acute to chronic pain after surgery. The Lancet, 393(10180), 1537–1546. https://doi.org/10.1016/S0140-6736(19)30352-6
Johdi, N. A., & Sukor, N. F. (2020). Colorectal Cancer Immunotherapy: Options and Strategies. Frontiers in Immunology, 11, 1624. https://doi.org/10.3389/fimmu.2020.01624
Kampf, G., Todt, D., Pfaender, S., & Steinmann, E. (2020). Persistence of coronaviruses on inanimate surfaces and their inactivation with biocidal agents. Journal of Hospital Infection, 104(3), 246–251. https://doi.org/10.1016/j.jhin.2020.01.022
Lisio, M.-A., Fu, L., Goyeneche, A., Gao, Z., & Telleria, C. (2019). High-Grade Serous Ovarian Cancer: Basic Sciences, Clinical and Therapeutic Standpoints. International Journal of Molecular Sciences, 20(4), 952. https://doi.org/10.3390/ijms20040952
Lurie, N., Saville, M., Hatchett, R., & Halton, J. (2020). Developing Covid-19 Vaccines at Pandemic Speed. New England Journal of Medicine, 382(21), 1969–1973. https://doi.org/10.1056/NEJMp2005630
Norris, P., & Inglehart, R. (2019). Cultural Backlash: Trump, Brexit, and Authoritarian Populism (1 ed.). Cambridge University Press. https://doi.org/10.1017/9781108595841
Parisi, G. I., Kemker, R., Part, J. L., Kanan, C., & Wermter, S. (2019). Continual lifelong learning with neural networks: A review. Neural Networks, 113, 54–71. https://doi.org/10.1016/j.neunet.2019.01.012
Phillips, J. C., Hardy, D. J., Maia, J. D. C., Stone, J. E., Ribeiro, J. V., Bernardi, R. C., Buch, R., Fiorin, G., Hénin, J., Jiang, W., McGreevy, R., Melo, M. C. R., Radak, B. K., Skeel, R. D., Singharoy, A., Wang, Y., Roux, B., Aksimentiev, A., Luthey-Schulten, Z., … Tajkhorshid, E. (2020). Scalable molecular dynamics on CPU and GPU architectures with NAMD. The Journal of Chemical Physics, 153(4), 044130. https://doi.org/10.1063/5.0014475
Van Trotsenburg, P., Stoupa, A., Léger, J., Rohrer, T., Peters, C., Fugazzola, L., Cassio, A., Heinrichs, C., Beauloye, V., Pohlenz, J., Rodien, P., Coutant, R., Szinnai, G., Murray, P., Bartés, B., Luton, D., Salerno, M., De Sanctis, L., Vigone, M., … Polak, M. (2021). Congenital Hypothyroidism: A 2020–2021 Consensus Guidelines Update—An ENDO-European Reference Network Initiative Endorsed by the European Society for Pediatric Endocrinology and the European Society for Endocrinology. Thyroid, 31(3), 387–419. https://doi.org/10.1089/thy.2020.0333
Walsh, E. E., Frenck, R. W., Falsey, A. R., Kitchin, N., Absalon, J., Gurtman, A., Lockhart, S., Neuzil, K., Mulligan, M. J., Bailey, R., Swanson, K. A., Li, P., Koury, K., Kalina, W., Cooper, D., Fontes-Garfias, C., Shi, P.-Y., Türeci, Ö., Tompkins, K. R., … Gruber, W. C. (2020). Safety and Immunogenicity of Two RNA-Based Covid-19 Vaccine Candidates. New England Journal of Medicine, 383(25), 2439–2450. https://doi.org/10.1056/NEJMoa2027906
Wang, G., Ye, J. C., & De Man, B. (2020). Deep learning for tomographic image reconstruction. Nature Machine Intelligence, 2(12), 737–748. https://doi.org/10.1038/s42256-020-00273-z
Wang, Y., Xu, Y., Tabari, H., Wang, J., Wang, Q., Song, S., & Hu, Z. (2020). Innovative trend analysis of annual and seasonal rainfall in the Yangtze River Delta, eastern China. Atmospheric Research, 231, 104673. https://doi.org/10.1016/j.atmosres.2019.104673
Wang, Z., Li, C., & Domen, K. (2019). Recent developments in heterogeneous photocatalysts for solar-driven overall water splitting. Chemical Society Reviews, 48(7), 2109–2125. https://doi.org/10.1039/C8CS00542G
Yatabe, Y., Dacic, S., Borczuk, A. C., Warth, A., Russell, P. A., Lantuejoul, S., Beasley, M. B., Thunnissen, E., Pelosi, G., Rekhtman, N., Bubendorf, L., Mino-Kenudson, M., Yoshida, A., Geisinger, K. R., Noguchi, M., Chirieac, L. R., Bolting, J., Chung, J.-H., Chou, T.-Y., … Moreira, A. L. (2019). Best Practices Recommendations for Diagnostic Immunohistochemistry in Lung Cancer. Journal of Thoracic Oncology, 14(3), 377–407. https://doi.org/10.1016/j.jtho.2018.12.005
Zemek, R. M., De Jong, E., Chin, W. L., Schuster, I. S., Fear, V. S., Casey, T. H., Forbes, C., Dart, S. J., Leslie, C., Zaitouny, A., Small, M., Boon, L., Forrest, A. R. R., Muiri, D. O., Degli-Esposti, M. A., Millward, M. J., Nowak, A. K., Lassmann, T., Bosco, A., … Lesterhuis, W. J. (2019). Sensitization to immune checkpoint blockade through activation of a STAT1/NK axis in the tumor microenvironment. Science Translational Medicine, 11(501), eaav7816. https://doi.org/10.1126/scitranslmed.aav7816
Zhou, M., Wang, H., Zeng, X., Yin, P., Zhu, J., Chen, W., Li, X., Wang, L., Wang, L., Liu, Y., Liu, J., Zhang, M., Qi, J., Yu, S., Afshin, A., Gakidou, E., Glenn, S., Krish, V. S., Miller-Petrie, M. K., … Liang, X. (2019). Mortality, morbidity, and risk factors in China and its provinces, 1990–2017: A systematic analysis for the Global Burden of Disease Study 2017. The Lancet, 394(10204), 1145–1158. https://doi.org/10.1016/S0140-6736(19)30427-1
Zong, Q., Yang, H., Wang, Q., Zhang, Q., Zhu, Y., Wang, H., & Shen, Q. (2019). Three-dimensional coral-like NiCoP@C@Ni(OH)2 core-shell nanoarrays as battery-type electrodes to enhance cycle stability and energy density for hybrid supercapacitors. Chemical Engineering Journal, 361, 1–11. https://doi.org/10.1016/j.cej.2018.12.041
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