Jurnal
EVALUASI SISTEM PENGENDALIAN INTERNAL PEMUNGUTAN PAJAK DAERAH PADA BADAN PENGELOLA PAJAK DAN RETRIBUSI DAERAH KOTA KENDARI
JURNAL AKUNTANSI DAN KEUANGAN · Vol. 4 No. 2 (2020)
- ISSN
- 2503-1635
- Published
- 2020-08-09
- Publisher
- Universitas Halu Oleo
- Language
- eng
Abstract
This study aims to evaluate the internal control system which is guided by government regulation number 60 of 2008 concerning the government's internal control system and the local tax collection system which is guided by government regulation number 55 of 2016 concerning general provisions and procedures for collecting local taxes. This research was conducted at the Tax Management Agency and Regional Retribution of Kendari City. The data analysis method used in this research is descriptive analysis method. The type of data used in this study is qualitative, qualitative data in the form of questionnaires. The method of data collection uses questionnaire and interview methods.The results of this study indicate that the percentage of the internal control system is categorized as very adequate with a value of 81.08%. The percentage obtained by each indicator, namely for the Control Indicator Environment is categorized as adequate with a value of 79.31%. The Risk Assessment Indicator is categorized as adequate with a value of 78.11%. The Indicator of Control Activities is categorized as very adequate with a value of 81.93%. Information and Communication indicators are categorized as very adequate with a value of 84.32%. Monitoring indicators are categorized as very adequate with a value of 88.21%. Overall, the five indicators show a very adequate category, which is 81.08%. The percentage of the local tax collection system is categorized very according to the value of 99.16%. The percentage obtained by each indicator, namely for the Registration Data Indicator is categorized as very suitable with a value of 98.65%. Determination indicators objections are categorized as very suitable with a value of 100.00%. Billing Indicators are categorized as very suitable with a value of 100.00%. Overall, the three indicators show very suitable categories, namely 99.16 %%
Collaboration network of the authors
33 authors · 95 co-authorship links
Hover or tap a name to highlight its co-authors. Double-click to open the author's page.
- Universitas Halu Oleo
- Universitas Muslim Indonesia
- Affiliation unknown
- Different organisations
- Same organisation
- Affiliation unknown
- Thicker line = more joint articles · bigger circle = more articles
Show as table
| Co-author | Organisation | Joint articles |
|---|---|---|
| Emillia Nurdin | Affiliation unknown | 2 |
| Ishak Awaluddin | Affiliation unknown | 2 |
| Sulvariany Tamburaka | Affiliation unknown | 2 |
| Husin husin | Affiliation unknown | 2 |
| Arifuddin Arifuddin | Universitas Halu Oleo | 1 |
| Tuti Dharmawati | Affiliation unknown | 1 |
| Safaruddin Safaruddin | Universitas Muslim Indonesia | 1 |
| Andi Basru Wawo | Affiliation unknown | 1 |
| Intihanah Intihanah | Affiliation unknown | 1 |
| Adol Pina | Affiliation unknown | 1 |
| Ahmad Ibnu Sulis | Affiliation unknown | 1 |
| Yusna Herman | Affiliation unknown | 1 |
| Ayu Lestari | Affiliation unknown | 1 |
| Nur Asni | Affiliation unknown | 1 |
| Rio Rizky Ansar | Affiliation unknown | 1 |
| Muntu Abdullah | Affiliation unknown | 1 |
| Ade Yustika Kamal | Affiliation unknown | 1 |
| Cahyaniza Cahyaniza | Affiliation unknown | 1 |
| Mulyati Akib | Affiliation unknown | 1 |
| Kadek Sutrawati | Affiliation unknown | 1 |
| Arifuddin Mas'ud | Affiliation unknown | 1 |
| Lilis Feby Rahayu | Affiliation unknown | 1 |
| Wa Ode Rahmi Damayanti | Affiliation unknown | 1 |
| Andi Basru Wawo | Affiliation unknown | 1 |
| Fathu Rahman | Affiliation unknown | 1 |
| Erwin Hadisantoso | Affiliation unknown | 1 |
| Fendi Fendi | Affiliation unknown | 1 |
| Wa Ode Aswati | Affiliation unknown | 1 |
| Rafat Rafat | Affiliation unknown | 1 |
| Capriyani Haris | Affiliation unknown | 1 |
Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.