The Effect of Auditor Competence, Independence, And Experience on Audit Quality in Public Accounting Firm (KAP) in Bali Province

The purpose of this study is to determine the influence of auditor competence, independence, and experience on audit quality. This research was conducted at a Public Accounting Firm located in the Province of Bali. The population used in this study is all auditors who work in several Public Accounting Firms in Bali Province. The sampling method in this study is by using convenience sampling, which is as many as 80 respondents. The data collection method used in this study is in the form of a questionnaire. Data analysis technique using Partial Least Squares. The results of this study show that auditor competence has a significant positive effect on audit quality, auditor independence has a significant positive effect on audit quality and auditor experience has a significant positive effect on audit quality. It is hoped that the Public Accounting Firm in Bali Province, can direct auditors to take part in training programs or certification of the public accounting profession, can provide regular training that focuses on the implementation of independence and provide mentoring programs for senior auditors or KAP partners as mentors for junior auditors, so that they can learn from direct experience

Validation of Daily Rainfall Based on Global Satellite Mapping of Precipitation (GSMAP) Data of Bali and Nusa Tenggara Region

Limitations of observation data cause analysis and prediction of precipitation is difficult. One way to overcome such limitations is the use of satellite data such as GSMaP, but satellite data needs to be validated before use. This study aims to validate GSMaP rainfall data on observation data in Bali and Nusa Tenggara. Through monthly time series analysis, GSMaP rainfall data tend to have smaller value than observation data, but it has similar data pattern in each region with rain pattern that occurs in November to March (NDJFM). While validation between GSMaP satellite rainfall data and observation using Pearson and RMSE correlation and MBE at each location showed strong positive correlation value (> 0.5), correlation value obtained from each location from 0.82 to 0.93 with RMSE value from 2.08 to 5.51 and MBE values ??from 0.23 to 0.89, this indicates that GSMaP satellite data is valid and can be used to fill in empty data especially in 5 observation areas ie Denpasar, Ampenan, Sumbawa Besar, Bima and Kupang

Peningkatan Kinerja Karyawan Melalui Motivasi dan Kompensasi dengan Kepuasan Kerja Sebagai Mediasi

Task encouragement as well as allowance are elements which are desired to increase the ability of employees. With work encouragement and good allowance, it is desired that employees can always be open minded, emit enthusiasm, to enjoy doing their jobs. This wish of this analysis is to understand the impact of task encouragement elements and task compensation factors on the ability of employees by mediating work pleasure at PT Setiawan Sedjati Denpasar Branch. In this analysis, involving all employees with a questionnaire for data accumulation uses a five-level Likert value. In addition, data split techniques are also used using multiple regression analysis using Statistical Product and Service Solutions. From an solving point the view, it proves that encouragement and benefits have a direct relationship with job satisfaction at PT Setiawan Sedjati Denpasar Branch, and motivation, benefits and work pleasure have a direct relationship with the ability of employees at PT Setiawan Sedjati Denpasar Branch

POTENSI PENGEMBANGAN MINAMULYASARI SEBAGAI OBJEK WISATA (STUDI KASUS DI DESA BENDOSARI, BLITAR)

The purpose of this research is to find 1)  the strengths, weaknesses, opportunities and threats of Minamulyasari in the village of Bendosari as tourism object.  2) the obstacles in the development of tourism object, and 3) to formulate strategies for the development of Minamulyasari tourism object. It is expected that the formulated strategy can increase the income of member group of Minamulyasari. Minamulyasari is a group of ornamental and freshwater fish farmers in Bendosari village, Blitar district which cultivate fish for consumption and ornamental fish. The pool area is about 3 hectares. Initially they were farmers who planted rice crops, corn and beans but saw the potential of better fish farming then they changed their farmland into fish ponds.This research is intended to find the potential that exists within the business group that can be developed into a tourism object. To achieve these objectives, the research was conducted by using descriptive qualitative method. Data includes primary data and secondary data. The data will be analyzed using SWOT analysis. The research results will also be used as a reference for business development of the group. To make Minamulyasari a tourism object there must be additional infrastructures and human development trainin

Pengaruh Teknik Penanganan Negasi Dalam Analisis Sentimen

“Garbage in, garbage out” merupakan sebuah ungkapan klasik dalam data science yang menyatakan bahwa kualitas keluaran suatu sistem bergantung pada kualitas data yang dimasukkan. Dalam klasifikasi sentimen, negasi memainkan peran penting dalam menentukan polaritas sentimen kalimat, tetapi sering kali dihapus pada tahap preprocessing sebagai stopword, yang dapat menghilangkan konteks negasi tersebut. Penelitian ini mengevaluasi dampak dua teknik penanganan negasi Next Word Negation dan penggantian antonim terhadap performa Naïve Bayes Classifier dan Support Vector Machine Classifier. Teknik Next Word Negation menggabungkan kata penanda negasi dengan kata setelahnya seperti “tidak cepat” menjadi “tidak_cepat”. Sementara itu, teknik penggantian antonim mengganti kata penanda negasi dan kata setelahnya dengan antonim dari kata setelahnya, misalnya “tidak cepat” menjadi “lambat”. Hasil penelitian menunjukkan bahwa teknik penanganan negasi meningkatkan akurasi Naïve Bayes dari 82,94% tanpa penanganan negasi menjadi 85,88% dengan Next Word Negation dan 87,64% dengan penggantian antonim. Untuk Support Vector Machine, akurasi meningkat dari 84,70% tanpa penanganan negasi menjadi 89,41% dengan penggantian antonim dan 88,23% dengan Next Word Negation. Abstract “Garbage in, garbage out” is a classic expression in data science that states the quality of a system’s output depends on the quality of the input data. In sentiment classification, negation plays a crucial role in determining the sentiment polarity of a sentence but is often removed during the preprocessing stage as a stopword, potentially eliminating the context of negation. This study evaluates the impact of two negation-handling techniques, Next Word Negation and antonym replacement, on the performance of Naïve Bayes Classifier and Support Vector Machine Classifier. The Next Word Negation technique combines the negation marker with the following word, for example, “tidak cepat” becomes “tidak_cepat”. Meanwhile, the antonym replacement technique replaces the negation marker and the following word with the antonym of the following word, for example, “tidak cepat” becomes “lambat”. The results of the study show that negation-handling techniques improve the accuracy of Naïve Bayes from 82.94% without negation handling to 85.88% with Next Word Negation and 87.64% with antonym replacement. For the Support Vector Machine, accuracy increases from 84.70% without negation handling to 89.41% with antonym replacement and 88.23% with Next Word Negation.“Garbage in, garbage out” merupakan sebuah ungkapan klasik dalam data science yang menyatakan bahwa kualitas keluaran suatu sistem bergantung pada kualitas data yang dimasukkan. Dalam klasifikasi sentimen, negasi memainkan peran penting dalam menentukan polaritas sentimen kalimat, tetapi sering kali dihapus pada tahap preprocessing sebagai stopword, yang dapat menghilangkan konteks negasi tersebut. Penelitian ini mengevaluasi dampak dua teknik penanganan negasi Next Word Negation dan penggantian antonim terhadap performa Naïve Bayes Classifier dan Support Vector Machine Classifier. Teknik Next Word Negation menggabungkan kata penanda negasi dengan kata setelahnya seperti “tidak cepat” menjadi “tidak_cepat”. Sementara itu, teknik penggantian antonim mengganti kata penanda negasi dan kata setelahnya dengan antonim dari kata setelahnya, misalnya “tidak cepat” menjadi “lambat”. Hasil penelitian menunjukkan bahwa teknik penanganan negasi meningkatkan akurasi Naïve Bayes dari 82,94% tanpa penanganan negasi menjadi 85,88% dengan Next Word Negation dan 87,64% dengan penggantian antonim. Untuk Support Vector Machine, akurasi meningkat dari 84,70% tanpa penanganan negasi menjadi 89,41% dengan penggantian antonim dan 88,23% dengan Next Word Negation. Abstract “Garbage in, garbage out” is a classic expression in data science that states the quality of a system’s output depends on the quality of the input data. In sentiment classification, negation plays a crucial role in determining the sentiment polarity of a sentence but is often removed during the preprocessing stage as a stopword, potentially eliminating the context of negation. This study evaluates the impact of two negation-handling techniques, Next Word Negation and antonym replacement, on the performance of Naïve Bayes Classifier and Support Vector Machine Classifier. The Next Word Negation technique combines the negation marker with the following word, for example, “tidak cepat” becomes “tidak_cepat”. Meanwhile, the antonym replacement technique replaces the negation marker and the following word with the antonym of the following word, for example, “tidak cepat” becomes “lambat”. The results of the study show that negation-handling techniques improve the accuracy of Naïve Bayes from 82.94% without negation handling to 85.88% with Next Word Negation and 87.64% with antonym replacement. For the Support Vector Machine, accuracy increases from 84.70% without negation handling to 89.41% with antonym replacement and 88.23% with Next Word Negation

Pengaruh Teknik Penanganan Negasi Dalam Analisis Sentimen

“Garbage in, garbage out” merupakan sebuah ungkapan klasik dalam data science yang menyatakan bahwa kualitas keluaran suatu sistem bergantung pada kualitas data yang dimasukkan. Dalam klasifikasi sentimen, negasi memainkan peran penting dalam menentukan polaritas sentimen kalimat, tetapi sering kali dihapus pada tahap preprocessing sebagai stopword, yang dapat menghilangkan konteks negasi tersebut. Penelitian ini mengevaluasi dampak dua teknik penanganan negasi Next Word Negation dan penggantian antonim terhadap performa Naïve Bayes Classifier dan Support Vector Machine Classifier. Teknik Next Word Negation menggabungkan kata penanda negasi dengan kata setelahnya seperti “tidak cepat” menjadi “tidak_cepat”. Sementara itu, teknik penggantian antonim mengganti kata penanda negasi dan kata setelahnya dengan antonim dari kata setelahnya, misalnya “tidak cepat” menjadi “lambat”. Hasil penelitian menunjukkan bahwa teknik penanganan negasi meningkatkan akurasi Naïve Bayes dari 82,94% tanpa penanganan negasi menjadi 85,88% dengan Next Word Negation dan 87,64% dengan penggantian antonim. Untuk Support Vector Machine, akurasi meningkat dari 84,70% tanpa penanganan negasi menjadi 89,41% dengan penggantian antonim dan 88,23% dengan Next Word Negation. Abstract “Garbage in, garbage out” is a classic expression in data science that states the quality of a system’s output depends on the quality of the input data. In sentiment classification, negation plays a crucial role in determining the sentiment polarity of a sentence but is often removed during the preprocessing stage as a stopword, potentially eliminating the context of negation. This study evaluates the impact of two negation-handling techniques, Next Word Negation and antonym replacement, on the performance of Naïve Bayes Classifier and Support Vector Machine Classifier. The Next Word Negation technique combines the negation marker with the following word, for example, “tidak cepat” becomes “tidak_cepat”. Meanwhile, the antonym replacement technique replaces the negation marker and the following word with the antonym of the following word, for example, “tidak cepat” becomes “lambat”. The results of the study show that negation-handling techniques improve the accuracy of Naïve Bayes from 82.94% without negation handling to 85.88% with Next Word Negation and 87.64% with antonym replacement. For the Support Vector Machine, accuracy increases from 84.70% without negation handling to 89.41% with antonym replacement and 88.23% with Next Word Negation

LINGKUNGAN TEMPAT TINGGAL SEBAGAI FAKTOR RESIKO INFEKSI VIRUS DENGUE PADA ANAK-ANAK

Demam Berdarah Dengue adalah penyakit disebabkan oleh virus dengue yang berkembang pesat di negara dengan iklim tropis seperti Indonesia. Penelitian ini bertujuan untuk mengidentifikasi faktor risiko infeksi virus dengue pada anak-anak di wilayah kerja Puskesmas Denpasar Selatan. Penelitian merupakan penelitian observasional analitikal dengan pendekatan cross-sectional. Data diperoleh dari jawaban reponden terhadap kuesioner yang telah tervalidasi sebelumnya dan selanjutnya data dianalisis secara univariat dan bivariat menggunakan aplikasi statistik yakni SPSS. Terdapat 75 responden yang mengikuti penelitian ini dengan rerata usia yakni 12±3,094 tahun. Karakteristik responden didominasi oleh anak laki-laki (73,3%) dan domisili di perkotaan (68%). Anak-anak lebih banyak tinggal di daerah yang padat penduduk (66,6%) dengan sanitasi lingkungan memadai hanya 45,3% dari total responden. Ditambah lagi, anak-anak memiliki risiko terinfeksi virus dengue dan mengalami demam berdarah pada lingkungan tempat tinggal di perkotaan dengan mobilitas penduduk yang padat (PR: 2,716; IK95%: 2,047-18,067; p: 0,011). Berdasarkan hasil penelitian ini, dapat disimpulkan bahwa lingkungan tempat tinggal menjadi faktor risiko terhadap infeksi virus dengue pada anak-anak, sehingga diperlukan upaya preventif yang terfokus untuk mencegah infeksi virus dengu

KEEFEKTIFAN SISTEM STRUKTURAL PADA MERU DALAM MENGHADAPI GEMPA BUMI

Studi ini menganalisis sifat tahan gempa Meru, pagoda bertingkat di Bali, yang selama ini tetap utuh meskipun lapisan atasnya berbahan kayu dan lapisan dasarnya dilapisi dinding bata. Penelitian ini meliputi bentuk arsitektur, sistem struktur, bahan bangunan, respons dinamis, dan dampak beban angin terhadap Meru dalam menghadapi aktivitas seismik. Dengan menggunakan model Elemen Hingga 2-D dan analisis dinamika sejarah waktu non linier, Meru tingkat sebelas di Kawasan Pura Ulun Danu Batur Kintamani, Bali, dipelajari dalam konteks ketahanan gempa dan pengaruh beban angin. Studi ini mengungkap bahwa Meru mampu menghadapi gempa maksimum dengan tingkat kepercayaan untuk periode ulang 2500 tahun, sambil mengidentifikasi periode alami dan mode getar struktur. Dengan mempertimbangkan pula pengaruh beban angin, penelitian ini memberikan wawasan awal mengenai perilaku Meru dalam situasi gempa dan kondisi lingkungan yang lebih luas. Penelitian selanjutnya dapat melibatkan eksperimen untuk mengonfirmasi temuan ini, termasuk analisis komponen individu dan struktur secara keseluruhan

Pengembangan Aplikasi Website Informasi Instansi X untuk Efisiensi Pengambilan Data API dan Desain Antarmuka Responsif dengan Next.js

Perkembangan teknologi informasi telah mendorong transformasi digital di berbagai sektor, termasuk layanan publik. Salah satu wujud transformasi tersebut adalah pengembangan website yang mampu memberikan informasi dan layanan secara efisien kepada masyarakat. Website yang responsif dan mudah diakses melalui berbagai perangkat menjadi kebutuhan penting bagi instansi yang ingin meningkatkan efisiensi pelayanan. Pada kerja praktik ini, dilakukan pengembangan website informasi untuk sebuah instansi X. Fokus utama pengembangan meliputi pengelolaan pengambilan data secara efisien melalui API, penanganan error dan status loading, serta perancangan antarmuka pengguna (user interface) yang responsif. Teknologi yang digunakan adalah Next.js dan TailwindCSS untuk membangun website yang cepat dan optimal, dengan integrasi framework seperti Axios dan React Query untuk fetching data serta pengelolaan state data, React Hook Form dan Zod untuk pengelolaan validasi data. ============================================================================================================================ The development of information technology has driven digital transformation in various sectors, including public services. One form of this transformation is the development of websites that are able to provide information and services efficiently to the public. Responsive websites that are easily accessible through various devices are an important need for agencies that want to improve service efficiency. In this practical work, an information website was developed for an agency X. The main focus of the development includes efficient data retrieval management through API, error handling and loading status, and responsive user interface design. The technologies used are Next.js and TailwindCSS to build fast and optimal websites, with framework integration such as Axios and React Query for fetching data and managing data states, React Hook Form and Zod for managing data validation