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All Journal NOTARIUS Jurnal Kesehatan Lingkungan indonesia Semantik Techno.Com: Jurnal Teknologi Informasi Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Abdimas PRIVATE LAW The Indonesian Accounting Review JAIS (Journal of Applied Intelligent System) Journal of Information System Journal of Development Research Sinkron : Jurnal dan Penelitian Teknik Informatika International Journal of Artificial Intelligence Research AKRUAL: Jurnal Akuntansi FENOMENA Jurnal Meta-Yuridis Voice Of Informatics Fair Value: Jurnal Ilmiah Akuntansi dan Keuangan Jurnal Pengabdian Hukum Indonesia (Indonesian Journal of Legal Community Engagement) JPHI JURTEKSI AT-TURAS: Jurnal Studi Keislaman Jurnal Ilmu Manajemen dan Akuntansi Terapan Indonesian Journal of Advocacy and Legal Services Abdimasku : Jurnal Pengabdian Masyarakat Seminar Nasional Hukum Universitas Negeri Semarang Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Jurnal Bisnis Mahasiswa An Nawawi Audito Comparative Law Journal (ACLJ) Abimanyu: Journal of Community Engagement Jurnal Multidisiplin Dehasen (MUDE) Al-Istinbath: Jurnal Hukum Islam Proceeding International Conference on Malay Identity Al-Musyrif : Jurnal Bimbingan dan Konseling Islam Managere: Indonesian Journal of Educational Management Amsir Accounting & Finance Journal JUDIKAT: Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat Kesehatan Indonesia FENOMENA: Journal of Social Science Journal of Law and Legal Reform Jurnal Pengabdian Hukum Indonesia Indonesian Journal of Advocacy and Legal Services Journal of Business and Information System
Pujiono Pujiono
Fakultas Ilmu Komputer, Universitas Dian Nuswantoro Semarang
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Effectiveness of Collaborative Governance Management of Public Complaints Based on Electronic Communication Media In Central Java Provincial Government Widianto, Dhoni; Pujiono, Pujiono; Astuti, Retno Sunu; Wijayanto, Wijayanto
Budapest International Research and Critics Institute-Journal (BIRCI-Journal) Vol 4, No 4 (2021): Budapest International Research and Critics Institute November
Publisher : Budapest International Research and Critics University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33258/birci.v4i4.3316

Abstract

This study aims to describe the effectiveness of Collaborative Governance in managing public complaints based on electronic communication media in the Central Java Provincial Government for 3 (three years, 2017, 2018, and 2019. This research method uses descriptive qualitative methods. The location of this research is in the Central Java Provincial Government conducted at the Department of Communication and Informatics of Central Java Province. The results of the study conclude that this collaboration has not been effective, such as the lack of commitment from other stakeholders outside the Central Java Provincial SKPD such as Regency/City Governments, vertical agencies, BUMN, and BUMD. Then the limited authority of the Provincial Government of Java Central to the Regency/City Government, vertical agencies, BUMN, and BUMD, resulting in the completion of follow-up on community complaints is still low.The governance of handling public complaints by stakeholders is unclear, lack of accountability and responsibility from stakeholders other than S. KPD of Central Java Province and the supervisory team has not yet been formed to control the follow-up to the handling of complaints in the field.
Pelatihan Peningkatan Kapasitas Tenant UPT Riau Science Technopark 2023 Fadrul, Fadrul; Rahman, Sarli; Yusrizal, Yusrizal; Setyawan, Onny; Chandra, Jennifer; Pujiono, Pujiono; Estu, Ahmad Zulkarnaen; Novitriansyah, Bob
JUDIKAT: Jurnal Pengabdian Kepada Masyarakat Vol 3 No 2 (2023): JUDIKAT: Jurnal Pengabdian Kepada Masyarakat
Publisher : Institut Bisnis dan Teknologi Pelita Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35145/judikat.v3i2.4048

Abstract

Di dalam praktik bisnisnya, UMKM di Indonesia menghadapi beberapa persoalan yang bisa menjadi penghambat bagi pertumbuhan bisnisnya, sehingga perlu untuk dilakukan pembinaan guna menemukan dan memberikan solusi yang mereka butuhkan, Inkubator Bisnis dan Teknologi UPT RSTP merupakan salah satu lembaga yang senantias melakukan pembinaan bagi UMKM di Provinsi Riau. Untuk Tahun 2023, Inkubator Bisnis dan Teknologi UPT RSTP telah melakukan kegiatan Pelatihan Peningkatan Kapasitas Tenant UPT Riau Science Technopark dengan menggandeng dosen-dosen dari IBT Pelita Indonesia sebagai tim tutor atau pelatih. Total terdapat 3 UMKM yang mengikuti pelatihan secara paralel, dengan tiga tema berbeda sesuai kebutuhan masing-masing UMKM. Setelah dilakukan pemaparan materi masing-masing tema, maka setiap UMKM diminta untuk melakukan praktik langsung di depan tim pelatih. Dan dari hasil evaluasi yang dilakuka pada tahap praktik, maka diketahui bahwa seluruh UMKM telah memahami dan dapat melakukan melakukan digitalisasi dan menyiapan rencana pengembangan usaha, menyusun laporan keuangan UMKM, dan melakukan digitalisasi pelaporan keuangan UMKM.
Enhancing Augmentation-Based Resnet50 for Car Brand Classification Sugiarto, Triga Agus; Soeleman, Moch Arief; Pujiono, Pujiono
(JAIS) Journal of Applied Intelligent System Vol. 8 No. 3 (2023): Journal of Applied Intelligent System
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i3.9385

Abstract

This research focuses on car classification and the use of the ResNet-50 neural network architecture to improve the accuracy and reliability of car detection systems. Indonesia, as one of the countries with high daily mobility, has a majority of the population using cars as the main mode of transportation. Along with the increasing use of cars in Indonesia, many automotive industries have built factories in this country, so the cars used are either local or imported. The importance of car classification in traffic management is a major concern, and vehicle make and model recognition plays an important role in traffic monitoring. This study uses the Vehicle images dataset which contains high-resolution images of cars taken from the highway with varying viewing angles and frame rates. This data is used to analyze the best- selling car brands and build car classifications based on output or categories that consumers are interested in. Digital image processing methods, machine learning, and artificial neural networks are used in the development of automatic and real-time car detection systems.The ResNet-50 architecture was chosen because of its ability to overcome performance degradation problems and study complex and abstract features from car images. Residual blocks in the ResNet architecture allow a direct flow of information from the input layer to the output layer, overcoming the performance degradation problem common in neural networks. In this paper, we explain the basic concepts of ResNet-50 in car detection and popular techniques such as optimization, augmentation, and learning rate to improve performance and accuracy. in this study, it is proved that ResNet has a fairly high accuracy of 95%, 92% precision, 93% recall, and 92% F1-Score.
Utilization Of Principal Component Analysis To Improve Emotion Classification Performance In Text Using Artificial Neural Networks Afrad, Mahazam; Muljono, Muljono; Pujiono, Pujiono
(JAIS) Journal of Applied Intelligent System Vol. 9 No. 1 (2024): Journal of Applied Intelligent System
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jais.v9i1.9923

Abstract

Emotions, being transient and variable, differ across locations, times, and individuals. Automatic emotion identification holds significant importance across various domains, such as education and business. In education, emotional analysis contributes to intelligent electronic learning environments, while in business, it aids in assessing customer satisfaction with products. This study advocates the application of Principal Component Analysis (PCA) to enhance the performance of text emotion classification using the Artificial Neural Network (ANN) method. PCA, a pattern identification method, reduces text dimensions, improving the classification process by determining word similarities. PCA offers the advantage of dimension reduction without compromising information integrity. The classification approach involves two stages: one after PCA dimension reduction and the other without PCA post TF-IDF stage. The study's conclusive findings, incorporating PCA in ANN classification, demonstrated a notable increase in recall for the happy class, reaching 0.92 compared to the pre-PCA score of 0.91. Furthermore, precision in the sadness class improved to 0.90, surpassing the pre-PCA precision of 0.80. This affirms the efficacy of integrating PCA in enhancing the accuracy and performance of emotion classification in text analysis.
RECRUITMENT AND SELECTION: UNDERSTANDING THE SCHOOL'S STRATEGY IN REALIZING SUPERIOR EDUCATIONAL STAFF PERFORMANCE Pujiono, Pujiono; Yetri, Yetri; Amiruddin , Amiruddin
Managere: Indonesian Journal of Educational Management Vol. 4 No. 2 (2022): Mei-Agustus
Publisher : Perkumpulan Manajer Pendidikan Islam (PERMAPENDIS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (390.456 KB) | DOI: 10.52627/managere.v4i2.110

Abstract

This study aims to analyze the strategy of recruitment and selection of teaching staff in order to achieve the goals of the institution. The method used in this study is a qualitative descriptive method, which describes existing phenomena. As for data collection techniques using observation, interviews and document study. Researchers conducted interviews with school principals, deputy principals, chairs and secretaries of the Muhammadiyah Elementary and Middle Education Council (MPDM) in Metro City. The results of the study show that the strategy for recruiting and selecting educators has been good. This recruitment activity begins with planning the needs of educators, namely by analyzing the needs of existing teachers, announcement of vacancies for educators, requirements that must be met by prospective educators, selection with various tests, interviews and determining teacher acceptance. The strategy used can be said to be effective for schools, this is proven by the very good quality of teaching staff obtained as expressed by the principal as the executor and decision maker in teacher recruitment activities.
Manajemen laba model jones dimodifikasi dan arus kas operasi terhadap keputusan investasi pada sektor aneka industri di BEI setelah implementasi IFRS Alik Katur Rofiah, Binti; Pujiono, Pujiono
Fair Value: Jurnal Ilmiah Akuntansi dan Keuangan Vol. 4 No. 11 (2022): Fair Value: Jurnal Ilmiah Akuntansi dan Keuangan
Publisher : Departement Of Accounting, Indonesian Cooperative Institute, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (347.53 KB) | DOI: 10.32670/fairvalue.v4i11.1798

Abstract

The purpose of this examination was to the benefits of accounting information in the form of earnings management and operating cash flow on investment decisions. One of the benchmarks in the consideration of investment decisions is the value of the enterprise which can be seen in its share price. The category of research used is quantitative using secondary data in the form of pool data. Companies used as research objects are in the different industrial sectors listed on the IDX after the implementation of IFRS. The data needed are financial statement data and company stock price data by using research is multiple linear regression. After testing the hypothesis, it shows that earnings management has no effect on the company's stock price, but operating cash flow affects the company's stock price. It shows that the financial statement information is useful for investors. This research suggests that further research should use companies whose data variance is not too high and classify companies that have positive and negative earnings management values so that results can be more informative in making an investment determination.
Requirements for Application for Cancellation of Peace and Analysis of Decision Concerning Cancellation of Peace Firdaus, Gilbert; Sulistianingsih, Dewi; Pujiono, Pujiono
Audito Comparative Law Journal (ACLJ) Vol. 4 No. 3 (2023): September 2023
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/aclj.v4i3.28838

Abstract

This writing intends to examine the judge’s ruling on the terms of the peace annulment application. The key focus and main objective of the Suspension of Debt Payment Obligations revolves around the Settlement process, aiming to achieve a peace proposal in accordance with Article 281 of the Bankruptcy and Postponement of Debt Payment Obligations Law, commonly referred to as Law Number 37 of 2004. This occurs within the framework of the Commercial Court's management of the Suspension of Debt Payment Obligations case. If the debtor fails to keep their promise or fulfill the terms of the peace agreement, there is a legal solution to request the annulment of the peace. This research employs a normative juridical method with a descriptive-analytical approach to comprehensively and deeply describe the circumstances or symptoms studied in relation to the conditions for peace annulment applications and the application of these conditions to Decision Number 2/Pdt.Sus-Cancellation of Peace/2023/PN.Niaga Sby Jo. Number 69/Pdt.Sus-PKPU/2020/PN.Niaga Sby. It can be analyzed from the research that the regulations for requesting the annulment of a peace agreement are already established in Law Number 37 of The Year 2004.  Article 170, along with Article 171 and Article 291 of the same law, forms the legal basis for the request, specifically addressing issues related to bankruptcy and the postponement of debt payment obligations.  
Exploiting Silhouette Principle Component For Dimension Reduction In Breast Ultrasound Images Classification Kartikadarma, Etika; Fanani, Ahmad Zainul; Pujiono, Pujiono; Affandy, Affandy; Wulandari, Sari Ayu
International Journal of Artificial Intelligence Research Vol 8, No 1 (2024): June 2024
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v8i1.1165

Abstract

This paper proposes the use of the Dimensional Reduction method with the Silhouette Principle Component (SPC) Approach to improve the classification of breast ultrasound images. The PCA method is used to reduce the dimensions of medical images to improve classification, with MobileNet-v2 and DenseNet-121 as the optimal classification algorithm choices. The results show that the SPC method succeeded in producing efficient feature representation with data sizes that are almost the same as the original data, while PCA produces greater dimensionality reduction. The SPC model also shows the best performance in terms of accuracy and loss. This research makes a significant contribution to the development of more sophisticated and efficient medical image analysis techniques to support the diagnosis and treatment of breast cancer.
Legal Reform of Artificial Intelligence's Liability to Personal Data Perspectives of Progressive Legal Theory Junaidi, Junaidi; Pujiono, Pujiono; Fadzil, Rozlinda Mohamed
Journal of Law and Legal Reform Vol. 5 No. 2 (2024): Justice and Law Reform in Various Perspectives
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jllr.vol5i2.3437

Abstract

Advances in technology help people carry out their activities more easily. One of them is artificial intelligence which is used in various fields. However, the use of Artificial Intelligence has a negative impact, such as the emergence of Artificial Intelligence actions that violate ethics, legal regulations, or harm other parties that must be accounted for. The purpose of the research is to find out the legal liability of Artificial Intelligence for misuse of personal data based on progressive legal theory and the protection of personal data against the use of Artificial Intelligence based on Law Number 27 of 2022. The research method used normative legal research focuses on active legal inventories, legal principles and doctrines, legal discovery in specific cases, legal systems, levels of uniformity, comparative law and legal history. The research found that the use of Artificial Intelligence in collecting and analysing personal data can threaten individual privacy. Indonesia already has Law Number 27 of 2022 concerning Personal Data Protection, for the application and implementation of the law there is no governing Government Regulation, so that the legal protection provided is still not optimal. For this reason, it is necessary to have laws and regulations that specifically regulate the use of Artificial Intelligence, so that violations of the law that result in losses due to the use of Artificial Intelligence that can collect and analyse personal data can be held legally responsible.
Parameter Testing on Random Forest Algorithm for Stunting Prediction Mubarok, Ahmad Hasan; Pujiono, Pujiono; Setiawan, Dicky; Wicaksono, Duta Firdaus; Rimawati, Eti
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 1 (2025): Research Article, January 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.14264

Abstract

Stunting is a significant public health problem, especially in developing countries like Indonesia. It is often caused by chronic malnutrition in the first 1,000 days of life, which can impact a child's physical growth and cognitive development. To find risk factors and find effective solutions, data analysis was conducted by utilising machine learning to predict stunting. This research uses the Random Forest algorithm with a focus on setting parameters such as n_estimators, max_depth, and the number of features to optimise model efficiency and accuracy. Using the 2023 Indonesian Health Survey data consisting of 25,800 data, this study managed to get the highest accuracy of 91.65% by a combination of Random Forest with parameter settings n_estimators 200, max_depth 30, and Synthetic Minority Oversampling Technique (SMOTE). Despite the high accuracy results, there are limitations such as potential noise coming from synthetic data from SMOTE and the limited number of features analysed. It is hoped that this research can contribute to the field of machine learning model development that is practically used to predict stunting, and support the government's efforts to reduce the stunting prevalence rate to 14% as targeted. This model also provides strategic insights for policy makers to design more effective data-driven interventions, which can help in decision making.
Co-Authors A.A. Ketut Agung Cahyawan W Adhe Irham Thoriq Affandy Affandy Ahmad Zainul Fanani Aini, Triska Rahmatul Aisyaturrahmi Al Azhar, Cahya Mutiara Alik Katur Rofiah, Binti Alwani, Alwani Amiruddin , Amiruddin Andry Setiawan, Andry Anugroho, Rohmat Aprila, Bord Nandre Arif Hidayat Arif Widagdo Asih Rohmani Budi Haryanto Budiono Budiono Busriyanti Busriyanti, Busriyanti Cantika Sari Siregar Chamdan, Umar Chandra, Jennifer Chusnia, Vina Maulidah Dewi Sulistianingsih Diah Restu Wardani Diah Restu Wardani Dian Anita Nuswantara Edi Noersasongko Eka Putri, Libryawati Elanda Fikri Estu, Ahmad Zulkarnaen Eti Rimawati Etika Kartikadarma Fadrul, Fadrul Fadzil, Rozlinda Mohamed Fahmi Amiq Fatihul Barokah Firdaus, Gilbert Fitriyani Fitriyani Fransisca, Luciana Freza Surya Asrina Herdhianta, Dhimas Heri Susanto Hernawan Hadi Heru Agus Santoso Imam Bukori Indriani, Azizah Defi Irianti, Lingga Resvita Irma Cahyaningtyas, Irma Istiyanti, Istiyanti Iwan Hermawan Junaidi Junaidi Jutono Gondohanindijo Kahar Kahar, Kahar Kusharyanti Kusharyanti Lazuardi, Afried Lintang Venusita Lubis, Lubis Bambang Purnama Made Dudy Satyawan Mahazam Afrad Marita Marita, Marita Martitah Martitah Mimelientesa Irman Moch Arief Soeleman Moch Arief Soeleman, Moch Arief Moch. Eko Rustiyono Mubarok, Ahmad Hasan Muchammad Shidqon Prabowo Muhamad Haris Zuhri Muljono Muljono Muljono, - Mursalim Nasution, Khairina Nofriza, Eri Noor Ageng Setiyanto, Noor Ageng Nova Rijati Novida, Irma Novitriansyah, Bob Nurhayati Sitorus NURUL HIDAYAH prabawa, randy aditya Pramana, Hendri Julian Pratama, Arfian Nanda Yogi Pulung Nurtantio Andono Purwanto Purwanto Putra, Tegar Islami Putro, Bagus Prindo Sugihartono R Arief Nugroho Rahman, Fathor Rahman, Sarli Rangkuti, Rahmadsyah Ravindo, Besky Pramudya Refky Fielnanda Retno Sunu Astuti Ridha Rahmawati Rini Fidiyani Romi Ilham, Romi Roy Aprianto, Roy Sahbar, Robi Sahninda, Berian Putra Sari Ayu Wulandari Septian Enggar Sukmana Setiawan, Dicky Setyawan, Onny Siti Muslifah, Siti Slamet Sumarto Soeleman, M Arief Solichul Huda Somad, Agus Sri Astuti Sri Slamet Mulyati, Sri Slamet SUGIARTO, LAGA Sugiarto, Triga Agus Sugito - Suharnawi Suharnawi Suharnawi Syahputra, Hidayat Syaiful A. Septemuryantoro Teguh Budi Prijanto, Teguh Budi Ujang Nurjaman, Ujang Wahyudi, Payzar Wicaksono, Duta Firdaus Widianto, Dhoni WIJAYANTO WIJAYANTO Yetri Hasan Yolanda, Oppie Yudistira, Ivan Bhakti Yuli Prasetyo Adhi Yuliana, Dhea Arsinta Yundari, Yundari Yusrizal Yusrizal