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Technological interventions: a pathway to combatting judicial corruption Syauket, Amalia; Wijanarko, Dwi Seno; Lestari, Tyastuti Sri; Ismaniah, Ismaniah
Otoritas : Jurnal Ilmu Pemerintahan Vol 14, No 1 (2024): (April 2024)
Publisher : Department of Government Studies Universitas Muhammadiyah Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26618/ojip.v14i1.12887

This study aims to find out whether corruption in the court can be prevented with Information Technology (IT). This research uses a qualitative descriptive approach where the main data source can be processed from relevant and current literature material with the theme of this article as secondary data. Information technology is the most influential factor in changing the world today. The administration of justice is an activity that includes the provision of information, communication, and production of new information. There is no denying that information technology will affect the way justice administration works. Corruption that often occurs in courts (judicial commissions) is in the form of petty corruption, namely administrative or bureaucratic corruption with a power approach, namely the exclusive power of decision makers. The results showed that optimal use of IT can support efforts to eradicate corruption in the court by using E-Court, paperless court, E-Filing, E-Skum, E-Payment, E-Summons applications. These various applications can prevent judicial corruption due to the application of transparency principles, efficiency principles such as cost savings, reduction of illegal levies, ease of information transfer, reduction of case broker practices, reduction of opportunities for corruption due to potential conflicts of interest and face. -face-to-face, reducing gratification and bribery which are the main requirements of smart governance so that efforts to eradicate judicial corruption can be effective.

Identification of Website-Based Product Sales Frequency Patterns using Apriori Algorithms and Eclat Algorithms at Rio Food in Bekasi Pramuhesti, Salwa Nabiila; Herlawati, Herlawati; Lestari, Tyastuti Sri
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 11 No. 1 (2023): March 2023
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v11i1.5941

Sales reports that are not managed automatically may hinder businesses from accurately determining their progress in the short or long term. With increasing community needs for a product, business owners have an opportunity to market their products to a larger audience. The abundance of data highlights the need for information to produce patterns that can be used as a reference for making decisions in buying products on the website. Data mining algorithms can provide support for analysis, which can help avoid inaccurate business progress reports. In this study, the Apriori and Eclat algorithms were applied to analyze frequent itemsets in association rule mining. The dataset used in this study consists of 20 transaction data from frozen food sales. The results showed that the combination of Nugget and Chicken Sausage itemsets were the most frequent, with higher support, confidence, and lift ratio values than the others. These results can be used as product recommendations that are most in demand by customers.

Particle Swarm Optimization for Optimizing Public Service Satisfaction Level Classification Lestari, Tyastuti Sri; Ismaniah, Ismaniah; Priatna, Wowon
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 1 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i1.69612

This research aims to categorize survey data to determine the level of satisfaction with the services provided by the village government as a public service provider. Villages or sub-districts currently offer services in response to community demand, although only partially or as efficiently as possible. The data collection technique used was distributing questionnaires to the village community. The method used for classification is the machine learning method. Before the classification process, feature selection is carried out at the data pre-processing stage using Particle Swarm Optimization (PSO), which has been proven to increase the accuracy of the classification values. The classification methods employed include Decision Tree (DT), Naive Bayes, Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) algorithms for classification purposes. This study achieves the maximum level of accuracy in decision tree classification, attaining an accuracy rate of 97.74%. Subsequently, the KNN algorithm achieved an accuracy of 77.90%, the Nave Bayes algorithm achieved 64.4%, and the SVM algorithm, which yielded the lowest accuracy value, achieved 59.90%. Following the application of Particle Swarm Optimization (PSO) for optimization, the accuracy of the SVM and KNN algorithms improved to 98.3%. The Decision Tree algorithm achieved a value of 97.77%, while the Naive Bayes technique yielded a value of 69.30%.

Building Excellent Human Resources through Merdeka Belajar Kampus Merdeka in Era 5.0 Rony, Zahara Tussoleha; Widodo, Aan; Lestari, Tyastuti Sri; Saimima, Ika Dewi Sartika; Ismaniah, Ismaniah; Mursito, Kendhy
International Journal of Social Science and Business Vol. 8 No. 3 (2024): August
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/ijssb.v8i3.77185

Welcoming the era of Society 5.0, through the program "Merdeka Belajar Kampus Merdeka," universities are expected to transform the higher education system as the driving force for creating superior human resources for the nation's future. This study aims to explain the dynamics of the independent learning program activities at the independent campus across seven faculties at Bhayangkara University, Jakarta. The research adopts a post-positivist paradigm with a case study approach, involving 25 informants and five key informants. Secondary data were obtained from the Sistem Pembelajaran Daring - Kementerian Riset, Teknologi, dan Pendidikan Tinggi (SPADA DIKTI), which includes a compilation of data from students, lecturers, and education staff. Primary data were collected through interviews, observations, and documentation studies related to the implementation of the Merdeka Belajar Kampus Merdeka program. The data were analyzed descriptively using manual data analysis procedures. The results indicate that most faculties and study programs have not yet optimally explained the flow, program procedures, and complete infrastructure used in implementing the program. However, most students and lecturers acknowledge that the program is highly beneficial and critical for developing quality human resources for the future.

Crawling Engine Pada Website Mann, Baldwin, Fleetguard Dan Pengelompokan Produk Menggunakan K-Means Rahman, Andi; Priatna, Wowon; Lestari, Tyastuti Sri; Hidayat, Agus
Jurnal Pelita Teknologi Vol 19 No 2 (2024): September 2024
Publisher : Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar

Tujuan penelitian ini adalah untuk mengelompokan produk pada beberapa web site. Dalam crawling engine akan sangat membantu dalam memasukan data produk secara otomatis mengambil data dari website produk tersebut, kemudian di input dalam aplikasi Odoo. Algoritma k-means klustering sendiri adalah algoritma mengelompokkan pengamatan ke dalam kelompok k, di mana k merupakan parameter input. Tiap data kemudian ditetapkan pada setiap pengamatan cluster berdasarkan kedekatan pengamatan nilai rata-rata cluster. Pengelompokan ini akan sangat membantu dalam klasifikasi produk berdasarkan cross reference. Hasil dari penelitian ini adalah produk produk terinput secara otomatis dan data sesuai dengan website produk tersebut dan produk terkelompok sesuai dengan cross reference.

The Role of Women's Leadership on the Effectiveness of Villages owned Enterprises in Indonesia Lestari, Tyastuti Sri; Ismaniah, Ismaniah; Saimima, Ika Dewi Sartika; Nuraida, Tia
Jurnal Manajemen Pelayanan Publik Vol 9, No 3 (2025): Jurnal Manajemen Pelayanan Publik
Publisher : Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/jmpp.v9i3.52806

The population of Indonesia according to the Central Statistics Agency (BPS) in mid 2023 is 278 million people. In spite of this, women still need to make up ground in a number of developmental fields, impacting national productivity. Globally, women face similar challenges in development, prompting the United Nations to prioritize sustainable development goals (SDGs) and strive for gender equality by 2030. This research is based on the theory of transformational leadership, where transformational female leaders empower villages, create inclusivity, and advance sustainable economics Leadership issues, particularly concerning women, remain a pertinent topic. In Indonesia, where women's participation in culture is limited, the Village-Owned Enterprises (BUMDes) program emerged as a pivotal initiative by the Ministry of Villages, Development of Disadvantaged Regions, and Transmigration. BUMDes, which was established in 2014, aims to enhance community welfare by establishing legal entities managed by villages. With an important focus on women's leadership, the program has acquired prominence and has contributed significantly to the success of BUMDes, as well as to the acceleration of village towards autonomy the nation.

Technological interventions: a pathway to combatting judicial corruption Syauket, Amalia; Wijanarko, Dwi Seno; Lestari, Tyastuti Sri; Ismaniah, Ismaniah
Otoritas : Jurnal Ilmu Pemerintahan Vol. 14 No. 1 (2024): (April 2024)
Publisher : Department of Government Studies, Universitas Muhammadiyah Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26618/ojip.v14i1.12887

This study aims to find out whether corruption in the court can be prevented with Information Technology (IT). This research uses a qualitative descriptive approach where the main data source can be processed from relevant and current literature material with the theme of this article as secondary data. Information technology is the most influential factor in changing the world today. The administration of justice is an activity that includes the provision of information, communication, and production of new information. There is no denying that information technology will affect the way justice administration works. Corruption that often occurs in courts (judicial commissions) is in the form of petty corruption, namely administrative or bureaucratic corruption with a power approach, namely the exclusive power of decision makers. The results showed that optimal use of IT can support efforts to eradicate corruption in the court by using E-Court, paperless court, E-Filing, E-Skum, E-Payment, E-Summons applications. These various applications can prevent judicial corruption due to the application of transparency principles, efficiency principles such as cost savings, reduction of illegal levies, ease of information transfer, reduction of case broker practices, reduction of opportunities for corruption due to potential conflicts of interest and face. -face-to-face, reducing gratification and bribery which are the main requirements of smart governance so that efforts to eradicate judicial corruption can be effective.

Sistem E-Payroll pada Karyawan Yayasan Pendidikan Islam An-Nadwah Menggunakan Algoritma Advanced Encryption Standard (AES) Berbasis Web Fitriyani, Linda; Handayani, Dwipa; Lestari, Tyastuti Sri; Hidayat, Agus
Journal of Students‘ Research in Computer Science Vol. 6 No. 2 (2025): November 2025
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/n7qt5a13

The rapid development of information technology encourages educational institutions to improve efficiency and security in administrative management, including payroll systems. This research aims to design a web-based E-Payroll system implemented at the Islamic Education Foundation An-Nadwah by applying the Advanced Encryption Standard (AES) algorithm to ensure the confidentiality of employee salary data. The system was developed using the Rapid Application Development (RAD) method to enable fast and user-responsive development. The implementation results show that the system can effectively encrypt and decrypt salary data, as well as provide real-time and secure payroll reports. System testing using the blackbox method demonstrates that all system functionalities work as expected. This system is expected to enhance efficiency, accuracy, and security in the payroll process within the foundation.

Penguatan Infrastruktur Digital Desa Melalui Penerapan Jaringan RT/RW-Net Dan Pelatihan Pemanfaatan Aplikasi Smart Village Priatna, Wowon; Lestari, Tyastuti Sri; Rasim
Jurnal Pengabdian kepada Masyarakat UBJ Vol. 9 No. 1 (2026): January - May 2026
Publisher : Lembaga Penelitian Pengabdian kepada Masyarakat dan Publikasi Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/57zv7x35

The digital transformation of rural areas has become a national priority to improve public service efficiency and strengthen technology-based village governance. This community service program aimed to enhance the digital infrastructure of Neglasari Village, Darmaraja District, Sumedang Regency, through the implementation of an RT/RW-Net network and training on the utilization of a Smart Village application. The program involved the deployment of RT/RW-Net as the village’s digital backbone, the development of a web-based Smart Village application using the PHP Laravel framework and MySQL database, and structured training sessions for village officials, administrators, operators, and residents. The training adopted participatory and hands-on methods covering network configuration and maintenance, operation of digital administrative services such as online letter requests and complaint management, and integration of population data.The results indicate that the RT/RW-Net infrastructure operated reliably and supported the optimal performance of the Smart Village application. Training activities significantly improved the technical capacity of village officials and operators, enabling independent management of the network and application. Residents also began utilizing digital services for administrative needs, complaints, and access to population information, leading to more efficient, effective, and transparent public services. This initiative demonstrates that the integration of localized digital infrastructure and practice-oriented capacity building can serve as a sustainable and scalable model for accelerating digital transformation in rural communities. Future development should focus on expanding application features, strengthening digital literacy, and promoting data-driven village governance.

Public Sentiment Analysis on the Service Quality of PT PLN on X Using Naïve Bayes and K-Nearest Neighbor Algorithms. Zahra, Nurul; Priatna, Wowon; Lestari, Tyastuti Sri
International Journal of Information Technology and Computer Science Applications Vol. 4 No. 1 (2025): January - April 2026
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar

Quality services since electricity is a primary public need. However, numerous complaints still highlight PLN’s lack of responsiveness, especially on the X platform (formerly Twitter). This study aims to analyze public sentiment toward PLN’s service quality expressed on X and compare the performance of the Naïve Bayes and K-Nearest Neighbor (KNN) algorithms in classifying sentiments into positive, negative, and neutral categories. The research employs the Knowledge Discovery in Databases (KDD) approach, involving data collection through tweet scraping using Tweet-Harvest, preprocessing (case folding, tokenizing, filtering, stemming), transformation with TF-IDF weighting, and data mining using Naïve Bayes and KNN. Evaluation through a confusion matrix shows that Naïve Bayes achieved an accuracy of 87%, outperforming KNN with an accuracy of 86%. These findings provide insights for PLN to better understand public perception and serve as a reference for future sentiment analysis research using machine learning.

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