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All Journal JSI: Jurnal Sistem Informasi (E-Journal) Scientific Journal of Informatics Jurnal Kajian Informasi & Perpustakaan SMATIKA Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Abdimas Dewantara CAPITAL: JURNAL EKONOMI DAN MANAJEMEN REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Journal of Soft Computing Exploration Journal of Advances in Information Systems and Technology Scientific Journal of Informatics Ulil Albab Journal of Advances in Information Systems and Technology Recursive Journal of Informatics
Budiman, Kholiq
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Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Library & Information Science Social Sciences Other

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Analysis of Public Awareness of Cybercrime in The Form of Adware suprih murdyantara; Kholiq Budiman
Journal of Advances in Information Systems and Technology Vol. 6 No. 1 (2024): April
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v6i1.10769

Abstract

The development of information technology has had a big impact on human life. The impact of the development of information technology is the internet, which reaches all circles of society. The development of the internet has positive and negative impacts. The positive impact of the internet is that it helps humans get information quickly and can be reached anywhere. Meanwhile, the negative impact of the internet itself is the existence of cybercrime. There are various modes of cybercrime, one of which is the most often encountered by the public: adware-type malware, often known as malicious online advertising. The purpose of this study is to determine the factors that influence public awareness of cybercrime in adware. This research uses a quantitative method approach with sample criteria for respondents who live on Java Island with an age range of 18–45 years and actively use the internet. The data from the distributed questionnaires was processed with the partial least squares structural equation model (PLS-SSEM) using SmartPLS 4. The results obtained showed that of the 10 hypotheses that had been proposed, 8 were accepted. Based on these results, there are factors that influence public awareness of cybercrime, including the use of social media, cybercrime information and news, cybercrime law enforcement, and adware knowledge. Furthermore, adware knowledge is influenced by cybercrime information, news, and social media usage.
Optimasi Model CNN Berbasis Transfer Learning Untuk Klasifikasi Pneumonia pada Citra X-Ray Dada Pasha, Rasikh Khalil; Budiman, Kholiq
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 15 No 01 (2025): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v15i01.1985

Abstract

Pneumonia is a leading cause of child mortality worldwide, and its diagnosis often relies on chest X-ray interpretation, which is prone to human error. This study aims to optimize a Convolutional Neural Network (CNN) model based on transfer learning using the DenseNet-121 architecture for pneumonia classification in chest X-ray images. The model was trained on a Kaggle dataset consisting of two classes: Normal and Pneumonia. Preprocessing included class balancing and data augmentation. Five fine-tuning strategies were tested, ranging from training only the classifier to unfreezing the entire pretrained layers. Evaluation metrics included accuracy, precision, recall, F1-score, and ROC-AUC. Results showed that the strategy of unfreezing Block 3–4 yielded the best performance with 94.39% accuracy, 95.61% F1-score, and 98.04% ROC-AUC. This study demonstrates that selective fine-tuning strategies significantly improve classification performance compared to training only the classifier or the entire network.
Measuring the Acceptance Level of the Warehouse Module Using the Extended Unified Theory of Acceptance and Use of Technology Model Sarmini; Budiman, Kholiq
Journal of Advances in Information Systems and Technology Vol. 7 No. 1 (2025): April
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v7i1.9332

Abstract

This study aims to measure the acceptance level of the warehouse module within the ERP system implemented at CV Kalingga Keling Jati, utilizing the extended UTAUT model. The analyzed variables include performance expectancy, effort expectancy, hedonic motivation, trust, behavioral intention, use behavior, and one moderator variable, education. The results indicate that effort expectancy, hedonic motivation, trust, and behavioral intention significantly influence users' intention and behavior in utilizing the warehouse module. However, performance expectancy and the moderator variable education do not show significant influence. This research also highlights the importance of effective warehouse management systems to minimize errors in inventory management and enhance operational efficiency within the company. With the implementation of an ERP system integrated with IoT, CV Kalingga Keling Jati aims to improve user satisfaction and reduce resistance to new technologies. The findings provide insights for other companies considering similar technology adoptions in their warehouse management.Furthermore, the study emphasizes the need for continuous evaluation and adaptation of technology to align with user needs and organizational goals. By understanding user acceptance, organizations can better tailor their systems to enhance productivity and foster a positive technological environment. This study contributes to a deeper understanding of the factors influencing technology acceptance in the business context, particularly in the manufacturing sector, and offers a foundation for future system improvements.  
Penguatan agribisnis berkelanjutan komoditas durian dan kopi melalui teknologi budidaya di Desa Brongkol, Kabupaten Semarang Pujiati, Amin; Sugiantoro, Bambang; Budiman, Kholiq; Retnoningsih, Amin; Efdika, Muhamad Fadil; Izdiharsant, Almaas; Habibah, Berlian Ummu; Karmesti, Danissa Wirna; Akbar, Bintang Faisal
ABDIMAS DEWANTARA Vol 8 No 1 (2025)
Publisher : Universitas Sarjanawiyata Tamansiswa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30738/ad.v8i1.18168

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan untuk menguatkan agribisnis berkelanjutan komoditas durian dan kopi melalui teknologi budidaya di Desa Brongkol, Kabupaten Semarang. Metode pemecahan masalah dilakukan secara parsitipatif melalui aktivitas sosialisasi, pelatihan, penerapan teknologi, pendampingan, monitoring, dan evaluasi, serta keberlanjutan program di wilayah Desa Brongkol. Kegiatan pengabdian kepada masyarakat terkait dengan Penguatan Agribisnis Berkelanjutan Komoditas Durian dan Kopi Melalui Teknologi Budidaya di Desa Brongkol, Kabupaten Semarang .Kegiatan pengabdian memiliki empat kegiatan utama yaitu sosialisasi, pelatihan, penerapan teknologi, pendampingan, monitoring dan evaluasi. Adapun mitra sasaran dalam kegiatan pengabdian ini ada dua yaitu Ajuning Tani (komoditas durian) dan Kelompok Tani Karya Bakti I (komoditas kopi Robusta). Program pengabdian ini berfokus untuk mengatasi berbagai  permasalahan yang dihadapi oleh mitra antara lain permasalahan produksi, manajemen, dan pemasaran. Dari aspek produksi, permasalahan yang dihadapi meliputi kualitas bibit rendah dan produktivitas tanaman rendah. Permasalahan dari aspek manajemen yaitu rendahnya pemahaman agroforestry yang dimiliki oleh para petani dan manajemen usaha rendah. Untuk mengatasi permasalahan yang ada, kegiatan pengabdian ini memberikan solusi berupa berbagai program pelatihan meliputi pelatihan topworking dan grafting, pelatihan agroforestry berkelanjutan melalui pelatihan Good Agriculture Practice (GAP), pelatihan pembuatan pupuk dan pemupukan yang ramah lingkungan. Pelatihan dan penerapan teknologi yang dierapkan melipatkan pemerintah desa, kabupaten dan provinsi khusunya cabang dinas kehutanan III. Keterlibatan mitra sangat berperan dalam mendukung keberhasilan agribisnis berkelanjutan.   Strengthening sustainable agribusiness of durian and coffee commodities through cultivation technology in Brongkol Village, Semarang Regency   Abstract: This community service activity aims to strengthen sustainable agribusiness of durian and coffee commodities through cultivation technology in Brongkol Village, Semarang Regency. The problem-solving method is carried out in a participatory manner through socialization activities, training, technology application, mentoring, monitoring, and evaluation, as well as program sustainability in the Brongkol Village area. Community service activities are related to Strengthening Sustainable Agribusiness of Durian and Coffee Commodities Through Cultivation Technology in Brongkol Village, Semarang Regency. Community service activities have four main activities, namely socialization, training, technology application, mentoring, monitoring and evaluation. There are two target partners in this community service activity, namely Ajuning Tani (durian commodity) and Kelompok Tani Karya Bakti I (Robusta coffee commodity). This community service program focuses on overcoming various problems faced by partners, including production, management, and marketing problems. From the production aspect, the problems faced include low seed quality and low plant productivity. Problems from the management aspect are the low understanding of agroforestry owned by farmers and low business management. To overcome the existing problems, this community service activity provides solutions in the form of various training programs including topworking and grafting training, sustainable agroforestry training through Good Agriculture Practice (GAP) training, environmentally friendly fertilizer and fertilization training. Training and application of technology that is implemented folds the village, district and provincial governments, especially the III forestry service branch. The involvement of partners plays a very important role in supporting the success of sustainable agribusiness.
Efektivitas Pemanfaatan MyUNNES-Keuangan Konten Aset dalam Pengelolaan Aset PTNBH Widayat, Widi; Mundzir, Ahmad; Budiman, Kholiq
ULIL ALBAB : Jurnal Ilmiah Multidisiplin Vol. 3 No. 11: Oktober 2024
Publisher : CV. Ulil Albab Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56799/jim.v3i11.5560

Abstract

Perubahan status UNNES dari PTN BLU menjadi PTN BH dengan dasar hukum Peraturan Pemerintah Republik Indonesia Nomor 36 Tahun 2022 tentang Perguruan Tinggi Negeri Badan Hukum Universitas Negeri Semarang tertanggal 20 Oktober 2022 yang dikuti perubahan visi, misi, dan tujuan UNNES. Selain perubahan visi, misi dan tujuan juga perubahan tata kelola aset.  Pengelolan aset PTN BH UNNES dapat dikatakan mengalami kenaikan status pengelolaan aset. Kenaikan status pengelolaan ini dulu sebagai pengelola adalah Kemenkeu dengan pengguna Kemendikbudristek dan UNNES sebagai kuasa pengguna, berubah menjadi pengelola adalah tingkat universitas dan pengguna bagi anak satker di lingkungan UNNES. Perubahan kenaikan status menjadikan UNNES memiliki keleluasan besar untuk mengelola asetnya sendiri namun juga memiliki tanggung jawab besar yang harus dijalankan. Peningkatan status pengelolaan aset PTN BH UNNES harus diimbangi kemampuan sumber daya manusia yang mengelola aset dan sistem informasi yang handal sebagi sistem pembantu dalam pengelolaan aset.  Pada tahun 2017 Seksi Aset bersama DSIH melakukan pembuatan sistem My-unnes keuangan konten aset. Perubahan sistem pengelolaan aset yaitu myunnes-keuangan konten myaset unnes tentunya mempengaruhi proses kerja pengelolaan aset dalam menjalankan tugasnya sehari-hari khususnya dalam mendata dan menginventarisasi atau penatausahaan serta laporan aset yang ada di UNNES. Penerapan sistem myaset UNNES diharapkan juga dapat mempermudah dalam penyampaian informasi laporan keuangan khususnya dalam laporan aset UNNES dan penggunaannya dapat mendukung kinerja organisasi semakin baik lagi. Konten Myaset UNNES adalah sistem baru penganti siagung yang mengadopsi sistem sakti. Operator pengelola aset di unit saat ini dapat dipastikan tidak memiliki pengalaman dalam pengelolaan aset dengan sakti atau ke MyUNNES-Keuangan konten aset. Oleh karena itu diperlukan pelatihan agar pengelola aset/operator aset di unit mampu menjalankan sistem my aset tersebut dengan baik. Selain itu juga perlu ada study lebih lanjut tentang fleksibilitas sistem MyUNNES-Keuangan konten aset dalam membantu mempermudah pengelola/operator aset dalam bekerja. Pemakaian myaset akan tergantung sejauh mana kepuasan dari penguna/operator. Kepuasan ini diwujudkan dalam penilaian sejauh mana efektivitas sistem.
Integrating C4.5 and K-Nearest Neighbor Imputation with Relief Feature Selection for Enhancing Breast Cancer Diagnosis Purwinarko, Aji; Budiman, Kholiq; Widiyatmoko, Arif; Sasi, Fitri Arum; Hardyanto, Wahyu
Scientific Journal of Informatics Vol. 12 No. 1: February 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v12i1.21673

Abstract

Purpose: Breast cancer remains a significant cause of mortality among women, requiring accurate diagnostic methods. Traditional classification models often face accuracy challenges due to missing values and irrelevant features. This investigation advances the classification of breast cancer through the amalgamation of the C4.5 algorithm with K-Nearest Neighbor (KNN) imputation and Relief feature selection methodologies, thereby augmenting data integrity and enhancing classification efficacy. Methods: The Wisconsin Breast Cancer Database (WBCD) was the core reference for evaluating the proposed methodology. KNN imputation addressed missing values, while Relief selected the most relevant features. The C4.5 algorithm executed training by utilizing data segregations in the corresponding proportions of 70:30, 80:20, and 90:10, with its efficiency gauged through a range of metrics, particularly accuracy, precision, recall, and F1-score. Result: This innovative methodology achieved the highest classification accuracy of 98.57%, surpassing several existing models. Particularly noteworthy, the strategy being analyzed exhibited remarkable success relative to PSO-C4.5 (96.49%), EBL-RBFNN (98.40%), Gaussian Naïve Bayes (97.50%), and t-SNE (98.20%), demonstrating associated advancements of 2.08%, 0.17%, 1.07%, and 0.37%. These results confirm its effectiveness in handling missing values and selecting relevant features. Novelty: Unlike prior studies that addressed missing values and feature selection separately, this research integrates both techniques, enhancing classification accuracy and computational efficiency. The findings suggest that this approach provides a reliable breast cancer diagnosis method. Future work could explore deep learning integration and validation on larger datasets to improve generalizability.
Unrevealing the Role of Social Media on Online Sex Trafficking: A Case Study and Conceptual Model of Cyber Prostitution in Indonesia Usman, Sahda Armandiva; Budiman, Kholiq
Journal of Advances in Information Systems and Technology Vol 5 No 2 (2023): October
Publisher : Department of Computer Science, Faculty of Mathematics and Natural Sciences, Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v5i2.67465

Abstract

Online prostitution is an example of cybercrime which is increasingly happening in today's digital era. Even though online prostitution cases have been well documented, in Indonesia itself there is no criminal law regulation that specifically addresses prostitution cases that occur on social media. Likewise, there is a lack of research that discusses the process of how online prostitution cases can occur from start to finish and social media interventions in these cases. The average previous research only focused on law violations that occurred at the final stage or at the exploitation stage. This indirectly ignores the role of social media in the process of building trust between perpetrators and victims (trust building), the process of trading or advertising (advertising), and the process of transactions between perpetrators and potential buyers (transactions). Therefore, in this study the author will discuss the role of technology in online prostitution cases and their relationship with criminals, victims and members of the police. The research design used by the author is Research & Development Level 1. The data in this study were obtained using in-depth interviews with informants and analysed by a deductive approach adapted from Nunamaker's research. Based on the results of the data analysis that has been carried out, the author finds that the social media most used by the actors is the MiChat application as much as 44%, Facebook 26%, WhatsApp 12% and other applications as much as 18%. In addition, this research also produces a conceptual model that describes the various processes that occur in online prostitution cases and the role of each social unit and social media. The conceptual model has been tested and validated by experts using the rating scale method. Obtained a percentage value of 86.67%. The results of this assessment prove that the conceptual model created is very feasible.
Sentiment Analysis of Presidential Candidates in 2024: A Comparison of the Performance of Support Vector Machine and Random Forest with N-Gram Method Muhammad Rizki Ramadhan; Kholiq Budiman
Recursive Journal of Informatics Vol. 3 No. 1 (2025): March 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/rji.v3i1.8385

Abstract

Abstract. This paper conducts a sentiment analysis of presidential candidates in Indonesia's 2024 election using Twitter data. Utilizing the "Indonesia Presidential Candidate’s Dataset, 2024" from Kaggle, containing 8555 Twitter entries, sentiment was categorized as positive or negative. Preprocessing techniques cleaned and normalized the data, followed by labeling with the VADER lexicon. This study contributes insights into public sentiment towards presidential candidates and the effectiveness of machine learning algorithms for political sentiment analysis. Purpose: This study aims to analyze public sentiment towards presidential candidates in Indonesia's 2024 election using the N-Gram method. By employing Support Vector Machine and Random Forest algorithms, we compare their performance in sentiment analysis. Utilizing the "Indonesia Presidential Candidate’s Dataset, 2024" from Kaggle, containing 8555 Twitter data entries, we seek to provide insights into the electorate's perceptions and preferences, contributing to a deeper understanding of the political landscape during this crucial period. Methods/Study design/approach: The study uses Support Vector Machine (SVM) and Random Forest algorithms for sentiment analysis on a dataset of 8555 tweets about Indonesia’s 2024 presidential candidates. SVM, paired with TF-IDF, and Random Forest, paired with N-Gram, are used for feature extraction. The data is labeled using the Vader lexicon. Result/Findings: The study compared Support Vector Machine (SVM) with TF-IDF and Random Forest with N-Gram methods in analyzing public sentiment towards Indonesia's 2024 presidential candidates. Results showed Random Forest with N-Gram achieved 85% accuracy, outperforming SVM with TF-IDF at 82%. Novelty/Originality/Value: This study provides insights into sentiment analysis applied to the 2024 Indonesian presidential election, enhancing understanding of public sentiment dynamics. Comparing SVM with TF-IDF and Random Forest with N-Gram contributes to the field, suggesting avenues for future research such as integrating contextual information or social network analysis for deeper insights into political opinion trends.
Improving Pantun Generator Performance with Fine Tuning Generative Pre-Trained Transformers Achmat Sodikkun; Kholiq Budiman
Recursive Journal of Informatics Vol. 3 No. 2 (2025): September 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/ge6xey51

Abstract

Purpose: The study aims to address the challenges in generating high-quality pantun, an important element of Indonesian cultural heritage. Traditional methods struggle with limited vocabulary, variation, and consistency in rhyme patterns. This research seeks to enhance the performance of a pantun generator by applying fine-tuning techniques to the Generative Pre-trained Transformers (GPT) model, coupled with post-processing, and validated by linguistic experts. Methods/Study design/approach: The research involves fine-tuning the GPT model using a dataset of Indonesian pantun. The methodology includes dataset collection, data pre-processing for cleaning and adjustment, and hyperparameter optimization. The effectiveness of the model is evaluated using perplexity and rhyme accuracy metrics. The study also incorporates post-processing to refine the generated pantun further. Result/Findings: The study achieved a best perplexity value of 14.64, indicating a strong predictive performance by the model. Post-processing significantly improved the rhyme accuracy of the generated pantun to 89%, a substantial improvement over previous studies by Siallagan and Alfina, which only achieved 50%. These results demonstrate that fine-tuning the GPT model, supported by appropriate hyperparameter settings and post-processing techniques, effectively enhances the quality of generated pantun. Novelty/Originality/Value: This research contributes to the development of generative applications in Indonesian, particularly in the context of cultural preservation. The findings highlight the potential of fine-tuning GPT models to improve language generation tasks and provide valuable insights for creative and educational applications. The validation by experts ensures that the generated pantun adheres to established writing standards
Co-Authors Achmat Sodikkun Afif Amirullah Ahmad Mundzir Aji Purwinarko, Aji Akbar, Bintang Faisal Akhmad Munawar Alfat Mutoriq Ali Djamhuri Alya Aulia Nurdin Amin Pujiati Amin Retnoningsih Amirullah, Afif Arif Widiyatmoko, Arif Asharinnisa Salsabila Bambang Sugiantoro Dianti, Erika Noor Efdika, Muhamad Fadil Efrilianda, Devi Ajeng Fattah, Ahmad Maulana Malik Fitri Arum Sasi, Fitri Arum Habibah, Berlian Ummu Hartono, Rudi Haryanti, Unik Slamet Izdiharsant, Almaas Karmesti, Danissa Wirna Khoirunnisa, Oktaria Mahargjo Hapsoro Adi Muhammad Rizki Ramadhan Muhammad Wildan Yasykur Mundzir, Ahmad Nurdin, Alya Aulia Pasha, Rasikh Khalil Pertiwi, Dwika Ananda Agustina Pramesti, Pricilia Intan Pricilia Intan Pramesti Putra Perdana, Muhamad Riza Firmansyah Sarmini Satrio Ardiansyah, Adi Slamet Kafrawi suprih murdyantara Unik Slamet Haryanti Usman, Sahda Armandiva Wahyu Hardyanto Widi Widayat Widi Widayat Yahya Nur Ifriza Yogiana Marta Dewi