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All Journal INOTEKS : Jurnal Inovasi Ilmu Pengetahuan, Teknologi, dan Seni BERKALA FISIKA POSITRON Jurnal Sains Dasar TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Penelitian Hutan dan Konservasi Alam Proceeding of the Electrical Engineering Computer Science and Informatics Pembaharuan Hukum Sinkron : Jurnal dan Penelitian Teknik Informatika RABIT: Jurnal Teknologi dan Sistem Informasi Univrab ATIKAN Jurnal Pengabdian Masyarakat MIPA dan Pendidikan MIPA Jurnal Pertahanan : Media Informasi tentang Kajian dan Strategi Pertahanan yang Mengedepankan Identity, Nasionalism dan Integrity Compiler Jurnal Ilmiah Sinus Jurnal Suara Keadilan JSAI (Journal Scientific and Applied Informatics) Academia Praja : Jurnal Ilmu Politik, Pemerintahan dan Administrasi Publik Aliansi : Jurnal Manajemen dan Bisnis The World of Public Administration Journal Jurnal Teknik Informatika (JUTIF) Jurnal AbdiMas Nusa Mandiri JPPHK (Jurnal Pendidikan Politik, Hukum Dan Kewarganegaraan) QISTINA: Jurnal Multidisiplin Indonesia Jurnal Pendidikan Fisika Jurnal Ilmu Fisika dan Terapannya (JIFTA)
Sumarna Sumarna
Jurusan Pendidikan Fisika, Universitas Negeri Yogyakarta, Jl. Colombo No. 1, Yogyakarta
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The Influence of Legal Literacy and Law Enforcement Effectiveness on Cybercrime Prevention Sumarna, Sumarna
Jurnal Pembaharuan Hukum Vol 12, No 3 (2025): Jurnal Pembaharuan Hukum
Publisher : UNISSULA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26532/jph.v12i3.49118

Abstract

This study examines the influence of legal literacy and law enforcement effectiveness on the prevention of cybercrime. As cybercrimes increasingly pose threats to individuals, organizations, and governments worldwide, understanding how legal awareness and the effectiveness of law enforcement mechanisms contribute to mitigating these crimes is crucial. The study uses a quantitative research design, with data collected from 300 respondents, including internet users and 50 law enforcement officers in Indonesia. The results indicate that higher legal literacy significantly correlates with better cybercrime prevention, as individuals with greater legal awareness are more proactive in protecting themselves online. Furthermore, the study finds that effective law enforcement, characterized by timely responses and adequate training for officers, plays a vital role in reducing cybercrime. The regression analysis confirms that both legal literacy and law enforcement effectiveness positively influence cybercrime prevention. Based on these findings, the study recommends enhancing legal education and improving law enforcement training to create a more secure digital environment. The study provides valuable insights for policymakers and law enforcement agencies to develop comprehensive strategies for cybercrime prevention, emphasizing the need for improved public legal awareness and stronger institutional capabilities.
A Statistical Benchmarking of Imbalance-Aware Ensemble Models for Cervical Cancer Prediction Sumarna, Sumarna; Astrilyana, Astrilyana; Sugiono, Sugiono; Wijaya, Ganda; Desvia, Yessica Fara
Sinkron : jurnal dan penelitian teknik informatika Vol. 10 No. 2 (2026): Article Research April, 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v10i2.15995

Abstract

Cervical cancer remains one of the leading causes of cancer-related mortality among women worldwide, particularly in developing countries. Early prediction through machine learning has the potential to support clinical decision-making; however, cervical cancer datasets often suffer from severe class imbalance, which reduces the ability of conventional models to correctly detect minority cases. This study aims to improve minority class detection in cervical cancer prediction by evaluating several imbalance-aware ensemble learning approaches. The proposed study compares five models, namely Random Forest (RF), SMOTE combined with Random Forest (SMOTE+RF), Balanced Random Forest (BRF), EasyEnsemble, and RUSBoost. The models were evaluated using 5-fold cross-validation with performance metrics including accuracy, recall, F1-score, and Area Under the Curve (AUC). Statistical validation was conducted using the Friedman test, followed by the Wilcoxon signed-rank test and Kendall’s W effect size analysis to assess the significance and magnitude of performance differences. Unlike prior studies that primarily focus on performance improvement, this study introduces a statistically rigorous comparative evaluation to assess both significance and practical effect of imbalance-aware ensemble methods. Experimental results show that imbalance-aware ensemble methods significantly improve minority detection compared to the baseline RF model. In particular, BRF achieved the highest AUC of 0.9469 with improved recall stability, while RUSBoost produced the highest F1-score of 0.7451. Although the Friedman test indicated no statistically significant difference among models (p = 0.2037), the Kendall’s W value of 0.297 suggests a small-to-moderate practical effect. These findings indicate that imbalance-aware ensemble learning can enhance the robustness of cervical cancer prediction models, particularly for minority class detection. The results highlight the importance of incorporating imbalance-handling strategies in medical prediction systems and suggest potential directions for future research in improving diagnostic decision-support models.
RANCANG BANGUN PENALA GITAR OTOMATIS BERBASIS ARDUINO DENGAN FAST FOURIER TRANSFORM SEBAGAI DETEKSI NADA Alfatika, Friska; Sumarna, Sumarna
Jurnal Ilmu Fisika dan Terapannya Vol 13, No 1 (2026): Jurnal Ilmu Fisika dan Terapannya (JIFTA)
Publisher : Prodi Fisika, Departemen Pendidikan Fisika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jifta.v13i1.25675

Abstract

Penelitian ini bertujuan untuk merancang-bangun penala senar gitar otomatis berbasis Arduino dan motor servo dengan fast fourier transform sebagai deteksi frekuensi nada, menguji tingkat akurasi dari sistem pengukur frekuensi yang digunakan dalam penala, dan menguji keseluruhan alat yang telah dibuat untuk mengetahui performanya. Penelitian terbagi menjadi tiga tahap, yaitu perancangan, perakitan, dan pengujian alat. Mikrofon elektret sebagai sensor yang menerima sinyal suara dan mengubahnya menjadi sinyal listrik. Rangkaian pengondisi sinyal menguatkan dan memfilter frekuensi sinyal mikrofon. Arduino menganalisis sinyal menggunakan algoritma fast fourier transform (FFT) untuk mendapatkan nilai frekuensi. Motor servo memutar peg gitar untuk menyesuaikan tegangan atau frekuensi senar. Arah rotasi motor servo dikontrol oleh Arduino setelah frekuensi terukur hasil FFT dibandingkan dengan frekuensi penyetelan standar gitar yang menjadi set point. Penelitian telah menghasilkan sebuah sistem yang mengatur tegangan senar gitar secara otomatis. Hasil pengujian menunjukkan bahwa pengukuran frekuensi menggunakan algoritma FFT pada Arduino mempunyai tingkat akurasi sebesar 99,82%. Sistem penala otomatis dapat melakukan penyetelan senar dengan eror tertinggi sebesar 1,2 hertz (senar 4 ) dan terendah 0,1 hertz (senar 1) dengan waktu penyetelan (settling time) cenderung linier terhadap frekuensi awal senar, yaitu semakin jauh frekuensi awal dari set point, maka penyetelan semakin lama.
Implementation of Military Incident Management System in Disaster Management in Indonesia Amiruddin, Muhammad; Saragih, Herlina Juni Risma; Aritonang, Sovian; Sumarna, Sumarna
Jurnal Pertahanan: Media Informasi tentang Kajian dan Strategi Pertahanan yang Mengedepankan Identity, Nasionalism dan Integrity Vol 10, No 2 (2024)
Publisher : The Republic of Indonesia Defense University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33172/jp.v10i2.19515

Abstract

Indonesia’s success in disaster management cannot be separated from the military’s role. The military plays a strategic role by mobilizing military resources on a massive scale through the military command system. However, the ability of Indonesian Army (TNI AD) soldiers and organizations, in general, is considered to have limited capabilities specifically for personnel handling natural disasters. This research aims to map the disaster management implemented by the Indonesian Army in disaster response through the Incident Management System. Data collection was conducted interactively through qualitative methods with in-depth interviews with the Indonesian Army’s Supply and Transportation Unit (Pusbekangad). The research results show that the Indonesian Army (TNI AD) has competent resources in disaster response, involving the Indonesian Army’s Supply and Transportation Unit, which has primary skills and capabilities in logistics and transportation. These capabilities are facilitated by the Incident Management System, which is structured, systematic, and well-organized. The Incident Management System built by the Indonesian Army involves an incident commander, operation section, planning section, logistics section, finance/administration section, driver section, and the cooking team as a trained, capable, experienced, and ready-to-deploy ad-hoc organization in all operational areas. Indonesian Army uses the Incident Management System to respond to disasters such as earthquakes in Cianjur, South Kalimantan floods, and West Sulawesi floods. The Incident Management System serves 
Co-Authors Abdul Basir Aditya Wisnugraha Sugiyarto Agus Maman Abadi AGUS PURWANTO Agustika, Dyah Kurniawati Agustika, Dyah Kurniawati Alfatika, Friska Anggiyani Ratnaningtyas Eka Nugraheni Arfianto, Muhammad Eka Kevin Aritonang, Sovian Astono, Juli Astrilyana Astrilyana, Astrilyana Azis, Mochammad Abdul Chairudin, Muhammad Rio Chintyawati, Sindy Dadan Rosana Desvia, Yessica Fara Dina Dina Dina Indriyani Fattya Ariani Felix Wuryo Handono Ganda Wijaya, Ganda Hafis Nurdin Hapsoh, Siti Ilham Fajar Suhendar Insih Wilujeng Iwa, Jatmika Iwan Sopwandin Juli Astono Jumadi Jumadi Lina Miftahul Jannah Luthfianingrum, Nurhamidah Melani Melani Muhamad Fahmi Fauzi, Muhamad Fahmi Muhammad Amiruddin Munawar Munawar Nibras, Iqbaluz Zain Nur Kadarisman Nurhidayah, Desy Nurjalilah, Siti Oktavia, Fuji Palahudin, Cecep Pitri, Anisa Pramastya, Ananda Bagus Purwanto, Agus Rashydny, Nabila Amina Riki, Wicaksono Aditya Saragih, Herlina Juni Risma Sartini Sartini Sofwan, Prima Yuana Subaryanto Subaryanto, Subaryanto Sugiono, Sugiono Suharjanto, David Sukresno Sukresno Sulistyowati Sulistyowati Suparwoto Suparwoto Supriadi, Riki Suryadithia, Rachmat Susatijo, Gatot Tasdik, Tasdik Taufik Rahman Thomas Thomas Verry Riyanto WITRIANA ENDAH PANGESTI Yana Iqbal Maulana Yayat Sudrajat