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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 Sinkron : Jurnal dan Penelitian Teknik Informatika 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) Aliansi : Jurnal Manajemen dan Bisnis Jurnal Teknik Informatika (JUTIF) Jurnal AbdiMas Nusa Mandiri JPPHK (Jurnal Pendidikan Politik, Hukum Dan Kewarganegaraan) 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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Analisis Penerimaan Pengguna Kartu Top-Up di Summarecon Mall Bekasi Menggunakan Technology Acceptance Model (TAM) Rahman, Taufik; Chairudin, Muhammad Rio; Sumarna, Sumarna
Jurnal Ilmiah SINUS Vol 23, No 2 (2025): Vol. 23 No. 2, Juli 2025
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/sinus.v23i2.917

Abstract

In the digital era, electronic payment systems are increasingly developing, including the use of top-up cards in shopping centers. However, the level of acceptance and effectiveness of top-up cards in increasing transaction efficiency is still a question. This study aims to analyze the factors that influence the acceptance of the top-up card payment system at Summarecon Mall Bekasi using the Technology Acceptance Model (TAM). The research method used is quantitative by distributing questionnaires to 80 respondents who are top-up card users. Data analysis was carried out through validity and reliability tests, multiple linear regression, and hypothesis testing to test the effect of Perceived Usefulness, Perceived Ease of Use, Attitude Toward Using, and Behavioral Intention on the acceptance of top-up cards. The results showed that Perceived Usefulness had the most significant effect on the acceptance of top-up cards, followed by Behavioral Intention, while Perceived Ease of Use and Attitude Toward Using also contributed but with a smaller effect. The regression model showed that 78% of the variation in top-up card acceptance could be explained by the variables in the TAM. The conclusion of this study confirms that increasing the use of top-up cards can be done by increasing the benefits felt by users, simplifying the top-up system, and increasing socialization and education to users. The results of this study provide insights for mall managers and payment service providers in increasing transaction efficiency and encouraging the adoption of digital payment systems in modern retail environments.
OPTIMALISASI PUTUSAN HAKIM TINDAK PIDANA KORUPSI SEBAGAI UPAYA PEMBERANTASAN KORUPSI Sumarna, Sumarna; Sulistyowati, Sulistyowati; Sukresno, Sukresno
Jurnal Suara Keadilan Vol 20, No 1 (2019): JURNAL SUARA KEADILAN
Publisher : LPPM Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/sk.v20i1.5557

Abstract

Korupsi merupakan kejahatan luar biasa. Hukuman bagi pelaku tindak pidana korupsi tampaknya berseberangan dengan efek jera sebagaimana dimaksud oleh keberadaan dan tujuan hukum. Salah satu penyebabnya, dan ini yang sering jadi bahan "perbincangan publik" adalah hukuman yang dijatuhkan oleh Hakim untuk koruptor dianggap tidak sebanding dengan kejahatan luar biasa yang dilakukan  ini.          Formulasi masalah terdiri dari: Mengapa Hakim Pidana Korupsi Tidak Menjatuhkan Putusan Maksimal (Berat) Terhadap Koruptor dan Bagaimana Mengoptimalkan Keputusan Hakim Korupsi sebagai Upaya Pemberantasan Korupsi. Tujuan Penelitian ini yaitu untuk memahami dan menganalisis faktor-faktor yang menyebabkan hakim korupsi tidak membuat keputusan maksimal kepada Koruptor sebagai upaya untuk memberantas korupsi di Indonesia, serta untuk memahami dan menganalisis bagaimana mengoptimalkan keputusan Hakim tentang korupsi sebagai upaya untuk memberantas korupsi di Indonesia.          Metode Penelitian terdiri dari Pendekatan Masalah yaitu yuridis empiris, spesifikasi penelitian menggunakan penelitian deskriptif analitis, Jenis Data dalam bentuk data Primer dan data sekunder, Metode Pengumpulan Data berupa wawancara dengan Hakim korupsi, serta metode analisis data kualitatif.          Faktor yang menyebabkan Hakim Tindak Pidana Korupsi tidak memberikan putusan yang berat adalah prinsip menjatuhkan hukuman harus proporsional dengan kesalahan Tergugat, hukuman harus mencerminkan tujuan pembinaan dan tujuan pengajaran Terdakwa, yang mana Terdakwa dapat merefleksikan apa yang telah dilakukannya. Cara untuk mengoptimalkan keputusan Hakim Pidana Korupsi adalah penerapan beban pembuktian terbalik murni dalam hukum acara untuk membuktikan korupsi yang telah menggunakan beban verifikasi afirmatif. Hakim kejahatan korupsi harus dapat membedakan korupsi sebagai hal yang luar biasa, dan harus ditangani dengan cara yang luar biasa pula serta membuat keputusan maksimum terhadap koruptor untuk memberikan efek jera.
PENGEMBANGAN PERANGKAT PEMBELAJARAN MODEL TEAM GAMES TOURNAMENT UNTUK MENINGKATKAN MINAT DAN HASIL BELAJAR Chintyawati, Sindy; Sumarna, Sumarna
Jurnal Pendidikan Fisika Vol 12, No 2 (2025): Jurnal Pendidikan Fisika
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jpf.v12i2.21785

Abstract

Penelitian ini dilakukan berdasarkan permasalahan peserta didik mengenai minat belajar dan hasil belajar kognitif yang masih rendah. Tujuan dari penelitian ini adalah: 1) menghasilkan perangkat pembelajaran dengan model Team Games Tournament (TGT) yang layak untuk meningkatkan minat belajar dan hasil belajar kognitif peserta didik, (2) mendeskripsikan ada tidaknya peningkatan minat belajar peserta didik yang menggunakan perangkat pembelajaran model Team Games Tournament (TGT), (3) mendeskripsikan ada tidaknya peningkatan hasil belajar kognitif peserta didik yang menggunakan perangkat pembelajaran model Team Games Tournament (TGT).  Penelitian ini menggunakan model 4D menurut Thiagarajan yang memiliki 4 tahap: define, design, develop, dan disseminate. Jenis data pada penelitian ini adalah kualitatif dan kuantitatif. Hasil penelitian ini berupa: (1) perangkat pembelajaran dengan model pembelajaran Team Games Tournament (TGT) layak digunakan untuk meningkatkan minat belajar dan hasil belajar kognitif peserta didik dengan perolehan nilai modul ajar dan LKPD sebesar 3,6 dengan kategori sangat baik., (2) perangkat pembelajaran dengan model pembelajaran Team Games Tournament (TGT) ada peningkatan minat belajar peserta didik dengan nilai standar gain 0,3 dengan kategori sedang., (3) perangkat pembelajaran dengan model pembelajaran Team Games Tournament (TGT) ada peningkatan hasil belajar kognitif peserta didik dengan nilai standar gain 0,57 dengan kategori sedang.
DECISION TREE OPTIMIZATION IN HEART FAILURE DIAGNOSTICS: A PARTICLE SWARM OPTIMIZATION APPROACH Sumarna, Sumarna; Sartini, Sartini; Pangesti, Witriana Endah; Suryadithia, Rachmat; Riyanto, Verry
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 3 (2024): JUTIF Volume 5, Number 3, June 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.3.1815

Abstract

The rapid advancement of technology has made the implementation of accurate diagnostic methods for serious diseases like heart failure extremely important. Heart failure, being a leading cause of death worldwide, necessitates precise and accurate diagnostic techniques. The problem with conventional diagnostic methods is that they often fail to effectively accommodate the complexity of clinical data, leading to an increase in mortality rates due to heart failure. Previous research has employed various data analysis methods, but there are still fluctuations in the accuracy of results. The aim of this study is to enhance the accuracy of heart failure diagnosis by integrating the Decision Tree (DT) method with Particle Swarm Optimization (PSO) optimization. This research involves collecting and preprocessing heart failure data, followed by the development of a DT model. This model is then optimized using the PSO technique. The study uses a dataset from the UCI Repository, involving testing and validation processes to measure the model's effectiveness. The results show a significant improvement in accuracy and the Area Under Curve (AUC) after applying PSO. Accuracy increased from 79.92% to 85.29%, and AUC from 0.706% to 0.794%. The conclusion is that the integration of DT and PSO successfully improved the accuracy and reliability of the model in diagnosing heart failure. This innovation offers potential for further research in integrating optimization techniques in health data analysis, with the possibility of application in various clinical scenarios.
Combatting Heart Diseases: Advanced Predictions Using Optimized DNN Architecture Azis, Mochammad Abdul; Sumarna, Sumarna
Compiler Vol 12, No 2 (2023): November
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/compiler.v12i2.1915

Abstract

Heart disease has become a global health issue and is recorded as one of the primary causes of death in many countries. In this modern era, with rapid technological advancements and shifting lifestyles, numerous factors contribute to the increasing prevalence of heart diseases. These range from dietary habits, lack of physical activity, stress, to genetic factors. Given the complexity of this ailment, information technology plays a crucial role in providing innovative solutions. One of them is predicting the risk of heart disease, enabling more targeted early prevention and treatment interventions.Correct data analysis is pivotal in making predictions. However, a common challenge often encountered is the imbalance in data classes, which can result in a predictive model being biased. This is certainly detrimental, especially in the context of predicting strokes, where prediction accuracy can mean the difference between life and death.In this research, our focus was on developing a Deep Neural Network (DNN) Architecture model. This model aims to offer more accurate predictions by considering data complexities. By optimizing several key parameters, such as the type of optimizer, learning rate, and the number of epochs, we strived to achieve the model's best performance. Specifically, we selected Adagrad as the optimizer, set the learning rate at 0.01, and employed a total of 100 epochs in its training.The results obtained from this research are quite promising. The optimized DNN model displayed an accuracy score of 0.92, precision of 0.92, recall of 0.95, and an f-measure of 0.93. This indicates that with the right approach and meticulous optimization, technology can be a highly valuable tool in combatting heart diseases.
PENGARUH MOTIVASI KERJA TERHADAP KINERGA PEGAWAI PADA KANTOR BADAN NASIONAL PENCARIAN DAN PERTOLONGAN (BASARNAS) JAKARTA Sumarna, Sumarna; Basir, Abdul
Aliansi : Jurnal Manajemen dan Bisnis Vol 19, No 1 (2024): ALIANSI : Jurnal Manajemen dan Bisnis
Publisher : Sekolah Tinggi Manajemen IMMI Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46975/aliansi.v19i1.555

Abstract

Kondisi yang memotivasi dan mendorong semangat kerja manusia untuk melakukan aktivitas dikenal sebagai motivasi. Kondisi ini tercermin dalam upaya yang dilakukan untuk mencapai suatu tujuan. Kinerja didefinisikan sebagai tingkat pencapaian program, kegiatan, atau kebijakan dalam mencapai sasaran, tujuan, visi, dan misi organisasi. Selama proses perencanaan strategi organisasi, ini diukur. Tujuan dari penelitian ini adalah untuk menentukan seberapa besar pengaruh motivasi terhadap kinerja 60 pekerja Basarnas Jakarta. Hasil dari uji T parsial menunjukkan bahwa variabel motivasi (X) memiliki nilai t-hitung yang signifikan (p 0,1) dan nilai t-hitung sebesar 2,950 melebihi nilai ttabel sebesar 1,68385. Oleh karena itu, dapat disimpulkan bahwa motivasi secara signifikan dan positif secara parsial memengaruhi kinerja pegawai (Y). Hipotesis ini diterima. Kata Kunci : Motivasi dan Kinerja Pegawai.
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 Iwan Sopwandin Juli Astono Jumadi Jumadi Luthfianingrum, Nurhamidah Muhamad Fahmi Fauzi, Muhamad Fahmi Muhammad Amiruddin Munawar Munawar Nur Kadarisman Nurhidayah, Desy Nurjalilah, Siti Oktavia, Fuji Palahudin, Cecep Pitri, Anisa Pramastya, Ananda Bagus Purwanto, Agus Rashydny, Nabila Amina 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 Taufik Rahman Verry Riyanto WITRIANA ENDAH PANGESTI Yana Iqbal Maulana