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All Journal JURNAL SAINS PEMASARAN INDONESIA ELKHA : Jurnal Teknik Elektro Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Althea Medical Journal Journal The Winners Prosiding SNATIF Jurnal Pamator : Jurnal Ilmiah Universitas Trunojoyo Madura Scientific Journal of Informatics Pedagogik : Jurnal Ilmiah Pendidikan dan Pembelajaran Fakultas Tarbiyah Unversitas Muhammadiyah Aceh Jurnal Kedokteran ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Jurnal Deformasi PROtek : Jurnal Ilmiah Teknik Elektro Jurnal Penelitian Karet Sistemasi: Jurnal Sistem Informasi Mimbar Agribisnis: Jurnal Pemikiran Masyarakat Ilmiah Berwawasan Agribisnis Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JPPUMA: Jurnal Ilmu Pemerintahan dan Sosial Politik Universitas Medan Area AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat Jurnal Geografi IT JOURNAL RESEARCH AND DEVELOPMENT Indonesian Journal of Artificial Intelligence and Data Mining JEPA (Jurnal Ekonomi Pertanian dan Agribisnis) INOVTEK Polbeng - Seri Informatika Jurnal Organisasi Dan Manajemen Jurnal Laut Khatulistiwa Jurnal Ulul Albab Scientific Journal of Reflection : Economic, Accounting, Management and Business SEIKO : Journal of Management & Business Martabe : Jurnal Pengabdian Kepada Masyarakat Jurnal Kebijakan Perikanan Indonesia Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal RESISTOR (Rekayasa Sistem Komputer) Patria Artha Technological Journal Jurnal Kreativitas PKM Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal JURNAL AGRICA Jurnal Rekayasa Hijau Dewa Ruci : Jurnal Pengkajian dan Penciptaan Seni Gelar : Jurnal Seni Budaya JTP - Jurnal Teknologi Pendidikan JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Sehat Mandiri EDUMATIC: Jurnal Pendidikan Informatika Journal Of Management Science (JMAS) Jurnal Fokus Elektroda : Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali Jurnal Review Pendidikan dan Pengajaran (JRPP) Poltekita : Jurnal Ilmu Kesehatan Jurnal Teknologi Informasi dan Pendidikan Building of Informatics, Technology and Science Syntax Idea Diligentia: Journal of Theology and Christian Education Titian: Jurnal Ilmu Humaniora Agro Bali: Agricultural Journal Jurnal Vokasi Management Studies and Entrepreneurship Journal (MSEJ) Jurnal Industri Kreatif dan Kewirausahaan Abdi Laksana : Jurnal Pengabdian Kepada Masyarakat BERNAS: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Informatika (JUTIF) JURNAL ABDIMAS TRIDHARMA MANAJEMEN Tax Literacy and Leadership Agility: Indigenous Peoples Awareness in Paying Taxes Fokus Elektroda: Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali) Jurnal Pendidikan dan Teknologi Indonesia Jurnal Perak Malahayati : Pengabdian Kepada Masyarakat Jurnal Abdimas Bina Bangsa Jurnal Pengabdian Masyarakat Nusantara Jurnal Agristan Jurnal Ekonomi Humantech : Jurnal Ilmiah Multidisiplin Indonesia Indonesian Collaboration Journal of Community Services (ICJCS) Prosiding Konferensi Nasional PKM-CSR Jurnal Minfo Polgan (JMP) Jurnal Ilmiah Management Agribisnis (Jimanggis) TRILOGI: Jurnal Ilmu Teknologi, Kesehatan, dan Humaniora Tameh : Journal of Civil Engineering Jurnal Pengabdian Masyarakat Tjut Nyak Dhien Asian Journal of Healthcare Analytics CONSEN: Indonesian Journal of Community Services and Engagement International Journal of Educational Research Excellence (IJERE) Jurnal Smart Hukum (JSH) Experimental Student Experiences TELL - US JOURNAL Jurnal Kebidanan, Keperawatan dan Kesehatan (J-BIKES) Jurnal Pendidikan dan Pengabdian Masyarakat Jurnal Pengabdian Masyarakat Bangsa Jurnal Manajemen Sistem Informasi Jurnal Pelangi Linguistika Kultura: Jurnal Linguistik Sastra Berdimensi Cultural Studies Jurnal Ilmiah Multidisiplin Indonesia JIM: Jurnal Ilmiah Mahasiswa Pendidikan Sejarah Jurnal Edukasi Pengabdian Masyarakat: EDUABDIMAS Jurnal Pengabdian Masyarakat dan Riset Pendidikan Baileo: Jurnal Sosial Humaniora Journal of Community Services: Sustainability and Empowerment Jurnal Menara Pengabmas Jurnal Kesehatan Lingkungan Mandiri Jurnal Keadaban: Jurnal Sosial dan Humaniora Jurnal Wasatiyah: Jurnal Hukum JTPPm (Jurnal Teknologi Pendidikan dan Pembelajaran) : Edutech and Intructional Research Journal CSRID Masile:Jurnal Studi Ilmu Keislaman Media Penelitian dan Pengembangan Kesehatan Elementary Education Research Sahur Journal JIM Sendratasik
Lindawati Lindawati
Program Studi Kepemerintahan, Fakultas Ilmu Sosial dan Ilmu Politik Universitas Medan Area
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Journal : Building of Informatics, Technology and Science

 1 
Komparasi Algoritma Neural Network dan K-Nearest Neighbor Dalam Mendeteksi Malware Android Ramadhan, Andi; Lindawati, Lindawati; Rose, Martinus Mujur
Building of Informatics, Technology and Science (BITS) Vol 5 No 1 (2023): June 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i1.3538

Abstract

The report from the State Cyber and Cryptography Agency (BSSN) recorded approximately 100 million cases of cyber attacks in Indonesia until April 2022, with ransomware and malware being the most commonly detected types of attacks. In this context, the increasingly sophisticated and hard-to-detect Android malware poses a serious threat, especially with successful penetrations into the Google Play Store. Therefore, early detection of Android malware is crucial. This research aims to compare the performance of two machine learning algorithms, Neural Network and K-Nearest Neighbors (KNN), in detecting malware on the Android platform. The dataset has been processed and divided into training and testing data. Both algorithms are trained using the training data, and their results are validated and evaluated. The research findings show that Neural Network achieves the best performance with an accuracy of 97%, precision of 97%, recall of 97%, and F1-score of 97%. Meanwhile, KNN performs slightly lower with an accuracy of 95%, precision of 96%, recall of 95%, and F1-score of 95%. In conclusion, Neural Network outperforms KNN in detecting Android malware based on accuracy and classification consistency. Further research suggestions involve the use of other algorithms, broader and more representative datasets, as well as the addition of features and parameter optimization. This research contributes to the development of accurate and effective solutions for detecting and identifying potentially harmful Android applications
Pengembangan Algoritma Convolutional Neural Networks (CNN) untuk Klasifikasi Objek dalam Gambar Sampah Putri Vandalis, Yoke Annisa; Soim, Sopian; Lindawati, Lindawati
Building of Informatics, Technology and Science (BITS) Vol 6 No 2 (2024): September 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i2.5585

Abstract

Waste is a serious issue facing the world today, with increasing human activity and global economic growth. One important step in waste management is the classification process, which aims to separate types of waste based on their characteristics so they can be recycled, processed, or disposed of properly. Previous research has shown that Convolutional Neural Networks (CNN) are effective algorithms for multi-class classification. Therefore, this study develops an optimized CNN model for automatic waste classification, with a primary focus on improving accuracy through modifications to the CNN architecture. The dataset used consists of 17,366 waste images from various sources, which are then divided into training and testing data after undergoing preprocessing to ensure good data quality before training the model. However, one of the main challenges in developing a CNN model for multi-class classification is the risk of difficulty in learning class features, especially when the model is faced with too many classes. To address this issue, this study implements a strategy by adding convolutional layers to the CNN architecture. This method aims to deepen the network to capture more complex features from the given data, which in turn can improve the model's generalization to new data. Evaluation results show that the modified CNN model achieved a training accuracy of 88% after 40 epochs, with a testing accuracy of around 83%. This research not only contributes to the development of more advanced automatic waste classification technology but also provides a strong foundation for further research in this field. With increased waste management effectiveness, it is hoped to have a positive impact on the environment and public health as a whole..
Analisis Deteksi Mata Kantuk Di Wajah Pengemudi Menggunakan Support Vector Machine (SVM) Berbasis Citra Real-Time Maharani, Ullya Dwi; Handayani, Ade Silvia; Lindawati, Lindawati
Building of Informatics, Technology and Science (BITS) Vol 6 No 2 (2024): September 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i2.5701

Abstract

Traffic accidents in Indonesia are a serious issue with a high number of fatalities, and one of the main causes is microsleep, which is a brief moment of sleep while driving. To address this problem, this research has developed a sleePIness detection system based on the Internet of Things (IoT) using a Raspberry PI and a webcam, utilizing the Support Vector Machine (SVM) algorithm. The system is designed to detect the driver’s eye condition and provide a warning through a buzzer if the eyes are closed for more than 3 seconds. The research results indicate that the SVM model with a polynomial kernel has a training accuracy of 85.04%, demonstrating its ability to classify eye data into "opened" and "closed" categories. Evaluation with various SVM kernels, including linear, radial basis function (RBF), and polynomial, shows that the polynomial kernel performs the best with an accuracy of 85%, precision of 86%, and recall of 85% in detecting closed eyes. Although the system is effective in real-time detection of driver sleePIness, challenges remain with lighting conditions and camera positioning. Further testing is needed to improve the reliability and accuracy of the system in various situations. By providing early warnings to drivers, this system has significant potential to enhance road safety and prevent accidents caused by drowsiness.
A Comparative Study of Machine Learning Classifiers with SMOTE for Predicting Purchase Intention Khairunnisa, Khairunnisa; Soim, Sopian; Lindawati, Lindawati
Building of Informatics, Technology and Science (BITS) Vol 7 No 2 (2025): September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i2.7615

Abstract

The rapid growth of e-commerce has made it increasingly important for online platforms to understand user behavior, particularly in predicting purchasing intention. This study examines the implementation of three machine learning models: Logistic Regression, Random Forest, and Gradient Boosting, to classify purchase intention using real transaction session data. One of the primary obstacles confronted in this investigation is the matter of class imbalance found in the dataset, where 10422 records indicate no purchase while only 1908 indicate a completed purchase. This disparity may result in a biased model performance that prioritizes the dominant class and limits the ability to accurately detect minority class behavior, which in this case is the actual purchase. To resolve this matter, During the data preprocessing phase, the Synthetic Minority Over-sampling Technique (SMOTE) was implemented. Accuracy, precision, recall, and F1-score metrics were implemented to assess each model's functionality. The results indicate that following the implementation of SMOTE, the Random Forest model attained the best accuracy of 93%, succeeded by Gradient Boosting at 90% and Logistic Regression with 84%. These findings demonstrate that the use of SMOTE significantly improves model sensitivity and balance. This study provides useful insights into designing fairer and more effective predictive systems in the field of e-commerce.
Pengembangan Algoritma Convolutional Neural Network dalam Menganalisis Emosi Suara Menggunakan Mel-Spektogram Zakka, Iqlima Sabila; Rakhman, Abdul; Lindawati, Lindawati
Building of Informatics, Technology and Science (BITS) Vol 7 No 2 (2025): September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i2.7875

Abstract

Speech Emotion Recognition (SER) still faces challenges in accuracy, especially in distinguishing acoustically similar emotions. Conventional approaches such as MFCC (Mel Frequency Cepstral Coefficients) are often ineffective in capturing the emotional nuances of voice. To address this, this study aims to develop a Convolution Neural Network (CNN) model based on the Spec-ResNet architecture that uses Mel-Spectrogram as input to improve the system's ability to extract and recognize emotional signatures from speech signals. Another objective is to evaluate the performance of primary emotion classification in the RAVDESS dataset and measure model consistency through 5-fold cross-validation. The model used, Spec-ResNet, is an adaptation of the ResNet architecture equipped with residual learning to maximize the multi-stage feature extraction process. Experiments were conducted with the RAVDESS dataset containing 1,440 voice samples from six primary emotions: neutral, happy, sad, angry, afraid, and surprised. The test results showed a significant increase in accuracy, with a macro score reaching 92%, up from the MLP/SVM baseline of 83%. Neutral and happy emotions were classified very well (F1-scores of 93% and 90%), but emotions such as fear and surprise remained difficult to distinguish due to the similarity of their vocal patterns. Validation through 5-fold cross-validation yielded an average accuracy of 91.5% ± 0.8%. This study demonstrates the great potential of Mel-spectrograms in SER, while also underscoring the need for advanced approaches such as attention mechanisms to handle ambiguous emotions.
Co-Authors -, Angelina . Zulfan A Halim Abdul Rakhman Abdul Rauf Abelia, Dinda Dwi Ade Silvia Handayani Adeliana, Adeliana Adelita Lubis, Adelita Adriani, Silfia Afdhal Afdhal Affrylia, Gita Afkar, Mufidul Afridayani, Afridayani Afridon, Afridon Agatha, Adelia Agustiar agustiar Ahmad Syai Ahmad Taqwa Ahmadin Ahmadin Akmalia, Alfi Alaisyi, Alaisyi Aldo, Ketut Alfharijy, Muhammad Daffa Alfiansyah, Ikhwan Alfiatun, Alfiatun Alfirdaus, Muhammad Farrel ali khaeri, imam Alliya, Annisa Ul Alvionita, Gusni Am, Zakiati Amalia Amalia Amelianda, Amelianda Amiza, Ibel Dwi Amri Amin Andi Andi Andila, Tria Anggraini, Anggun Anisah Ardelia, Naila Arifani, Rizka Arifin Soenggono, Arifin Arlinda, Sari ARMEN ZULHAM Arsella, Shendy Aryanti Aryanti Asep Irfan Asmaul Husna Asriyadi Asriyadi Asrul Asrul Astari, Devina Atminingsih Atminingsih, Atminingsih Audina, Reka Aulia, Muhammad Rafi Awalia Gusti Awaluddin Awaluddin Az-zahra, Maudhy Azizah, Nur Putri Azwandi Azwandi Azzahra, Siti Azzahrah, Ladysa Baehaqi Bakhir , Norfarizah Mohd Bambang Pratama, Bambang Baso Intang Sappaile, Baso Intang Bunyamin Bunyamin Chairunnisaak, Mariam Cucu Atikah Cut Rahmawati Cut Zuriana Damiati, Tri Darus, Mozard Bahauddin Darwel, Darwel Deddy Junaedi Dewi Maya Sari Dharmalau, Andy Diana Chalil Didit Haryadi Dina Mayadiana Suwarma Effendy, Amalia Eka Pradani, Rizki Febri Eka Putri, Yuliantini Eka Susanti Eka Susanti, Eka Susanti Eko Sugiarto Elmerillia, Elmerillia Elvina, Aminah Enda Kartika Sari, Enda Kartika Enda, Enda Kartika Sari Endang Larasati Eri Yusni Ermawati Ermawati Ermawati, Yuli Fadhli, Mohammad Fadmawati, Any Fadmawaty, Any Faisal Ahmadi Fatani, Muhammad Fatimatuzzahra Fatimatuzzahra Febriani, Dina Fitra, Miladil Fitri Wardani, Erika Fitri, Aida Fitriadi, Nuzuli FITRIYANTI, RAMADHINA Frenica, Agnes Gameli, Cahyani Rahmi Garnita, Ria Ghodina, Aurina Willy Ghufran S., Mufti Miadi Ginanjar, Seandy Grenaldo Ginting Gusdi Sastra, Gusdi Hadir Hudiyanto, Hadir Hafsaridewi, Rani Hanah, Siti Handayani, Sri Hardi Siswo, Hardi Hasmawaty, Hasmawaty Hedra Bayu, Hendi Hesniati, Hesniati Hidayah, Hidayah Hidayat, Sholeh Hikmah Hikmah Holiawati, Holiawati HS, Alicia Husin, M. Husna, Ainul Ida Zulfida, Ida Iif Rahmat Fauzi, Iif Rahmat Ikhsan Yuda Pratama Indah Sari, Dewi Indawati, Indawati Iqbal Iqbal Iqmy, Ledy Oktaviani Irfan, Basuki Ario Seno Irma Salamah Irma Suryani Ironia Vivie Susanti, Ironia Vivie Ismawan Ismawan, Ismawan Iswanda, Odi Ivan Suaidi Iwan Setiawan Jaifan, Muhammad Jamjuri, Endi Jamratul Ula Jannah, Syifaul Joey, Joey Jonathan Ginting juliana, Nanin Khairunnisa Khairunnisa Khairunnisya, Aqilla Khie, Sak Komariah, Eneng Kurnita, Taat Lanza Pahlevi, Muhammad Lase, Yolanda Leni Marlina Lestari, Khotifah Puji Leuwol, Ferdinand Salomo Lili Dianah Lina Lina Linda Junia Ningsih Listiorini, Dewi Lucyana Lucyana, Lucyana Lukman Hakim M. Ridha Madiyoh, Abdulhakim Maharani, Ullya Dwi Mahaza Maisun, Maisun Maizal, Ilham Mamusung, Robby Tanod Mardiana, Dinny Mardikawati, Budi Margie, Lyandra Aisyah Marietta Shanti Marita, Tia Martianingsih, Baiq Lilik Martinus Mujur Rose Marur, Muhammad Marza, R. Firwandri Maulida, Putri Maulidin, Aula Maulin, Siti Maulisa, Ella Mayanda, Afrida Rizki Mediana, Salwa Deta Meliyana Meliyana, Meliyana Mirdayanti, Rina Monika, Sinar Monika, Sinar Mu'arif, Syamsul Muchlis, Yusrizal Muhammad Alwi Muhammad Faisal Muhammad Iqbal Muhtadin Muhtadin Mukhlis Mukhlis Mulyani, Riri Muniroh, Leny Muslim, Burhan Muslimah, Rina Mutaqin, Raihan Muthaharah, Muthaharah Mutmainnah Mutmainnah Na:am, Muh Fakhrihun Nahdudin, Nahdudin Nasution, Siti Khadijah Hidayati Novarijah, Syarifah Novianda, Nabila Rizqi Novianda, Nabila Rizqia Noviani, Fadiah Nur, Erdi Nurfi, Nurfi Nurhajar Anugraha Nurhanifa, Nurhanifa Nurjihan, Nisrina Nurlaili Nurlaili Nurwijayanti Onasis, Aidil Palawi, Ari Palin T, Yona Paryanto, Alfin Dwi Ponimin Purnamarini, Tri Ratna Putri Vandalis, Yoke Annisa Putri, Wulandari Cahyani Rabbani, Ali Rabiah, Nur Nabila Radifan, Hadyan Hilman RADITE TISTAMA Rahmanta Rahmanta, Rahmanta Rahmanta`, Rahmanta Rahmawati, Cut Raihan, Ahmad Raihanah, Adinda Rajes Ikhlas Rosaguna, Rajes Ikhlas Ramadhan, Andi Ramadhan, Muhammad Fadli Ratna Novita Punggeti RD Kusumanto Reo, Petrus Renol Rida Safuan Selian Rina Herawati, Augustin Riswanto, Muhammad Riviwanto, Muchsin Riviwanto, Muchsin` Rizka Fadli Wibowo, M. Roiyan, Lalu Muhammad Rosini, Iin Rudiyanto Rudiyanto, Rudiyanto Rukiyanto Rukiyanto, Rukiyanto Safitry, Yuwaffy Safriyani, Lia Saharani, Saharani Salsabila, Meidita Salsabila, Raina Saptanto, Subhechanis Saptanto, Subhechanis Sarhindi, Sarhindi Sari Wardani Sari, Rani Purnama Sari, Tengku Dede Rachma Sarjana Sarjana Sarjono Sarjono, Sarjono Sasrita, Bysmira Septiana, Ardilla Septiani, Rizka Ayu Septina, Phuja Tawilla Sholihin Sholihin Silfia Silfia, Silfia Silviana, Mery Sipasulta, Grace Carol Siregar, Nur Mawaddah Siti Hawa Sitorus, Abdoni Sopian Soim, Sopian Sopian, Adi Sri Wahyuni Suandari, Fitri Sufri, Rahmat Suksmerri Suksmerri Sume, Syahlan A. Sumilat, Rohyani Rigen Is Supadmi, Tri Suryani Suryani SURYANI, TRIA ANANDA Suyuti, Suyuti suzan zefi Syahardi, Amri Syahbana, Mahdi Syahril Syahril syakir syakir Syamsul Muarif Tengku Hartati Tengku Riza Zarzani N Tetep Tety Sriana Teuku Rizky Noviandy Tiurma, Tiurma Triani, Susi Trianov, Rilky Triasensi, Sherlya Tumilantouw, Kireina Gabriela Ul Karimah, Lulu Ummir, Badril Utami, Futri UTAMI, FUTRI Valerie, Michelle Viviani, Viviani Wahyudin, Mokhammad wahyudin, mukhammad Wardani, Happy Kusuma Wardani, Sari Wasludin, Wasludin Wibowo, Rulianda P. Widianty, Anggie Wijayantono, Wijayantono Wilyuza, Wilyuza Witomo, Cornelia Mirwantini Wulandari, Fadhilah Dwi Wulandari, Widyana Wusqa, Asy Syifa Urwatul Yanti Yanti Yulianto Yulianto Yuliasari, Dewi Yusnita, Emilia Yusrizal Yusrizal Zakka, Iqlima Sabila Zamakhari, Ahmad Zardi, Muhammad Zulprianto Zulprianto