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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) Register: Jurnal Ilmiah Teknologi Sistem Informasi JOIN (Jurnal Online Informatika) Syntax Literate: Jurnal Ilmiah Indonesia Muaddib : Studi Kependidikan dan Keislaman Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control JURNAL INSTEK (Informatika Sains dan Teknologi) Literasi: Jurnal Ilmiah Pendidikan Bahasa, Sastra Indonesia dan Daerah JOISIE (Journal Of Information Systems And Informatics Engineering) Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Kajian Ilmiah Paedagogie: Jurnal Pendidikan dan studi ISlam TAJDID: Jurnal Pemikiran Keislaman dan Kemanusiaan Indonesian Journal of EFL and Linguistics Makara Journal of Technology Kohesi: Jurnal Sains dan Teknologi Jurnal Penelitian Pendidikan Indonesia
Sari, Zamah
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Religion Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mechanical Engineering Public Health Social Sciences Other

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IMPLIKASI NILAI-NILAI AIK DALAM PERKULIAHAN: RELEVANSI PENDIDIKAN MUHAMMADIYAH ERA DISRUPSI Nurjam'an, Muhamad Ichsan; Sari, Zamah; Dwifajri, Muhammad
Tajdid Vol 9 No 2 (2025): Oktober
Publisher : LP2M IAI Muhammadiyah Bima

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52266/tadjid.v9i2.4935

Abstract

Era disrupsi membawa perubahan dunia pendidikan. Perubahan nilai, teknologi, dan orientasi pembelajaran. Nilai-nilai Al Islam menjadi pondasi utama pendidikan. Muhammadiyah sebagai lembaga pendidikan menghadapi tantangan dan peluang untuk diimplikasikan dalam proses perkuliahan. Penelitian ini bertujuan menjawab nilai-nilai Al Islam dalam perkuliahan relevansi pendidikan Muhammadiyah era disrupsi. Penelitian ini menggunakan pendekatan kualitatif deskriptif dan teknik pengumpulan data dokumen dan wawancara. Hasil penelitian menunjukkan implikasi nilai Al Islam sudah dilaksanakan dalam perkuliahan. Dibuktikan melalui dokumen RPS. Namun, hasil wawancara sebanyak 33 mahasiswa (70,22%) menyatakan bahwa pembelajaran AIK sangat membantu mereka dalam membentuk kepribadian dan meningkatkan kesadaran spiritual, 8 mahasiswa (17,02%) merasa pembelajaran AIK cukup menarik jika dikaitkan dengan isu-isu kontemporer, dan 3 mahasiswa (6,38%) menyatakan AIK masih bersifat normatif dan kurang relevan dengan dunia profesi mereka sebagai calon guru bahasa. Namun, terdapat 3 mahasiswa (6,38) yang tidak pernah ada selama perkuliahan (keluar/cuti). Temuan ini pendidikan Muhammadiyah tetap relevan dalam menyiapkan generasi yang bernilai Islam. Implikasi penelitian mampu mendorong penguatan pembinaan dan peningkatan berkelanjutan di Perguruan Tinggi Muhammadiyah.
Transfer Learning Approaches for Non-Organic Waste Classification: Experiments Using MobileNet and VGG-16 Sari, Zamah; Basuki, Setio
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 10, No. 4, November 2025
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v10i4.2319

Abstract

This paper develops machine learning (ML) models for classifying non-organic waste automatically. The goal is to support more effective waste management by increasing recycling rates, reducing landfill use, and minimizing environmental impact. The ML models proposed in this paper classify 20 types of non-organic waste collected from the internet, which consists of 2,552 instances. Our experiments reveal several key findings. First, MobileNet, which achieved 86% accuracy, outperforms VGG-16, which reaches only 72% accuracy. Second, both models show good classification performances in classifying glass bottles, toothbrushes, and cigarette butts. Third, both models suffer from misclassification in visually similar categories, especially when it comes to paper-based waste like books, cardboard, foam packaging, and carton packaging. Fourth, MobileNet has difficulty detecting plastic packaging, carton packaging, and books, while VGG-16 exhibits higher misclassification rates for foam packaging, cardboard, and newspapers. These results pose a further critical development of the model to classify non-organic waste with similar textures and shapes. Moreover, it presents the urgency of improving the model to distinguish visually similar waste materials. Considering the number of labels used in this paper compared with existing studies, the findings demonstrate the competitiveness of our models for non-organic waste classification.
ANALISIS FORENSIK TOOLWIZ TIME SOLID STATE DRIVE MENGGUNAKAN METODE NIST Anam, Bagas Khoirul; Sari, Zamah; Muthohirim, Bashor Fauzan
JOISIE (Journal Of Information Systems And Informatics Engineering) Vol 8 No 2 (2024)
Publisher : Institut Bisnis dan Teknologi Pelita Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35145/joisie.v8i2.4768

Abstract

Kini dengan berkembangnya teknologi internet, perkembangan dunia informasi sangat berkembang pesat. Tidak sedikit pengaruh negatif yang timbul dari teknologi terbaru yang kedepannya bisa mengancam kehidupan manusia. Kejahatan siber sekarang sudah marak terjadi dan menjadikan ini masalah utama yang harus diselesaikan. Siber adalah jenis aktifitas ilegal yang dilakukan menggunakan teknologi komputer. Kejahatan yang mencakup hacking, phising dan pencurian identitas dapat dilakukannya. Adapun solusi yang ditawarkan dalam penelitian ini dengan menggunakan sofware Autopsy dan sebagai uji coba menggunakan Toolwiz Time. Penggunaan dari software tersebut serta adanya ilmu forensik dapat dengan mudah mengetahui kejahatan apa saja yang sudah disembunyikan maupun dihapus untuk menghilangkan barang bukti yang dilakukan. Tujuan dari penelitian ini adalah untuk mengetahui bagaimana cara software Toolwiz Time bekerja untuk melakukan frozen pada SSD serta Autopsy dapat menemukan barang bukti pada SSD yang terkena frozen. Metode yang digunakan adalah NIST. Pada metode ini ada empat tahap yang harus dilakukan yaitu collection, examination, analisys dan reporting. Hasil yang diperoleh dari penelitian ini adalah penemuan bukti berupa perubahan log folder yang dapat diketahui dengan Autopsy. Kesimpulan yang didapat penggunaan software autopsy berhasil melakukan analisis pada modified time dan change time yang ditunjukkan pada software tersebut.
Analysis of the Combination of Naïve Bayes and MHR (Mean of Horner’s Rule) for Classification of Keystroke Dynamic Authentication Sari, Zamah; Chandranegara, Didih Rizki; Khasanah, Rahayu Nurul; Wibowo, Hardianto; Suharso, Wildan
JOIN (Jurnal Online Informatika) Vol 7 No 1 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i1.839

Abstract

Keystroke Dynamics Authentication (KDA) is a technique used to recognize somebody dependent on typing pattern or typing rhythm in a system. Everyone's typing behavior is considered unique. One of the numerous approaches to secure private information is by utilizing a password. The development of technology is trailed by the human requirement for security concerning information and protection since hacker ability of information burglary has gotten further developed (hack the password). So that hackers can use this information for their benefit and can disadvantage others. Hence, for better security, for example, fingerprint, retina scan, et cetera are enthusiastically suggested. But these techniques are considered costly. The advantage of KDA is the user would not realize that the system is using KDA. Accordingly, we proposed the combination of Naïve Bayes and MHR (Mean of Horner’s Rule) to classify the individual as an attacker or a nonattacker. We use Naïve Bayes because it is better for classification and simple to implement than another. Furthermore, MHR is better for KDA if combined with the classification method which is based on previous research. This research showed that False Acceptance Rate (FAR) and Accuracy are improving than the previous research.
The Implementation of Restricted Boltzmann Machine in Choosing a Specialization for Informatics Students Nastiti, Vinna Rahmayanti Setyaning; Sari, Zamah; Chintia Eka Merita, Bella
JOIN (Jurnal Online Informatika) Vol 8 No 1 (2023)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v8i1.917

Abstract

Choosing a specialization was not an easy task for some students, especially for those who lacked confidence in their skill and ability. Specialization in tertiary education became the benchmark and key to success for students’ future careers. This study was conducted to provide the learning outcomes record, which showed the specialization classification for the Informatics students by using the data from the students of 2013-2015 who had graduated. The total data was 319 students. The classification method used for this study was the Restricted Boltzmann Machine (RBM). However, the data showed imbalanced class distribution because the number of each field differed greatly. Therefore, SMOTE was added to classify the imbalanced class. The accuracy obtained from the combination of RBM and SMOTE was 70% with a 0.4 mean squared error.
Teachers' perception of the impact of the flipped learning model on student learning and engagement in high school education in Indonesia Kusumawati, Endah Tri; Solihati, Nani; Sari, Zamah; Nurhanan, Nurhanan
JPPI (Jurnal Penelitian Pendidikan Indonesia) Vol. 10 No. 2 (2024): JPPI (Jurnal Penelitian Pendidikan Indonesia)
Publisher : Indonesian Institute for Counseling, Education and Theraphy (IICET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29210/020244463

Abstract

This study aims to investigate teachers' perceptions of the impact of flipped learning on student learning and motivation in a high school in West Java. The study involved 103 teachers who have implemented flipped learning in their teaching practice. Data were collected using a questionnaire consisting of 17 statements related to teachers' perceptions of flipped learning, which were then analyzed using descriptive statistics with validity and reliability tests to examine the relationship between teachers' perceptions with gender and teaching experience. The results showed that the majority of teachers responded positively to the implementation of flipped learning, indicating a positive impact on students' motivation and readiness to be actively involved in class. However, no significant differences were found between teachers' perceptions based on gender or length of teaching experience. These findings provide important insights into the potential of flipped learning to be implemented more widely in Indonesia. The limitation of this study lies in the limited scope of the sample, so further research is needed to explore other contexts and more diverse factors. The findings can be used by teachers and policy makers to design more effective training and support programs to improve the implementation of flipped learning in Indonesia.
Deteksi Penyakit Malaria Menggunakan Klasifikasi Berbasis CNN Yusuf, Achmad; Azhar, Yufis; Sari, Zamah
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/syntax-literate.v9i1.14771

Abstract

Malaria merupakan penyakit yang serius dan berpotensi fatal yang disebabkan oleh parasit protozoa. Penyakit ini umumnya ditularkan oleh nyamuk dan tersebar luas di berbagai wilayah tropis dan subtropis, salah satu metode deteksi malaria berbasis citra digital yang banyak digunakan adalah deteksi malaria berbasis convolutional neural network (CNN). Tujuan penelitian ini adalah untuk mendeteksi penyakit malaria menggunakan klasifikasi berbasis CNN. Penelitian ini menggunakan metode penelitian systematic literature review. Data dikumpulkan melalui pencarian sistematis dalam database akademik dan perpustakaan digital yang relevan seperti Google Schoolar dengan kata kunci penyakit malaria & CNN. Data yang telah terkumpul kemudian dianalisis mencakup perbandingan, kategorisasi, dan penyajian temuan-temuan yang relevan dari studi-studi yang ada sehingga diperoleh 8 penelitian yang digunakan dalam penelitian ini. Hasil systematic literature review adalah menemukan bahwa diagnosis penyakit malaria berbasis CNN efektif dan dapat diandalkan untuk mendeteksi penyakit malaria dengan persentase lebih dari 90%.
PENINGKATAN KEMAMPUAN PENGOLAHAN DATA DENGAN PEMANFAAATAN APLIKASI BERBASIS KECERDASAN BUATAN BAGI PENELITI BAPPEDA KABUPATEN SIDOARJO Azhar, Yufis; Sari, Zamah; Kholimi, Ali Sofyan
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 5 No. 1 (2024): Volume 5 No 1 Tahun 2024
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v5i1.22719

Abstract

Kegiatan pengabdian ini bertujuan untuk meningkatkan kemampuan pengolahan data dengan menggunakan aplikasi berbasis Artificial Intelligence (AI), atau kecerdasan buatan, bagi para peneliti di BAPPEDA Kabupaten Sidoarjo. Kegiatan ini dilakukan dengan metode pelatihan hybrid, yaitu kombinasi antara pelatihan luring dan daring. Pelatihan ini meliputi pengenalan konsep dan prinsip dasar pengolahan dan analisis data, penggunaan software analisis data seperti Microsoft Excel, Aplikasi berbasis AI dalam penggalian informasi tersembunyi dalam dataset, dan metode dan teknik analisis data yang lebih canggih. Hasil evaluasi menunjukkan bahwa kegiatan pengabdian ini berhasil meningkatkan pengetahuan, keterampilan, perilaku, dan hasil peserta dalam pengolahan data dengan menggunakan aplikasi berbasis AI. Kegiatan pengabdian ini juga memberikan dampak positif terhadap kinerja individu, organisasi, dan pembangunan daerah.
User Classification Based On Mouse Dynamic Authentication Using K-Nearest Neighbor Chandranegara, Didih Rizki; Ashari, Anzilludin; Sari, Zamah; Wibowo, Hardianto; Suharso, Wildan
Makara Journal of Technology Vol. 27, No. 1
Publisher : UI Scholars Hub

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

Abstract

Mouse dynamics authentication is a method for identifying a person by analyzing the unique pattern or rhythm of their mouse movement. Owing to its distinctive properties, such mouse movements can be used as the basis for security. The development of technology is followed by the urge to keep private data safe from hackers. Therefore, increasing the accuracy of user classification and reducing the false acceptance rate (FAR) are necessary to improve data security. In this study, we propose to combine the K-nearest neighbor method and simple random sampling and obtain a sample from a dataset to improve the classification of users and attackers. The results show that our proposed method has high accuracy for implement to practical system and reports the best results than previous research with a FAR of 0.037. Therefore, this method can be implemented in a real login system. The high false rejection rate of our proposed method will not be a problem because the most important thing in the login system is denying the attacker system access.
Co-Authors Abdul Hakim, Sudarnoto Abdul Munir Mulkhan Adian Husaini Agus Eko Minarno Akbi, Denar Regata Ali Sofyan Kholimi Amirullah -, Amirullah Anam, Bagas Khoirul Aristyo, Ananda Rizaldy Ashari, Anzilludin Bashor Fauzan Muthohirin Basuki, Setio Chandranegara, Didih Rizki Chintia Eka Merita, Bella Dewantoro, Muhammad Bagas Didin Saefudin Dwi Fajri, Muhamad Dwifajri, Muhammad Hakim , Sudarnoto Abdul Hardianto Wibowo Hidayatullah, Rakhmad Arif Ina Setiawati Indrabayu, Rizky Jupri, Abdul Rahman Khasanah, Rahayu Nurul Kiki, Muhammad Rizkiansyah Maulana Kusumawardani, Mila Kusumawati, Endah Tri Luqman Hakim Mahar Faiqurahman MANGUNWIBAWA, ARIA AHMAD Moechammad Sarosa Mulya, Gani Mulyono, Herdiana Muthohirim, Bashor Fauzan Nani Solihati Naser Jawas, Naser Novitasari, Diyan Anggraini Nurhanan, Nurhanan Nurjam'an, Muhamad Ichsan Pangestu, Syahrul Pratama, Bagus Aryo Hany Primandhika, Restu Bias Rizki, Didih S, Vinna Rahmayanti Saefuddin, Didin Salam, Fajar Mayda Shintya Larasabi , Auliya Tara Sucia, Dara Sudarnoto Abdul Hakim Suyono, Achmad Syahid Widyanto, Azis Nur Syamsul Arifin Tsuchiya, Masatoshi Wahyu Andhyka Kusuma Wildan Suharso Yufis Azhar Yusuf, Achmad