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All Journal Al-Mizan (e-Journal) Al-Risalah : Jurnal Imu Syariah dan Hukum AL-Daulah Laa Maisyir Jurnal Ekonomi Islam Al-Ihkam: Jurnal Hukum dan Pranata Sosial Jurnal Penelitian Pendidikan IPA (JPPIPA) Agregat: Jurnal Ekonomi dan Bisnis Studi Arab Journal of Computer Science and Informatics Engineering (J-Cosine) Jurnal Pengabdian Magister Pendidikan IPA Dielektrika : Jurnal Ilmiah Kajian Teori dan Aplikasi Teknik Elektro Jurnal Teknik Informatika C.I.T. Medicom International Journal of Electrical, Energy and Power System Engineering (IJEEPSE) Alauddin Law Development Journal (ALDEV) Al-Ahkam : Jurnal Hukum Pidana Islam Asy-Syarikah : Jurnal Lembaga Keuangan, Ekonomi dan Bisnis Islam Qadauna: Jurnal Ilmiah Mahasiswa Hukum Keluarga Islam El-Iqtishady Iqtishaduna : Jurnal Ilmiah Mahasiswa Hukum Ekonomi Syariah TASAMUH: Jurnal Studi Islam Al-Mutsla: Jurnal Ilmu-Ilmu Keislaman dan Kemasyarakatan Qisthosia Al-Ubudiyah: Jurnal Pendidikan dan Studi Islam Jurnal Kolaboratif Sains Journal of Islamic History ISTIQRA: JURNAL HASIL PENELITIAN Journal of Scientech Research and Development Journal Online Manajemen ELPEI (JOMEL) Asalibuna Journal of Islamic Communication and Counseling Jurnal Karajata Engineering Journal of Mathematics Learning Innovation (JMLI) DIKTUM: JURNAL SYARIAH DAN HUKUM An Nuqud: Journal of Islamic Economics Business and Investment Review Gudang Jurnal Multidisiplin Ilmu Tafaqquh : Jurnal Hukum Ekonomi Syariah dan Ahwal Syahsiyah Serambi Engineering Tamalanrea: Journal of Government and Development Jurnal Wicara Desa Al-Qawānīn: Jurnal Ilmu Hukum, Syariah, dan Pengkajian Islam Journal of Islamic Education Management Research (JIEMER) Parewa Saraq: Journal of Islamic Law and Fatwa Review Indonesian Journal of Islamic Jurisprudence, Economic and Legal Theory PENA BANGSA: BISNIS DAN TATA KELOLA PUBLIK ADPTIF
Misbahuddin
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Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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Efektivitas Belanja Pendidikan dan Kesehatan terhadap Indeks Pembangunan Manusia: Analisis Regresi Nonparametrik Misbahuddin; Andi Rahmat Nizar Hidayat; Tri Cahyo Nugroho; Irfan. B; Mahrani
PENA BANGSA: Bisnis dan Tata Kelola Publik Adaptif Vol. 1 No. 2 (2025): December 2025
Publisher : PT. Palem Edukasi Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/pb.v1i2.562

Abstract

This study analyzes the effectiveness of provincial government spending on education and health in relation to the Human Development Index (HDI) in Indonesia using a nonparametric regression approach. Cross-sectional data from 34 provinces for the year 2025, obtained from the Central Statistics Agency (BPS) and the Ministry of Finance, were utilized. The Nadaraya-Watson kernel regression method was applied to capture the nonlinear relationship between public spending and HDI without imposing a predetermined functional form, while conventional linear regression was used for comparison (R² = 0.43). The results reveal a nonlinear relationship with three distinct phases: rapid initial growth, stable growth, and a plateau indicating diminishing returns. Based on spending effectiveness, provinces were classified as high (6 provinces), medium (18 provinces), and low (10 provinces). Provinces with low performance exhibited high spending but lower-than-predicted HDI, indicating inefficiencies in governance and program implementation. These findings highlight that the success of human development is not solely determined by the size of the budget, but also by the quality of fiscal governance and implementation capacity. The study recommends evidence-based budgeting, strengthening fiscal governance, and targeted capacity-building support for low-performing provinces to enhance the effectiveness of public spending.
OPTIMIZATION OF CONVOLUTIONAL NEURAL NETWORK ALGORITHMIC ACCURACY FOR THE IDENTIFICATION OF DIFFERENT FONT TYPES Kanata, Bulkis; Misbahuddin; Akhdan, M. Rafif
Jurnal Teknik Informatika C.I.T Medicom Vol 17 No 5 (2025): November : Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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

Abstract

Text not only conveys the message through the words used, but also through its visual aspects. One of the most influential visual elements is the type of font. Recognising and determining font types appropriately is essential, whether in the academic sector, the printing industry, graphic design, or digital systems. However, in practice, manually recognising font types takes time, skill, and high precision. With the advancement of digital technology, the variety of font types is increasing, making the process of identifying fonts more complicated. This requires the development of methods that are able to distinguish different types of fonts precisely and accurately. This study reveals the potential of Convolutional Neural Network (CNN) algorithms as an optimisation in facing font identification challenges, as well as to prove that deep learning can provide more efficient and precise solutions, by comparing three different CNN architectures, namely DenseNet121, ResNet50, and VGG16. The implementation of the method is carried out by applying data augmentation techniques and setting CNN parameters such as the number of epochs, learning rate, batch size, Adam optimiser, and image size. The results showed that the DenseNet121 model achieved an accuracy of up to 96.8%, ResNet50 92.9%, and VGG16 96.4%. The convolutional neural network algorithm proves that it can identify various font types with optimal accuracy.
Co-Authors , Muhammad Taufik A. Sjamsjiar Rachman Abd Wahab Abd. Rahman Razak Abd. Rauf M. Amin Abdul Rivai Poli Abdullah Agung Setiyawan, Agung Ahmad Ramadlan Ahsan, Muhammad Aidi, Ahmad Pajar Ainul Maqsurah S Akbar, L. Syamsul Irfan Akhdan, M. Rafif Akram Ista Amal Ashraf Ana Mariana, Ana Andi Rahmat Nizar Hidayat Anisa, Nur Ainun Aprialdy Budi Saputra ARDIANSYAH, FAISAL Arif Imam Suroso Asfar, Khaerul Asfira Yuniar Aupiya, Sayidatul B, Irfan Bakence, Lutfi Bakri, Muhammad Rizal Basirun, Adam BN, Andi Muh. Taqiyuddin Bulkis Kanata Diva Septiawan Djul Fikry Budiman, Djul Fikry Fahrianty, Nyimas Alvira Fattah, Salman FIKRI HAIKAL Fikriansyah, Muhamad Giri Wahyu Wiriasto Guntur, Ihsan GUSTI MUZAINAH Hakikah, Zahiratul Hakzah Hamsyah Harahap, Ida Lestari Hartawan, Bagi Herlina Herman Hidayat, Andi Rahmat Nizar Hidayat, Muhammad Rihan Hisbullah Hisbullah Hisbullah HM. Kafrawi, Try Sa’adurrahman Ibtisam Ida Ayu Putu Sri Widnyani Ilnawati Iqbal, M. Syamsu Irfan Akbar, L. Ahmad Syamsul Irfan. B j, Winaldi Jailuddin, Syuaib Kamaruddin Kaprawi Kasim Yahiji Khaerul Rasyidi Krisdiana, Putri Kurniati L.A.Syamsul Irfan Akbar Lutfi , Mukhtar Mahrani Maulan, Muhammad Galih Maulana, Muhammad Galih Maunte, Narwin Meilani Misbahuddin, Misbahuddin Mohammad Syamsul Maarif Muammar M. Bakry Muhamad Syamsu Iqbal Muhammad Akbar Muhammad Ilham Nanda Muhammad Rahman Almunawir Muhammad Shuhufi Muhammad Usman, Muhammad Mujiburrahman Mukhtar Lutfi Mulham Jaki Asti Muslimin Kara Mustakim Mustakim Nafizatunni’am Nasaruddin Nasim, Abu Sahman Nasriah Akil Nur Fhayruzia Nur Hayani Nur Taufik Sanusi Nur Taufiq Sanusi nurfaika ishak Nurfaika, Sitti Nurjannah Nurlina Nurul Mujahidah Nurwijayanti Pikahulan, Rustam Magun Putri, Nurliana Andini Rahim, Asrianto Rahman, Rayn Ade Rahmawati Ramoddin Rasyid, St. Cheriah Ridal Ridwan Rifai, Ahmad Faizal Rohmatun Lukluk Isnaini, Rohmatun Lukluk Rosyida, Khairul Rukmanasari, Ita Saleh Ridwan Salsabila Usman Sapa, Nasrullah Bin Saputra, Udes Shuhufi Siradjuddin Sofyan SUHARTO Supriadi Supriadi Suprijati Sarib Syamsul Darlis Taufik, Imran Thahir, Muhammad Nasir Tri Cahyo Nugroho Tri Cahyo Nugroho Ulfa Wahidah Wicaksono, Eko Prasetyo Yunus Triyonggo