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All Journal International Journal of Public Health Science (IJPHS) Jurnal Ilmu Lingkungan Jurnal Sains dan Teknologi Pangan The Indonesian Journal of Public Health Minda Baharu JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI JIIP (Jurnal Ilmiah Ilmu Pendidikan) Jurnal Keselamatan Transportasi Jalan (Indonesian Journal of Road Safety) Jurnal Ilmiah Jophus: Journal of Pharmacy UMUS Buletin Poltanesa Jurnal Ilmiah Kebidanan Imelda International Journal of Basic and Applied Science Fruitset Sains : Jurnal Pertanian Agroteknologi JAMU : Jurnal Abdi Masyarakat UMUS Journal of Food and Agricultural Product Journal of Technology and Food Processing (JTFP) Community: Jurnal Pengabdian Pada Masyarakat Jurnal Teknologi Pangan dan Industri Perkebunan Journal of Agribusiness and Community Development Umus Jurnal Teknologi Pangan dan Ilmu Pertanian Jurnal Cendekia Ilmiah Jurnal Keselamatan Transportasi Jalan Jurnal Teknologi Pangan dan Ilmu Pertanian Journal of Current Studies in SDGs Journal of Current Studies in SDGs
Yan El Unzilatirrizqi D
Universitas Muhadi Setiabudi
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering 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 Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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YOLO-Based Real-Time Artificial Intelligence Traffic Counting for Urban Transportation Monitoring in Surakarta: Implications for SDG 11 Bambang Istiyanto; Yan El Rizal Unzilatirrizqi D; Alfan Baharuddin; Pipit Rusmandani
Journal of Current Studies in SDGs Vol. 2 No. 1 (2026): March
Publisher : Sekolah Tinggi Agama Islam Sabilul Muttaqin Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63230/jocsis.2.1.152

Abstract

Objective: To develop and evaluate an artificial intelligence (AI)-based traffic counting system using the YOLO (You Only Look Once) deep learning algorithm to provide accurate and real-time traffic volume data for urban transportation management. Method: Employing a deep learning approach by implementing the YOLO algorithm for vehicle detection and traffic counting. Traffic video data from road objects in Surakarta City were processed to identify and classify various vehicle types. The AI-generated traffic counting results were then compared with manual traffic survey data to assess the system’s accuracy and effectiveness. Results: The findings indicate that the proposed AI-based traffic counting system can accurately detect and classify multiple vehicle categories, including cars, motorcycles, trucks, buses, bicycles, and Bajaj. The traffic-counting data produced by the system were highly readable and reliable. Comparison with manual traffic surveys showed that the AI-generated results were very similar while requiring significantly less time and human resources. The system achieved nearly 100% consistency with the available secondary traffic volume data, demonstrating its effectiveness in monitoring urban traffic conditions. Novelty: Application of the YOLO deep learning algorithm for automated traffic counting in the urban road environment of Surakarta City. The proposed system provides a practical and efficient alternative to conventional manual traffic surveys by delivering accurate, real-time traffic data with minimal human intervention, thereby supporting more effective urban transportation planning and management. These contributions are also relevant to SDG 11 (Sustainable Cities and Communities) by enabling data-driven traffic monitoring and facilitating smarter, more sustainable urban mobility management.
YOLO-Based Real-Time Artificial Intelligence Traffic Counting for Urban Transportation Monitoring in Surakarta: Implications for SDG 11 Bambang Istiyanto; Yan El Rizal Unzilatirrizqi D; Alfan Baharuddin; Pipit Rusmandani
Journal of Current Studies in SDGs Vol. 2 No. 1 (2026): March
Publisher : Sekolah Tinggi Agama Islam Sabilul Muttaqin Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63230/jocsis.2.1.152

Abstract

Objective: To develop and evaluate an artificial intelligence (AI)-based traffic counting system using the YOLO (You Only Look Once) deep learning algorithm to provide accurate and real-time traffic volume data for urban transportation management. Method: Employing a deep learning approach by implementing the YOLO algorithm for vehicle detection and traffic counting. Traffic video data from road objects in Surakarta City were processed to identify and classify various vehicle types. The AI-generated traffic counting results were then compared with manual traffic survey data to assess the system’s accuracy and effectiveness. Results: The findings indicate that the proposed AI-based traffic counting system can accurately detect and classify multiple vehicle categories, including cars, motorcycles, trucks, buses, bicycles, and Bajaj. The traffic-counting data produced by the system were highly readable and reliable. Comparison with manual traffic surveys showed that the AI-generated results were very similar while requiring significantly less time and human resources. The system achieved nearly 100% consistency with the available secondary traffic volume data, demonstrating its effectiveness in monitoring urban traffic conditions. Novelty: Application of the YOLO deep learning algorithm for automated traffic counting in the urban road environment of Surakarta City. The proposed system provides a practical and efficient alternative to conventional manual traffic surveys by delivering accurate, real-time traffic data with minimal human intervention, thereby supporting more effective urban transportation planning and management. These contributions are also relevant to SDG 11 (Sustainable Cities and Communities) by enabling data-driven traffic monitoring and facilitating smarter, more sustainable urban mobility management.
INOVASI PENGENALAN MIE SEHAT BERBASIS SAYUR DAN BUAH SEBAGAI UPAYA EDUKASI GIZI DI SMA N 1 LOSARI Diah Ratnasari; Azizah Indriyani; YanYan El Rizal Unzilatirrizqi D D; Rifatul Masrikhiyah; Febriani Febriani
JAMU : Jurnal Abdi Masyarakat UMUS Vol. 6 No. 02 (2026): Februari
Publisher : LPPM Universitas Muhadi Setiabudi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46772/jamu.v6i02.1859

Abstract

Program Pengabdian Kepada Masyarakat ini berfokus pada edukasi pengenalan mie sehat berbahan dasar buah dan sayuran sebagai upaya memberikan pengetahuan kepada masyarakat mengenai dampak negatif konsumsi mie instan serta mendorong perubahan ke arah pola makan yang lebih sehat. Kegiatan ini ditujukan khusus untuk meningkatkan kesadaran siswa-siswi SMA N 1 Losari, Brebes, mengenai pentingnya menjaga kesehatan melalui konsumsi pangan bergizi yang diolah secara inovatif agar dapat diterima semua kalangan. Selain itu, program ini juga menanamkan pemahaman bahwa kreativitas dalam pengolahan pangan tidak hanya bermanfaat bagi kesehatan, tetapi juga berpotensi meningkatkan pendapatan masyarakat. Metode pelaksanaan dilakukan melalui sistem pembelajaran daring yang dilengkapi dengan modul dan video tutorial pembuatan mie sehat. Pendekatan yang digunakan meliputi metode ceramah, diskusi interaktif, serta sesi tanya jawab untuk memperdalam pemahaman peserta. Hasil yang diperoleh setelah program berjalan selama satu bulan menunjukkan bahwa masyarakat, khususnya siswa-siswi, telah memiliki pengetahuan dasar mengenai mie sehat berbahan buah dan sayuran, termasuk pemahaman tentang proses pembuatannya
Analisis Kadar Antosiani Tepung Bunga Telang (Clitoria Ternatea L) Serta Pengaruhnya Terhadap Tekstur dan Organoleptik Soft Cookies aallya rizki utami; Yan El Rizal Unzilatirrizqi; Melly Fera; Yunika Purwanti
Journal of Technology and Food Processing (JTFP) Vol. 6 No. 02 (2026): Juli
Publisher : Program Studi Ilmu Teknologi Pangan Universitas Muhadi Setiabudi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46772/jtfp.v6i02.1946

Abstract

Bunga telang (Clitoria ternatea L.) merupakan sumber antosianin alami yang berpotensi dimanfaatkan sebagai bahan fungsional dan pewarna alami pada produk bakery. Penelitian ini bertujuan menganalisiskadar antosianin tepung bunga telang serta pengaruhnya terhadap tekstur dan organoleptik soft cookies. Penelitian ini menggunakan Rancangan Acak Lengkap (RAL) dengan penambahan tepung bunga telang 0%, 10%, 15%, dan 20% dengan tiga kali ulangan. Kadar antosianin dianalisis dengan menggunakan metode pH diferensial, tekstur diuji menggunakan penetrometer, dan uji organoleptik dievaluasi dengan uji mutu hedonik. Data dianalisis menggunakan ANOVA yang dilanjutkan dengan uji Duncan Multiple Range Test (DMRT), dan data organoleptik dianalisis dengan uji Kruskal-Wallis dan Mann-Whitney. Hasil penelitian menunjukkan tepung bunga telang mengandung antosianin sebesar 653,52 ppm, kadar antosianin soft cookies setelah pemanggangan sebesar 50,48 ppm. Penambahan tepung bunga telang berpengaruh nyata terhadap tekstur dan seluruh atribut organoleptik, dengan perlakuan terbaik diperoleh pada penambahan 10%. Tepung bunga telang berpotensi dimanfaatkan sebagai sumber antosianin alami dalam pengembangan soft cookies fungsional dengan konsentrasi optimum 10%.
Pengaruh Penambahan Kapur Sirih Terhadap Karakteristik Organoleptik Keripik Kulit Pisang Kepok (Musa Paradisiaca Linn) Ilma Aenan Hidayah; Melly Fera; Yan El Rizal Unzilatirrizqi Dewantoro
Jurnal Teknologi Pangan dan Ilmu Pertanian Vol. 1 No. 3 (2023): September : Jurnal Teknologi Pangan dan Ilmu Pertanian
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jtpip-widyakarya.v1i3.1347

Abstract

Banana is one of the potential tropical fruit commodities in Indonesia, including in Brebes Regency, Central Java Province. So far, people have only used the banana fruit and heart as food processing materials, while banana peels have only been processed product waste. Even though the banana peel contains 18.5% carbohydrates, 68.90% water, some vitamin C, various B-complex vitamins, including B6, fat, lutein, anti-oxidants, calcium, vegetable oil, fiber, serotonin and sufficient protein. With a simple food processing technology, these banana peels can be processed into banana peel chips with sweet, savory and spicy flavors which can be family meals or snacks that have nutritional value and can automatically reduce organic waste and generate income. The purpose of this study was to determine the effect of the addition of whiting on the organoleptic characteristics of banana peel chips. This research was conducted using a quantitative experimental method using a completely randomized design (CRD) with two factors, namely the addition of whiting and soaking time. Parameters measured were acceptability or organoleptic texture, color, aroma and taste.
Co-Authors aallya rizki utami Akh Khotib Kurniawan Alfan Baharuddin Alik Kandhita Febriani Amanda Putri Ismayanti Anis Wulandari Ataqwa, Krisjayanti Azise Wijinurhayati, Anissofiah Bambang Cahyono Bambang Istiyanto Diah Ratnasari Dini Adita, Muhammad El Husna, Iksiroh Febriani Febriani Fera, Melly Harnawati, Riska Arsita Idayatma, Widya Putri Ilma Aenan Hidayah Ilma Aenan Hidayah Indriyani, Azizah khusnul khotimah Krisjayanti Melly Fera Mohammad Jusuf Randi Muh Taufiq Mahfudh Muhammad Juwanda, Muhammad Juwanda Nur Utami, Suci Pipit Rusmandani, Pipit Pungkas Hendratmoko, Pungkas Putra, Zidan Raafi Utama Rahmawati, Yuniarti Dewi Rifatul Masrikhiyah Riska Arsita Harnawati Rizkiyani, Sari Salsabila Rois Nurlatifah Rois Nurlatifah Sari Salsabila Rizkiyani Sari Salsabila Rizkiyani Sholeh Setiawan, Riandy Sholeh Setiawan, Riandy Sri Mukodiningsih Syahidah Mutmainah Wadli Wadli Wadli, Wadli Yunika Purwanti Zul muzhahir Zul Muzhahir