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All Journal Jurnal technoscientia Techno (Jurnal Fakultas Teknik, Universitas Muhammadiyah Purwokerto) JUITA : Jurnal Informatika JSAI (Journal Scientific and Applied Informatics) JURNAL TEKNOLOGI TECHNOSCIENTIA Jurnal Generic Innovation in Research of Informatics (INNOVATICS) Jurnal Pendidikan dan Teknologi Indonesia Automotive Experiences Jurnal Informatika Teknologi dan Sains (Jinteks) Blend Sains Jurnal Teknik Prosiding Seminar Nasional Hasil-hasil Penelitian dan Pengabdian Pada Masyarakat VISA: Journal of Vision and Ideas Sistem dan Teknik Transportasi Indonesia
Tito Pinandita
Universitas Muhammadiyah Purwokerto
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering Public Health Social Sciences Transportation

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Short-Term Prediction of Bus Station Fleet Number Using a Combination of BiLSTM Models Siswanto, Joko; Rahmawati, Ainun; Rahardja, Untung; Putra, Nanda Dwi; Hakim, Muhammad Iman Nur; Pinandita, Tito; Prasetyo, Ilham Bagus
Automotive Experiences Vol 8 No 1 (2025)
Publisher : Automotive Laboratory of Universitas Muhammadiyah Magelang in collaboration with Association of Indonesian Vocational Educators (AIVE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/ae.13402

Abstract

Predicting the number of bus station fleets requires a holistic approach, using sophisticated data analysis techniques and appropriate predictive modeling. Short-term predictions of bus station fleet numbers are proposed based on the best MAPE evaluation values ​​from the comparison of the Bi-LSTM, BiLSTM-CNN, BiLSTM-Transformer, BiLSTM-Informer, and BiLSTM-Reformer models. The dataset used is in the form of a CSV consisting of 6 types of arrivals and departures of the Giwangan City Yogyakarta type A bus station fleet from 01/01/2021 to 09/30/2023. The best prediction model was found in BiLSTM-Transformers based on a MAPE value of 0.2211 with a relatively fast time (00:00:52) compared to BiLSTM, BiLSTM-CNN, BiLSTM-Informer, and BiLSTM-Reformer. The BiLSTM-Transformer model can short-term predict 6 types of fleet arrivals and departures at the bus station in the next 30 days. The peak of the bar and curve is at 0 which means the proposed prediction model is very accurate. There is 1 strong positive correlation, 2 weak positive correlations, 2 strong negative correlations, 8 weak negative ones, and 2 uncorrelated ones. Prediction results can be used to support short-term decision making in fleet planning and management based on the dynamics of community mobility.
Menuju Desa Cerdas: Pengembangan Sistem Surat Digital untuk Modernisasi Pelayanan Publik Kusuma, Fajar Budi; Supriyono, Supriyono; Pinandita, Tito; Wicaksono, Agung Purwo
Blend Sains Jurnal Teknik Vol. 4 No. 1 (2025): Edisi Juli
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/blendsains.v4i1.969

Abstract

Di Desa Pahonjean, kegiatan administrasi surat menyurat masih dilakukan secara manual, yang mengakibatkan proses pelayanan publik menjadi lambat, kurang efisien, dan rentan terhadap kesalahan pencatatan. Penelitian ini bertujuan untuk meningkatkan kualitas layanan publik dengan mengembangkan sistem pengelolaan surat digital berbasis web menggunakan metode Waterfall, yang mencakup tahap analisis kebutuhan, perancangan, implementasi, dan pengujian. Pengujian sistem dilakukan menggunakan metode black-box untuk memastikan bahwa setiap fungsi berjalan sesuai spesifikasi. Hasil implementasi menunjukkan peningkatan efisiensi pelayanan surat, dengan waktu pemrosesan berkurang dari 30–60 menit menjadi hanya 5–15 menit per pengajuan. Selain itu, tingkat akurasi data meningkat karena sistem otomatisasi meminimalisasi kesalahan input. Sistem ini juga meningkatkan transparansi dengan menyediakan pelacakan status surat secara real-time bagi pengguna. Secara keseluruhan, penerapan sistem ini menjadi langkah konkret menuju transformasi digital desa yang lebih efisien, transparan, dan responsif, mendukung konsep smart village yang adaptif terhadap perkembangan teknologi informasi.
Deteksi Penyakit Daun Tomat Real-Time pada Platform Android Berbasis Convolutional Neural Network Nova Rahmawati, Eprisa; Pinandita, Tito; Ayu Fitriani, Maulida; Ambar Pambudi, Elindra
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 8 (2025): JPTI - Agustus 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.964

Abstract

Tanaman tomat (Solanum lycopersicum) merupakan komoditas hortikultura dengan kerentanan tinggi terhadap infeksi patogen pada daun, berdampak signifikan pada kualitas dan produktivitas. Identifikasi dini penyakit daun tomat menjadi krusial untuk mencegah kerugian ekonomi, namun metode konvensional secara visual dinilai kurang efektif karena bersifat subjektif dan membutuhkan waktu lama. Penelitian ini bertujuan mengembangkan aplikasi mobile untuk mengidentifikasi penyakit daun tomat secara real-time, akurat, dan dapat mengetahui hasil langsung di lokasi penanaman. Sistem dikembangkan menggunakan pendekatan CNN dengan arsitektur MobileNetV2V2 yang di optimasi untuk perangkat mobile. Model dilatih menggunakan 9.600 citra daun tomat mencakup enam kategori penyakit, dikonversi ke format ONNX dan diimplementasikan ke platform Android melalui Unity dengan framework Barracuda. Evaluasi model menunjukkan performa yang sangat baik dengan akurasi pelatihan 95%. Pengujian pada 60 sampel di lingkungan nyata menghasilkan akurasi deteksi real-time 88,33%, dengan precision 87,5%, recall 88,3%, dan F1-score 87,9%. Aplikasi ini menawarkan solusi praktis bagi petani untuk identifikasi penyakit tanpa bergantung pada koneksi internet, memungkinkan penanganan dini yang tepat, mengurangi penggunaan pestisida berlebihan, dan berpotensi meningkatkan produktivitas tanaman tomat melalui pengendalian penyakit yang lebih efektif.
Implementasi Perpustakaan Digital untuk Meningkatkan Minat Baca Siswa di SDN 3 Cikoneng Firdaus, Rizqi Muhammad; Pinandita, Tito
VISA: Journal of Vision and Ideas Vol. 4 No. 2 (2024): VISA: Journal of Vision and Ideas (In Press)
Publisher : IAI Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/visa.v4i2.3409

Abstract

Reading interest is an important aspect for students' intellectual and academic development at the primary school level. However, in some elementary schools, including SDN 3 Cikoneng, students' interest in reading tends to be lacking or declining. Especially in the era of rapid development of information and communication technology, utilizing information and communication technology is one of the solutions to increase students' reading interest by implementing a digital library. The purpose of this research is to design and implement a digital library at SDN 3 Cikoneng as a means to increase student interest in reading. This digital library can be accessed easily and quickly to various learning resources in digital form. The system is designed and developed with the Waterfall model with stages including Requirements Analysis, System Design, Implementation, Testing, and Maintenance. The results of this study indicate that the digital library has begun to increase student interest in reading at SD Negeri 3 Cikoneng, because it is undeniable that now students use cellphones more than their books. Through the digital library, it will be easier for students to read material books anytime and anywhere. So it is hoped that the use of digital libraries can increase student interest in reading more effectively and efficiently.
Co-Authors . Suwarsito Achmad Fauzan, Achmad Agung Purwo Wicaksono Ahmad Ahmad Ainun Rahmawati Ambar Pambudi, Elindra Annisa Dwi Risqi Ardhine Attafaqquf Ayu Fitriani, Maulida Aziz, Hilmi Feri Wibowo Firdaus, Rizqi Muhammad Hidayat, Arif Lukman Hidayat, Arif Lukman Himawan, Hidayatulloh Hindayati Mustafidah Joko Siswanto Juanita Juanita Kusuma, Fajar Budi Muhammad Iman Nur Hakim Nova Rahmawati, Eprisa Prasetyo, Ilham Bagus Purnomo Purnomo Putra, Nanda Dwi Rizky Ridwan Supriyono Supriyono Suwarti Suwarti Syah, Hendar Ivan Untung Rahardja Verdiatmoko, Ardief Candra