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All Journal Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) International Journal of Health, Engineering and Technology Jurnal Teknik Informatika dan Teknologi Informasi
Dendi Putra Prakoso
Universitas Amikom Purwokerto
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Education Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Mechanical Engineering Medicine & Pharmacology Nursing Public Health Veterinary

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Prediksi Preferensi Peserta Event Marathon terhadap Kategori Lomba menggunakan Algoritma Machine Learning Dominic Dinand Aristo; Satria Dwi Nurwicaksana; Dendi Putra Prakoso; M Afrian Maulana; Nurfaizah Nurfaizah
Jurnal Teknik Informatika dan Teknologi Informasi Vol. 5 No. 1 (2025): April: Jurnal Teknik Informatika dan Teknologi Informasi
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jutiti.v5i1.5364

Abstract

Marathons are becoming an increasingly popular form of exercise and social interaction. Participants who choose race categories based on the mileage provided, such as 6K, 7.9K, and 11K, according to personal preference. However, this category selection has not been analyzed based on participant characteristics, even though this information is important for organizers to support promotional strategies, and segmentation of participants. This study aims to predict marathon category selection based on demographic characteristics, namely age and gender, by applying Decision Tree and Random Forest machine learning algorithms. The dataset used is primary data from two events, namely RSDK Berlari with a total of 1091 data and Skybridgefunrun with 1519 data. The results show that the Decision Tree algorithm gets an accuracy of 56.81%, and the Random Forest algorithm is 57.38%. With these results, it shows that the Random Forest algorithm has higher accuracy than the Decision Tree algorithm, with accuracy reaching 57.38%. However, the model tends to be biased towards the 7.9K category, with recall reaching 94%, while the 6K and 11K categories are very low. Then, feature importance analysis shows that the most influential factor on category selection is age, while gender is smaller. This research provides insight for event organizers in designing promotional strategies and participant segmentation more precisely.
Arsitektur Sistem Streaming Efisiensi Tinggi: Integrasi Hardware dan Manajemen Jalur Konektivitas dalam Produksi Podcast Dendi Putra Prakoso; Dhanar Intan Surya Saputra
Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Vol. 5 No. 1 (2026): Juni 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v5i1.1061

Abstract

Perkembangan teknologi digital telah mendorong peningkatan popularitas podcast sebagai media komunikasi, hiburan, dan edukasi. Produksi podcast modern tidak hanya memerlukan kualitas audio dan video yang baik, tetapi juga sistem streaming dan recording yang efisien dan stabil. Penelitian ini membahas arsitektur sistem streaming efisiensi tinggi melalui integrasi perangkat keras (hardware) dan jaringan komputer (networking) dalam proses produksi podcast. Metode yang digunakan berupa studi literatur dan analisis implementasi sistem streaming berbasis komputer multi-perangkat. Hasil penelitian menunjukkan bahwa arsitektur dual-PC dengan manajemen routing antarmuka (HDMI, PCIe, USB) dapat mendistribusikan beban kerja secara efisien tanpa mengurangi kualitas produksi.Integrasi antara perangkat capture, audio interface, encoder, dan manajemen bandwidth menjadi faktor utama dalam menciptakan sistem produksi podcast yang optimal dan hemat sumber daya.
Spatial Validation Analysis And Prediction Of Service Reach Of Trans Banyumas Purwokerto-Banyumas Corridor 4 Ahead Of Operation In January 2026 Dendi Putra Prakoso; Purwadi Purwadi
International Journal of Health Engineering and Technology Vol. 4 No. 5 (2026): IJHESS JANUARY 2026
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55227/ijhet.v4i5.525

Abstract

The expansion of Trans Banyumas services through Corridor 4 to the Banyumas area has entered the final stage with an operational schedule set for January 1, 2026. This study conducted a pre-operational evaluation to validate route readiness and predict service coverage using Geographic Information Systems (GIS). By modeling the route along the Bulupitu Purwokerto Terminal to Banyumas Terminal which includes 49 Bus Stops (TPB), the analysis used QGIS 3.40.11 with Network Analysis and Service Area Analysis methods. The results show that the route has high efficiency with an estimated travel time of 45-60 minutes. Service Area analysis with a radius of 400 meters confirmed that the TPB is able to cover 6 major hospitals, 8 educational institutions, and all major tourist destinations in the Old Town of Banyumas. Spatial validation concluded that the route is very feasible for operation, with high potential to support the revitalization of heritage areas and the integration of public transportation in the Greater Banyumas area
Co-Authors Dhanar Intan Surya Saputra Dominic Dinand Aristo M Afrian Maulana Nurfaizah Purwadi Purwadi Satria Dwi Nurwicaksana