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All Journal Lontar Komputer: Jurnal Ilmiah Teknologi Informasi Jurnal Teknik Teknosains: Media Informasi Sains dan Teknologi JUITA : Jurnal Informatika JURNAL INSTEK (Informatika Sains dan Teknologi) Jambura Journal of Informatics Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat Aptisi Transactions on Technopreneurship (ATT) Jurnal Teknologi Dan Sistem Informasi Bisnis Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Informatika (JUTIF) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Proceedings Series on Physical & Formal Sciences Automotive Experiences Jurnal Teknoif Teknik Informatika Institut Teknologi Padang The Indonesian Journal of Computer Science Research Inspiration: Jurnal Teknologi Informasi dan Komunikasi Jurnal Sains, Nalar, dan Aplikasi Teknologi Informasi
Joko Siswanto
Politeknik Keselamatan Transportasi Jalan
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Parameter Tuning dalam Klasifikasi Load Factor pada Bus Rapid Transit (BRT) Hakim, Muhammad Iman Nur; Siswanto, Joko; Anggari Nuryono, Aninditya
JURNAL FASILKOM Vol. 14 No. 2 (2024): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v14i2.7258

Abstract

Public transport services are facing more challenges and some problems are gradually emerging with the increase in public transport users and varying travel demands. BRT as a type of public transportation in determining efficiency, service feasibility, and determining operational costs refers to the load factor. BRT bus load factor classification using KNN is proposed with parameter tuning to increase accuracy values. KNN algorithm with tuning parameters on 2 types of matrices (Minkowski and Euclidean) for BRT load factor classification for Transjatim corridor 1. The BRT load factor classification with the KNN algorithm increased by 7.81% by tuning parameters on the Euclidean matrix compared to the Minkowski matrix. The increase in accuracy is reflected in the confusion matrix with changes in increasing true negatives and decreasing false positives. Category 1 has a higher class than category 2 for boarding and alighting passengers. The classification presented can be a reference for Transjatim Corridor 1 Managers in determining efficiency, feasibility and operational costs.
INDUKSI KESELAMATAN PENUMPANG ANGKUTAN UMUM BUS MENGGUNAKAN APLIKASI BERBASIS WEB Febrianta, Arjuna Rizky; Siswanto, Joko; Oktopianto, Yogi
Jurnal INSTEK (Informatika Sains dan Teknologi) Vol 9 No 2 (2024): OCTOBER
Publisher : Department of Informatics Engineering, Faculty of Science and Technology, Universitas Islam Negeri Alauddin, Makassar, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/instek.v9i2.48283

Abstract

Risiko bahaya yang besar terhadap penumpang angkutan umum bus disebabkan pelayanan induksi keselamatan yang masih kurang. Aplikasi berbasis website yang berisi informasi dan video tentang induksi keselamatan penumpang angkutan umum bus di PO. New Shantika dibangun dengan menggunakan metode pengembangan ADDIE (analyze, Design, Development, Implementation, Evaluation). Metode IPA (Importance Perfomance Analysis) digunakan untuk menganalisis kebutuhan, storyboard dan UML digunakan untuk melakukan perancangan, capcut dan wordpress digunakan untuk pengembangan, dan metode SUS (System Usability Scale) digunakan untuk pengevaluasian. Analisis kebutuhan dengan IPA menghasilkan 8 indikator pada kuadran 1 dan 1 indikator pada kuadran 2 yang tersaji pada diagram kartesius. Aplikasi yang dibangun berisi tentang 9 penjelasan dan video induksi keselamatan. Pengujian aplikasi menggunakan SUS mendapatkan nilai rata-rata sebesar 74,7(B) yang berarti penumpang sebagai pengguna menerima penggunaan aplikasi yang dibangun. Aplikasi yang dibangun dapat dimanfaatkan sebagai upaya peningkatan keselamatan penumpang angkutan umum bus.
HEALTH SERVICE QUALITY VALUES OF PRIMARY CLINIC USING EPARTICIPATION SERVICE QUALITY ASSESSMENT Siswanto, Joko; Lisangan, Erick Alfons; Zaenudin, Zaenudin
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 3 (2023): JUTIF Volume 4, Number 3, June 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.3.934

Abstract

The use of technology to manage participation in the quality of health services needs to be carried out to produce relevant, valid and accurate assessments of service quality. Not all Primary Clinics have health service quality standards and quality evaluation data for participation services using information technology (via electronic media). This is crucial for evaluating clinic development, upgrading the status to Main Clinic, and improving the service quality. The methodology used adopts the eParticipation framework with the stages of Areas of Participation (determining the main areas of participation), Category of Tools (determining the categories of ICT support tools), and Technology (determining ICT support technologies). The participation area is limited to Primary Clinic patients who act as participants of 1,308 people. 14 elements with a total of 33 detailed elements are the basic elements for assessing service quality. Application of eParticipation SQA website-based is used to manage and present the results of service quality assessments by Primary Clinic Managers. The highest average service quality assessment is in the answers to Good (62%), the Worse and Poor options are minimized, and the options of Good and Very Good are maximized. The technology required consists of software, hardware, and network devices. The application is supported by Manager and is used easily, quickly, and precisely.
Design and Build The Dokestrans Application For Document Management of The Perum Damri Safety Management System Moh. Adam Asshofi; Joko Siswanto; Nurul Fitriani
Inspiration: Jurnal Teknologi Informasi dan Komunikasi Vol. 14 No. 2 (2024): Inspiration: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Pusat Penelitian dan Pengabdian Pada Masyarakat Sekolah Tinggi Manajemen Informatika dan Komputer AKBA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35585/inspir.v14i2.90

Abstract

The Safety Management System (SMK) documents at the Public Transportation Company (PAU) Perum Damri are currently stored using Google Drive, leading to inefficiencies such as document loss, difficulty in locating specific files, and disorganized storage. These challenges hinder the effective compilation and management of SMK PAU documents, potentially impacting safety and compliance standards. To address these issues, the "Dokestrans" archiving system was developed as a comprehensive document management solution using the 4D methodology, which includes definition, design, development, and dissemination phases. The Dokestrans system streamlines document organization, provides graphical reports of documents collected per year or per element, and issues notifications for deficiencies in sub-elements, ensuring timely updates and compliance. Usability testing using the System Usability Scale (SUS) yielded an average score of 86, indicating excellent user satisfaction, while Blackbox testing confirmed the validity of all features. The implementation of Dokestrans significantly improves efficiency, accuracy, and organization in managing SMK PAU documents, contributing to enhanced safety management and operational effectiveness for public transportation companies.
Predicting the Number of Passengers in Public Transportation Areas Using the Deep Learning Model LSTM Joko Siswanto; Sri Yulianto Joko Prasetyo; Sutarto Wijono; Evi Maria; Untung Rahardja
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi Vol 15 No 03 (2024): Vol.15, No. 3 December 2024
Publisher : Institute for Research and Community Services, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/LKJITI.2024.v15.i03.p03

Abstract

Accurate predictions of the number of public transport passengers on buses in each region are crucial for operations. They are required by the planning and management authority for bus public transport. A deep learning-based LSTM prediction model is proposed to predict the number of passengers in 4 bus public transportation areas (central, north, south, and west), evaluated by MSLE, MAPE, and SMAPE with dropout, neuron, and train-test variations. The CSV dataset obtained from Auckland Transport(AT) New Zealand metro patronage report on bus performance(1/01/2019-31/07/2023) is used for evaluation. The best prediction model was obtained from the lowest evaluation value and relatively fast time with a dropout of 0.2, 32 neurons, and train-test 80-20. The prediction model on training and testing data improves with the suitability of tuning for four predictions for the next 12 months with mutual fluctuations. The strong negative correlation is central-south, while the strong positive correlation is north-west. Predictions are less closely interconnected and dependent, namely central-south. With its potential to significantly impact policy-making, this prediction model can increase public transport mobility in each region, leading to a more efficient and accessible public transport system and ultimately enhancing the public's daily lives. This research has practical implications for public transport authorities, as it can guide them in making informed decisions about service planning and resource allocation.
Metode AHP Untuk Sistem Pendukung Keputusan Sekolah Sadar Lalu Lintas Joko Siswanto; I Made Suartika; Rahadian Satya Mahaddhi
JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Vol 5 No 1 (2024)
Publisher : SOTVI - Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/jitsi.5.1.222

Abstract

Traffic conscious school covers various aspects that influence the effectiveness and accuracy of traffic education program evaluation. A structured and comprehensive approach is needed involving all stakeholders to update and adapt the traffic conscious school strategy to suit needs and developments. DSS is proposed to support traffic conscious school decisions using the website based AHP method. DSS was built adopting the XP Model with planning, design, coding and testing stages. Planning consists of functional and non functional requirements. The design contains application designs and AHP calculation designs with a CR value of 0,04 for 5 criteria 4 sub criteria, which means they are consistent. The highest priority value is 048 for the teacher and human environment criteria, while the lowest is for the object environment criteria. The test results show there is no difference between manual calculations and the proposed system. DSS can support stakeholder decisions to adopt traffic conscious school policies and strategies.
Predicting Transjakarta Passengers with LSTM-BiLSTM Deep Learning Models for Smart Transportpreneurship Siswanto, Joko; Hendry, Hendry; Rahardja, Untung; Sembiring, Irwan; Lisangan, Erick Alfons
Aptisi Transactions On Technopreneurship (ATT) Vol 7 No 1 (2025): March
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v7i1.440

Abstract

Travel pattern variations pose challenges in building a prediction model that accurately captures seasonal patterns or precision of BRT passenger numbers. An approach that integrates sophisticated prediction algorithms with high accuracy is needed to address the Transjakarta BRT passenger number prediction model problem. The proposed prediction model with the best accuracy is sought using deep learning on 8 models. The prediction model is used for short-term and long-term predictions, as well as looking for correlations in the prediction results of 13 Transjakarta corridors. The Python programming language with the Deep Learning Tensor Flow framework is run by Google Colaboratory used in the prediction simulation environment. The combination of BiLSTM-CNN was found to have the best accuracy of the evaluation value (SMAPE = 15.9387, MAPE = 0.598, and MSLE = 0.0425), although it has the longest time (134 seconds). Fluctuations in short-term predictions of passenger numbers evenly occur simultaneously across all corridors. Fluctuations in long-term predictions evenly occur simultaneously across all corridors, except in February. There is no negative correlation in the 13 prediction results and there are 8 corridors that have a close positive correlation. The prediction results can be used by transportation operators and the government to optimize resource planning and transportation policies to support sustainable community and economic mobility.
Optimalisasi Kinerja Ruas Jalan Dengan Metode PKJI 2023 dan Aplikasi PTV Vissim Pratma, Najwan; Aprianto, Rizal; Siswanto, Joko
Jurnal Teknik Vol 23 No 1 (2025): Jurnal Teknik
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37031/jt.v23i1.607

Abstract

The suboptimal performance of road segments is a major issue in the transportation system that causes congestion and a decrease in mobility efficiency. Kaliurang Road in Sleman Regency has poor road performance, resulting in disrupted inter-regional connectivity. Optimization of road segment performance is proposed through performance analysis and traffic engineering scenario simulation. PKJI 2023 is used to analyze performance and PTV Vissim 2025 is used for simulating the testing of 30 optimization scenarios. Data was collected through direct surveys and documentation from the Transportation Department. Simulation validation uses GEH for vehicle volume and MAPE for speed with an analysis of five variables (vehicle speed, travel time, vehicle density, occupancy rate, and relative delay). Scenario 30, with a combination of lane additions, road widening, removal of on-street parking, one-way systems, and vehicle type hour restrictions, resulted in the best optimization with an 11.57% increase in speed, a 30.93% reduction in travel time, a 67.74% reduction in density, a 64.76% reduction in occupancy rate, and a 92.66% reduction in relative delay. The optimization results can be used as a strategic step for stakeholders in formulating policies to improve road segment performance to support sustainable inter-regional connectivity.
Aplikasi induksi keselamatan alat survei inspeksi keselamatan jalan Prasetiyo, Wahyu Jati; Siswanto, Joko; Oktopianto, Yogi
Teknosains Vol 18 No 3 (2024): September-Desember
Publisher : Fakultas Sains dan Teknologi Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/teknosains.v18i3.48822

Abstract

Pelaksanaan survei inspeksi keselamatan jalan (IKJ) tidak lepas dari kemungkinan terjadinya kecelakaan kerja dari kendaraan yang lewat maupun pengguna jalan yang melintas. Pelaksanaan survei IKJ memiliki risiko tinggi dikarenakan kurangnya pemahaman induksi keselamatan survei. Pengembangan sistem induksi keselamatan melalui video berbasis aplikasi. Pembuatan aplikasi  menggunakan metode Rapid Application Development (RAD) dengan tahapan perencanaan, workshop desain, implementasi. Perencanaan aplikasi induksi keselamatan meliputi perangkat lunak (XAMPP, Visual Studio Code, Google Chrome, dan MySQL) dan perangkat keras (Laptop Acer Nitro 5, kamera iPhone 11). Workshop desain menghasilkan rancangan tampilan video berupa storyboard dan aplikasi menggunakan Unfied Modelling Language (UML). Aplikasi induksi keselamatan bisa diakses kapanpun dan di manapun oleh para surveyor. Pengujian aplikasi dengan metode SUS dan mendapat hasil 77 dan memenuhi syarat. Pengembangan aplikasi induksi keselamatan berbasis aplikasi dapat mengurangi risiko kecelakaan yang disebabkan karena kurangnya informasi dan edukasi pekerja tentang kesehatan dan keselamatan.
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.
Co-Authors Adi Setiawan Ainun Rahmawati Alfianti, Pramesti Gita Anas Azhimi Qalban Anggari Nuryono, Aninditya Aprianto, Rizal Bagus Ikapraja Benny Hamdi Rhoma Putra Brasie Pradana Sela Bunga Riska Ayu Erick Alfons Lisangan Evi Maria Febrianta, Arjuna Rizky Frans Tohom Hariani Hariani Hendry Humami, Faris I Made Suartika Immanuel, Candra Great Irianti, Faizah Irwan Sembiring Iwan Setyawan Joko Siswanto Lestari, Astri Mifta, Eka Moh. Adam Asshofi Mohamad, Ar Rofiqi Muhammad Iman Nur Hakim Mustaqbal, Zhilal Akbar Nurul Fitriani Pramesti, Meisya Nira Prasetiyo, Wahyu Jati Prasetyo, Ilham Bagus Pratma, Najwan Putra, Nanda Dwi Putro, Dimas Nugroho Rahadian Satya Mahaddhi Ramadhan Dwi Prasetyo Siti Shofiah Sri Nilawaty Lahay Sri Yulianto Joko Prasetyo Sugiyanto, Mohammad Ibrahim Suprapto Hadi Sutarto Wijono Syaban, Alfath Satria Negara Tito Pinandita Tri Susila Hidayati Tsani, Mokhammad Rifqi Untung Rahardja Untung Rahardja Varadinta, Salsabilla Widyaningrum, Shiska Wahyu Yoga, Mahendra Yogi Oktopianto Zaenudin Zaenudin