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"Penelitian mengenai perancangan desain kemasan transportasi buah salak menggunakan metode QFD sebagai salah satu usaha untuk mengembangkan kemasan yang disesuaikan terhadap keinginan konsumen. QFD digunakan untuk mengumpulkan dan menganalisa kebutuhan kemasan buah salak ini. Metode yang digunakan meliputi tingkat kepentingan, kepuasan serta harapan yang diinginkan oleh konsumen terhadap produk yang akan dikembangkan. Penelitian ini bertujuan untuk menghasilkan kemasan transportasi buah salak yang baik dan tepat. Selain itu dari perancangan ini memilih jenis bahan yang tepat untuk dapat memenuhi aspek teknis yang diinginkan konsumen serta standar dimensi untuk mendapatkan pengangkutan yang optimal.

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Research on snakefruit transportation packaging design using QFD design as an attempt to develop packaging as consumers wish for. QFD is used to collect and analyze the snakefruit packaging necessity. Methode is used comprises level of significance, satisfaction and wishes of consumer over the product that is being developed. This research aims to result well and appropriate snakefruit transportation packaging. Other than that, based on this research, it can be determined correct type of material to meet the technical aspect consumers desire, and dimension standard in order to optimalize the carriage."

"Pengiriman barang merupakan salah satu kegiatan umum masyarakat yang semakin sering dilakukan akibat peningkatan pengguna sarana belanja dalam jaringan (daring). Peningkatan kegiatan belanja daring mengakibatkan permintaan terhadap jasa pengiriman barang juga mengalami peningkatan. Hal ini juga berdampak pada meningkatnya masalah pengiriman barang terkait masalah lingkungan seperti meningkatnya polusi udara dan juga efisiensi pengiriman barang. Oleh karena itu, dibutuhkan suatu solusi untuk mengatasi masalah lingkungan serta menambah efisiensi pengiriman barang di tahap terakhirnya. Penelitian ini berfokus pada tahap last-mile delivery, yaitu tahap barang dikirimkan dari depot terakhir ke lokasi pelanggan dengan memanfaatkan penggunaan truk pengiriman dan digabung dengan drone. Kombinasi truk dan drone dipandang sebagai solusi yang inovatif. Drone yang menggantikan pengiriman dengan kendaraan bermotor tidak menghasilkan polusi yang biasanya dihasilkan oleh kendaraan berbahan bakar minyak bumi. Kemacetan juga dapat dihindari oleh drone sehingga waktu pengiriman bisa dipersingkat. Drone dapat dengan mudah melakukan pengiriman ke tempat-tempat yang tidak bisa dijangkau oleh kendaraan pengirim barang seperti truk. Dibalik semua kelebihannya, drone memiliki beberapa kendala yaitu harganya yang mahal sehingga menimbulkan keterbatasan kesediaan drone dan juga keterbatasan jangkauan terbangnya. Metode clustering diperkenalkan untuk mengatasi batasan tersebut. Pada penelitian ini digunakan metode Hierarchical Agglomerative Clustering (HAC) dengan mempertimbangkan jumlah drone yang tersedia dan jangkauan terbang maksimum dari drone. Hasil pengelompokkan kemudian digunakan untuk mencari rute optimal dengan metode Tabu Search (TS). Kedua metode ini diimplementasikan pada data simulasi sebanyak 90 pelanggan. Biaya pengiriman yang terdiri dari biaya operasional drone, biaya operasional truk, biaya penggunaan drone serta biaya penggunaan truk akan diminimalkan. Hasil berupa biaya pengiriman, jarak tempuh serta waktu tempuh yang diperoleh dibandingkan dengan hasil dari clustering data berdasarkan jarak tanpa memaksimalkan penggunaan drone serta memperhatikan batasannya. Implementasi HAC dan TS memberikan hasil pengurangan waktu sekitar 45%, pengurangan jarak sekitar 70% dan pengurangan biaya pengiriman sekitar 9%.

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Goods delivery is a common activity in the society, and it’s becoming more frequent with the existence of online shopping. The surge in online shopping has led to a heightened demand for delivery services. This increase in demand impacts environmental concerns such as escalating air pollution and the efficiency of parcel delivery. Consequently, there’s a need for a solution to address environmental issues and enhance the efficiency of last-mile delivery. This research focuses on the last-mile delivery stage, specifically the movement of goods from the final depot to the customer’s location, utilizing a combination of delivery trucks and drones. The integration of trucks and drones is seen as an innovative solution. Drones, replacing motor vehicles in delivery, reduce pollution typically generated by fossil fuel-powered vehicles. Additionally, drones can evade traffic congestion, shortening delivery times, and easily access locations inaccessible to trucks. However, despite their advantages, drones have constraints, including high costs leading to limited availability and flight range limitations. Clustering methods are introduced to address these constraints. This study employs the Hierarchical Agglomerative Clustering (HAC) method, considering the available number of drones and their maximum flight range. The resulting clusters are then utilized to determine the optimal routes using the Tabu Search (TS) method. Both of this method is implemented on a simulation data of 90 customers. Delivery cost that includes drone operational cost, truck operational cost, drone cost, and truck cost is minimized. The result (delivery cost, distance traveled, and duration) are compared to clustering based on distance only without maximized drones available or consider its constraints. The implementation of HAC and TS provides a reduction in time of around 45%, a distance reduction of about 70%, and a shipping cost reduction of about 9%."

"Salah satu tantangan yang kita hadapi saat ini adalah menghubungkan kinerja keberlanjutan proyek infrastruktur dengan SDGs. Insinyur sipil perlu memiliki alat yang praktis untuk menilai dampak pada proyek yang layak untuk kemudian dilakukan pengambilan tindakan terkait sustainabilitas. Saat penelitian ini dibuat, masih belum ada kerangka penilaian sustainabilitas yang berbasis SDGs yang secara khusus diarahkan untuk mengevaluasi proyek infrastruktur transportasi. Penelitian ini bertujuan untuk mengisi kesenjangan tersebut dengan mengusulkan kerangka sistem untuk menilai dampak infrastruktur transportasi pada tahap perencanaan serta mengembangkan model machine learning yang mampu memprediksi hasil penilaian berdasarkan indikator dari kerangka yang diberikan. Melalui serangkaian studi literatur, diusulkan kerangka sistem penilaian dengan 15 indikator yang merepresentasikan empat pilar sustainabilitas, sosial, ekonomi, lingkungan, dan institusional. Indikator merefleksikan 25 target dari 12 tujuan SDGs. Berdasarkan pembobotan indikator dengan metode Analytic Hierarchy Process, didapatkan indikator persentase pekerja disabilitas memiliki bobot kepentingan terbesar, yaitu 8.08%, dan indikator jumlah pengaduan yang diajukan oleh masyarakat setempat memiliki bobot kepentingan terkecil sebesar 5.30%. Indikator sosial memiliki tingkat kepentingan yang paling tinggi, dilanjutkan dengan indikator lingkungan, ekonomi, dan institusional. Model machine learning yang dihasilkan menggunakan tiga algoritma pengklasifikasi, Naïve Bayes, ANN/Deep Learning, dan Decision Tree. Model dengan algoritma Naïve Bayes memiliki akurasi sebesar 64.7%, algoritma ANN/Deep Learning memiliki akurasi sebesar 86.7%, dan algoritma Decision Tree memiliki akurasi sebesar 75.3%.

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One of the challenges we face today is linking the sustainability performance of infrastructure projects with the SDGs. Civil engineers need to have a viable practical tool for assessing impacts on a project to be able to take sustainable actions. At the time this research was conducted, there was no framework for SDG-based sustainability assessment that was specifically directed at evaluating transportation infrastructure projects. This study aims to fill this gap by proposing a system framework to assess the impact of transportation infrastructure at the planning stage and develop a machine learning model that can predict the results of the assessment based on indicators from the given framework. Through a series of literature studies, a scoring system framework with 15 indicators is proposed, representing the four pillars of sustanability, social, economic, environmental, and institutional. The indicators reflect 25 targets of the 12 SDGs goals. Based on the weighting of the indicators using the Analytic Hierarchy Process method, it was found that the percentage of disabled workers indicator has the largest importance weight, which is 8.08%, and the indicator of the number of complaints submitted by the local community has the lowest importance with a weight of 5.30%. Social indicators have the highest importance, followed by environmental, economic, and institutional indicators. The resulting machine learning model uses three classifier algorithms, Naïve Bayes, ANN/Deep Learning, and Decision Tree. The model with Naïve Bayes algorithm has an accuracy of 64.7%, the ANN/Deep Learning model has an accuracy of 86.7%, and the Decision Tree model has an accuracy of 75.3%."

"Pada masa sekarang permasalah penentuan rute kendaraan merupakan keadaan yang harus diperhitungkan dalam bisnis pengiriman. Dalam logistic permasalah penentuan rute kendaraan memiliki peranan kunci bagi perusahaan guna meminimalisir biaya transportasi, biaya penalti atas keterlambatan, dan meningkatkan kualitas layanan pada pengiriman. Permasalahan ketepatan waktu dalam proses pengiriman pada saat sekarang ini. Penelitian ini berpusat pada pengoptimalan biaya bahan bakar dan pinalti. Dalam makalah ini nantinya penulis memakai Vehicle Routing Problem with Time Windows (VRPTW). Dimana VRPTW sendiri merupakan masalah penentuan rute kendaraan yang paling banyak dibahas dalam  dunia nyata. Algoritma Artificial Bee Colony (ABC) dan Algoritma Camel (CA) akan diterapkan dalam penelitian ini. Selanjutnya kedua algoritma akan dilihat mana dari kedua algoritma yang paling ideal untuk penyelesaian permasalahan penentuan rute dalam VRPTW.

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At present The problem of determining vehicle routes is a condition that must be taken into account in the shipping business. In logistics, the problem of determining vehicle routes has a key role for companies to minimize transportation costs, penalty fees for delays, and improve service quality on delivery. The problem of timeliness in the delivery process at this time. This research focuses on optimizing fuel costs and penalties. In this paper, the author will use the Vehicle Routing Problem with Time Windows (VRPTW). Where VRPTW itself is the problem of determining vehicle routes that are most widely discussed in the real world. Artificial Bee Colony Algorithm (ABC) and Camel Algorithm (CA) will be applied in this research. Furthermore, the two algorithms will determine which of the two algorithms is the most ideal for solving the problem of determining routes in VRPTW."

"Vehicle Routing Problem (VRP) merupakan salah satu model yang dapat mengatasi permasalahan rute distribusi. Salah satu permasalahan yang ada di dunia nyata adalah rute distribusi kantong darah di UDD PMI DKI Jakarta. UDD PMI DKI Jakarta harus mengirim kantong darah setiap harinya menuju lima UDD PMI masing-masing kota di Provinsi DKI Jakarta. Adanya durasi shelf life darah dan kapasitas mobil yang terbatas membuat permasalahan ini berkembang menjadi Capacitated Vehicle Routing Problem with Time Windows (CVRPTW). Dengan menggunakan software Gurobi, terbukti bahwa rute distribusi masih bisa dioptimasi. Di mana rute awal memerlukan waktu selama 1.034 menit, dan rute hasil optimasi memerlukan waktu selama 707 menit. Pengurangan waktu yang didapat adalah 31,6%, dengan tetap memenuhi kendala lainnya, seperti kapasitas kendaraan dan durasi shelf life kantong darah. Analisis sensitivitas juga dilakukan untuk mengetahui apakah model dapat dipakai dengan fluktuasi permintaan kantong darah yang merepresentasikan kondisi sebenarnya. Dari hasil optimasi menggunakan tiga skenario, didapat bahwa terdapat perubahan durasi perjalanan dan penambahan jumlah kendaraan yang dipakai, serta perubahan rute yang dipilih oleh setiap kendaraan.

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The Vehicle Routing Problem (VRP) is a model that addresses distribution route issues. One real-world problem is the distribution of blood bags at UDD PMI DKI Jakarta. UDD PMI DKI Jakarta needs to deliver blood bags daily to five UDD PMI located in each city in DKI Jakarta. The presence of limited blood shelf life duration and vehicle capacity has led to the development of the Capacitated Vehicle Routing Problem with Time Windows (CVRPTW) for this problem. By using Gurobi software, it has been proven that the distribution routes can be optimized. The initial route took 1.034 minutes, while the optimized route took 707 minutes. This resulted in a time reduction of 31,6%, while still meeting other constraints such as vehicle capacity and blood bag shelf life duration. Sensitivity analysis was also conducted to assess whether the model can be used with blood bag demand fluctuations that represent real-world conditions. From the optimization results using three scenarios, it was found that there were changes in travel duration, an increase in the number of vehicles used, and changes in the selected routes for each vehicle."

"[ABSTRAKPenelitan ini bertujuan untuk memberikan usulan perbaikan terhadappemenuhan permintaan perbaikan karoseri pada sebuah perusahaan transportasi diIndonesia. Penelitian ini berfokus pada permasalahan tidak terpenuhinyapermintaan perbaikan pada pabrik perbaikan karoseri di salah satu perusahaantransportasi di Indonesia. Perusahaan ini mendapatkan permintaan dari sembilanpool yang tersebar di Jakarta dan Jawa Barat. Sehingga membuat permintaanperbaikan karoseri yang semakin bertambah. Oleh karena itu diperlukan sebuahperbaikan pada proses produksi di PT Primajasa Perdanarayautama. Metode yangdigunakan dalam penelitian ini adalah DMAIC (Define, Measure, Analyze,Improve, dan Control) untuk mendapatkan solusi yang terbaik untuk dapatdiimplementasi. Penelitian ini akan berfokus pada proses painting yang terbagimenjadi enam aktifitas besar, yaitu pembersihan pelat, efoxy primer,pendempulan, cat/painting, vernis dan finishing. Perbaikan yang dilakukan akanmemberikan dampak terhadap waktu proses produksi pada pabrik perbaikankaroseri ini yang akan meningkatkan angka pemenuhan permintaan.ABSTRACTThis research aims to propose improvements for achieving thedemand for carrosserie repair for a transportation company in Indonesia. Thefocus of this research is about the backlog of demand from its carrosserie repairfactory in one of the transportion company in Indonesia. This company has 9pools which are spread throughout Jakarta and West Java, the demand came fromthese pools this is why the level of demand is high and the reason that this factoryneeds an improvement to fulfill its demand. DMAIC (Define, Measure, Analyze,Improve, and Control) is the method used in this research, in order to get the bestoutput that is going to be implemented in this company. Painting process is goingto be the focus of this research, painting process is separated into six big subactivitieswhich are metal cleansing, primer efoxy, putty, painting, and finishing.The improvements that are going to be made is going to have impact on itsproduction process duration which will lead to fulfillment of this company?sdemand.;This research aims to propose improvements for achieving thedemand for carrosserie repair for a transportation company in Indonesia. Thefocus of this research is about the backlog of demand from its carrosserie repairfactory in one of the transportion company in Indonesia. This company has 9pools which are spread throughout Jakarta and West Java, the demand came fromthese pools this is why the level of demand is high and the reason that this factoryneeds an improvement to fulfill its demand. DMAIC (Define, Measure, Analyze,Improve, and Control) is the method used in this research, in order to get the bestoutput that is going to be implemented in this company. Painting process is goingto be the focus of this research, painting process is separated into six big subactivitieswhich are metal cleansing, primer efoxy, putty, painting, and finishing.The improvements that are going to be made is going to have impact on itsproduction process duration which will lead to fulfillment of this company?sdemand.;This research aims to propose improvements for achieving thedemand for carrosserie repair for a transportation company in Indonesia. Thefocus of this research is about the backlog of demand from its carrosserie repairfactory in one of the transportion company in Indonesia. This company has 9pools which are spread throughout Jakarta and West Java, the demand came fromthese pools this is why the level of demand is high and the reason that this factoryneeds an improvement to fulfill its demand. DMAIC (Define, Measure, Analyze,Improve, and Control) is the method used in this research, in order to get the bestoutput that is going to be implemented in this company. Painting process is goingto be the focus of this research, painting process is separated into six big subactivitieswhich are metal cleansing, primer efoxy, putty, painting, and finishing.The improvements that are going to be made is going to have impact on itsproduction process duration which will lead to fulfillment of this company?sdemand., This research aims to propose improvements for achieving thedemand for carrosserie repair for a transportation company in Indonesia. Thefocus of this research is about the backlog of demand from its carrosserie repairfactory in one of the transportion company in Indonesia. This company has 9pools which are spread throughout Jakarta and West Java, the demand came fromthese pools this is why the level of demand is high and the reason that this factoryneeds an improvement to fulfill its demand. DMAIC (Define, Measure, Analyze,Improve, and Control) is the method used in this research, in order to get the bestoutput that is going to be implemented in this company. Painting process is goingto be the focus of this research, painting process is separated into six big subactivitieswhich are metal cleansing, primer efoxy, putty, painting, and finishing.The improvements that are going to be made is going to have impact on itsproduction process duration which will lead to fulfillment of this company’sdemand.]"

"Seiring dengan pertumbuhan mahasiswa, kendaraan yang melintasi Universitas Indonesia (UI) semakin banyak. Pada tahun 2019, kurang lebih terdapat sebanyak 2500 kendaraan keluar masuk area UI setiap harinya. Banyaknya kendaraan yang keluar masuk ini menyebabkan UI menjadi penyumbang besar emisi gas karbon dan hal ini bertentangan dengan visi UI untuk menjadi kampus hijau. Sistem transportasi memainkan peran penting pada tingkat emisi karbon dan polutan di universitas serta transportasi merupakan salah satu kategori dalam penilaian kampus hijau. Dengan adanya hal ini, diperlukan suatu alternatif untuk mengurangi jumlah kendaraan dan pengurangan gas karbon. Salah satu alternatif yang dapat digunakan yaitu dengan beralih dari kendaraan pribadi menjadi transportasi umum. UI menyediakan layanan transportasi umum kampus yang disebut bus kuning untuk memfasilitasi mahasiswa, dosen, staff dan masyarakat disekitar UI ketika berkegiatan didalam kampus. Untuk mendorong seseorang agar mau menggunakan layanan bus kuning, maka dilakukan studi mengenai faktor yang menjadi pertimbangan seseorang untuk menggunakan layanan bus kuning. Studi ini menggunakan second-order confirmatory analysis untuk melihat faktor yang mempengaruhi kualitas layanan bus kuning serta structural equation modeling untuk melihat faktor apa yang mempengaruhi intensi seseorang untuk menggunakan bus kuning. Studi ini memberikan rekomendasi strategi untuk meningkatkan intensi penggunaan bus kuning sebagai alat transportasi dalam kampus berdasarkkan hasil yang diperoleh dari structural equation modeling dan relationship matrix quality function deployment.

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As the number of higher education students has been increasing, there are also more vehicles crossing at Universitas Indonesia (UI). In 2019, there was approximately 2500 vehicles going in and out to the UI areas every day. The number of vehicles going in and out caused UI to be a major contributor to carbon gas emissions. This is contrary to UI's vision to become a green campus. The transportation system plays an important role in the level of carbon emissions and pollutants in universities. Besides, transportation is also one of the categories in the green campus assessment. Given this, some alternatives are needed to reduce the number of vehicles and reduce carbon gas. One alternative that can be used is by switching from private vehicles to public transportation. UI provides campus public transportation services called yellow buses to facilitate students, lecturers, staff, and the community around UI when they are active on campus. In order to encourage someone to have an intention to use the yellow bus service, a study was conducted on the faktors that were considered by someone to use the yellow bus service. This study uses a second-order confirmatory analysis to see the faktors that influence the quality of yellow bus services and structural equation modeling to see what faktors influence a person's intention to use a yellow bus. This study provides a strategy recommendation to increase people's intention to use yellow buses as a means of transportation on campus based on the results obtained from structural equation modeling and relationship matrix quality function deployment.

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"Penelitian ini mencoba memformulasikan kebijakan sistem transportasi terutama transportasi darat. Model dinamis digunakan untuk menggambarkan sistem transportasi darat dengan tujuan, untuk mengetahui faktor-faktor yang mempengarui (leverage factors) sistem transportasi dan kebijakan apa saja yang memungkinkan untuk mengoptimalkan penggunaan infrastruktur transportasi darat terkait pengurangan kemacetan.Hasil penelitian ini menemukan bahwa kebijakan yang berkaitan dengan kapasitas tampung kendaraan dipersimpangan, waktu yang dibutuhkan untuk mengurai kemacetan, perubahan pola transportasi dari kendaraan pribadi berbasis jalan raya, ke moda transportasi berbasis rel (komuter), faktor penggunaan kendaraan terkait dengan waktu tempuh, dan jumlah kendaraan adalah unsur yang memberikan efek paling besar pada kemacetan di kota besar.

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This research is trying to reformulated the policy of transportation system particularly land transportation. Dynamic model was used to describe land transportation system in which objectives are discovering transportation system influenced factors (leverage factors) and reformulating policy that might optimalized the used of land transportation infrastructure in order to decrease traffic jam.

This research discover some result as follows : policy related to vehicles capacity at the intersection, times needed to disentangled traffic jam, transportation pattern change from main street based private vehicles to rail based transport modes (commuter), vehicles utilization factors related to travel time, and the amount of vehicles are the most influencing element to traffic jam in metropolis."