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PENGEMBANGAN MODEL MATEMATIS VEHICLE ROUTING PROBLEM with compartmen DENGAN KARAKTERISTIK SPLIT DELIVERY, MULTI PRODUCT DAN TIME WINDOWS Normasari, Nur Mayke Eka
Angkasa: Jurnal Ilmiah Bidang Teknologi Vol 11, No 1 (2019): MEI
Publisher : Sekolah Tinggi Teknologi Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (453.415 KB)

Penelitian ini mengusulkan model matematika dari Vehicle Routing Problem with Compartment (VRPC) dengan karakteristik split delivery, multi product, dan time windows. VRPC adalah varian VRP yang merupakan pengembangan dari Capacitated Vehicle Routing Problem (CVRP) dengan kendaraan yang digunakan memiliki kompartemen untuk misahkan beberapa jenis produk yang akan didistribusikan. Penerapan konsep VRPC dalam sistem nyata, dapat ditemukan pada sistem pendistribusian bahan bakar, minyak, limbah daur ulang, maupun pendistribusian makanan. Model matematika yang dibangun bertujuan untuk menentukan rute optimal dengan meminimasi jarak. Perangkat lunak AMPL dengan CLPEX solver digunakan untuk menyelesaikan model matematika yang dibangun. Model matematika yang dikembangkan berbentuk Mixed Integer Nonlinear Programming (MINLP). Eksperimen numeris digunakan untuk mengilustrasikan pengggunaan model yang dibangun. Hasil eksperimen menunjukkan bahwa model yang dibangun lulus uji verifikasi dan validasi. Kata Kuci: VRPC, split delivery, multi product, time windows, CPLEX, MINLP

STOCHASTIC DEMAND IN VEHICLE ROUTING PROBLEM WITH COMPARTMEN Normasari, Nur Mayke Eka; Warangga, Anjas Fikhri; Nugrahandika, Widyasari Her
Angkasa: Jurnal Ilmiah Bidang Teknologi Vol 11, No 2 (2019): November
Publisher : Sekolah Tinggi Teknologi Adisutjipto

This research focus on consideration of stochastic demand in deterministic Vehicle Routing Problem with Compartment (VRPC) model. VRPC in this research consider split delivery, multi product, and time windows characteristic. Stochastic demand in this research is handled using scenario-based approach. The demand is modeled by constructing discrete scenarios then implementing it in the deterministic VRPC model. The change of customer demand over time is considered as normal probability distribution. Stochastic VRPC model then solved using robust approach by looking for the highest demand under each scenario to be solve, therefore the solution generated deals with the minimum probability of unmet demand.

MATHEMATICAL MODEL OF BLOOD COLLECTION ROUTING PROBLEM Normasari, Nur Mayke Eka; Muallifah, Nabilah
Angkasa: Jurnal Ilmiah Bidang Teknologi Vol 12, No 1 (2020): Mei
Publisher : Sekolah Tinggi Teknologi Adisutjipto

The scarcity of blood that is still happening today is the result of a combination of high blood needs and the difficulty of recruiting and maintaining donors. There is no research discover the substitute that can replace the role of blood, therefore the only source is from donations or blood donors. Approximately 80% of total blood donations collected by American Red Cross are come from blood drive events. Because blood has 6-hour spoilage time, donated blood at various donation locations must be collected and sent to a blood center for processing in less than 6 hours. This research study the Maximum Blood Collection Routing Problem (MBCRP). This problem is the extension of Vehicle Routing Problem with Time-Window (VRPTW) by considering the spoilage time limitation in blood. A mathematical model with objective to maximize total blood collection is built to cope with this problem. The mathematical model will be tested for verification and validation. The model is written in a computer programming language using AMPL software and is solved using the CPLEX solver. Furthermore, the results of verification and validation tests will be evaluated to see the applicability of the model.

STOCHASTIC DEMAND IN VEHICLE ROUTING PROBLEM WITH COMPARTMEN Nur Mayke Eka Normasari; Anjas Fikhri Warangga; Widyasari Her Nugrahandika
Angkasa: Jurnal Ilmiah Bidang Teknologi Vol 11, No 2 (2019): November
Publisher : Institut Teknologi Dirgantara Adisutjipto

This research focus on consideration of stochastic demand in deterministic Vehicle Routing Problem with Compartment (VRPC) model. VRPC in this research consider split delivery, multi product, and time windows characteristic. Stochastic demand in this research is handled using scenario-based approach. The demand is modeled by constructing discrete scenarios then implementing it in the deterministic VRPC model. The change of customer demand over time is considered as normal probability distribution. Stochastic VRPC model then solved using robust approach by looking for the highest demand under each scenario to be solve, therefore the solution generated deals with the minimum probability of unmet demand.

Heterogeneous fleet green vehicle routing problem: a literature review Nur Mayke Eka Normasari; Nurul Lathifah
Angkasa: Jurnal Ilmiah Bidang Teknologi Vol 13, No 1 (2021): Mei
Publisher : Institut Teknologi Dirgantara Adisutjipto

Transportation, as a part of the supply chain process, contributes to carbon emission which leads to climate change and global warming. This environmental issue gives an impact to decisions regarding the supply chain of a company. One way to deal with this issue is by analyzing their vehicle routing problem. In this study, the issue about routing problems in green supply chain by considering the heterogeneous fleet is being discussed. One variant of Green Vehicle Routing Problem (GVRP) reviewed in this paper is about Heterogeneous Alternative Fuel Vehicles for Green Vehicle Routing Problem (HAFVGVRP). The purpose of this study is to review the development of GVRP with heterogeneous alternative fuel vehicles and the gap or state-of-the-art on existing researches. The review was classified according to the objectives, type of fleet, and solution used. Moreover, this study also presents the trend and direction of further research.

MATHEMATICAL MODEL OF BLOOD COLLECTION ROUTING PROBLEM Nur Mayke Eka Normasari; Nabilah Muallifah
Angkasa: Jurnal Ilmiah Bidang Teknologi Vol 12, No 1 (2020): Mei
Publisher : Institut Teknologi Dirgantara Adisutjipto

The scarcity of blood that is still happening today is the result of a combination of high blood needs and the difficulty of recruiting and maintaining donors. There is no research discover the substitute that can replace the role of blood, therefore the only source is from donations or blood donors. Approximately 80% of total blood donations collected by American Red Cross are come from blood drive events. Because blood has 6-hour spoilage time, donated blood at various donation locations must be collected and sent to a blood center for processing in less than 6 hours. This research study the Maximum Blood Collection Routing Problem (MBCRP). This problem is the extension of Vehicle Routing Problem with Time-Window (VRPTW) by considering the spoilage time limitation in blood. A mathematical model with objective to maximize total blood collection is built to cope with this problem. The mathematical model will be tested for verification and validation. The model is written in a computer programming language using AMPL software and is solved using the CPLEX solver. Furthermore, the results of verification and validation tests will be evaluated to see the applicability of the model.

MATHEMATICAL MODEL OF VEHICLE ROUTING PROBLEM WITH COMPARTMENT, SPLIT DELIVERY, MULTI PRODUCT, AND TIME WINDOWS Nur Mayke Eka Normasari; Anjas Fikhri Warangga
Angkasa: Jurnal Ilmiah Bidang Teknologi Vol 11, No 1 (2019): Mei
Publisher : Institut Teknologi Dirgantara Adisutjipto

Penelitian ini mengusulkan model matematika dari Vehicle Routing Problem with Compartment (VRPC) dengan karakteristik split delivery, multi product, dan time windows. VRPC adalah varian VRP yang merupakan pengembangan dari Capacitated Vehicle Routing Problem (CVRP) dengan kendaraan yang digunakan memiliki kompartemen untuk misahkan beberapa jenis produk yang akan didistribusikan. Penerapan konsep VRPC dalam sistem nyata, dapat ditemukan pada sistem pendistribusian bahan bakar, minyak, limbah daur ulang, maupun pendistribusian makanan. Model matematika yang dibangun bertujuan untuk menentukan rute optimal dengan meminimasi jarak. Perangkat lunak AMPL dengan CLPEX solver digunakan untuk menyelesaikan model matematika yang dibangun. Model matematika yang dikembangkan berbentuk Mixed Integer Nonlinear Programming (MINLP). Eksperimen numeris digunakan untuk mengilustrasikan pengggunaan model yang dibangun. Hasil eksperimen menunjukkan bahwa model yang dibangun lulus uji verifikasi dan validasi.

Algoritma Spotted Hyena Optimizer pada Capacitated Vehicle Routing Problem Prayoga Yudha Pamungkas; Nur Mayke Eka Normasari
Prosiding Seminar Nasional Sains dan Teknologi Terapan 2022: Energi Terbarukan dan Keberlanjutannya di Berbagai Sektor
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Transportation is used in the delivery of goods from one location to another, contributing costs to the final price of a product or service. Efficiency is needed to reduce transportation costs, one of which can be done by optimizing transportation routes. Vehicle Routing Problem (VRP) is a problem that is often referred to to find the optimal route from a source to several points at minimal cost. VRP is evolving into a complex problem as the number of consumers to visit increases. This complexity causes VRP to be included in the combinatorial optimization which has a lot of configuration in finding the shortest route. In this study, VRP was completed with a metaheuristic approach using the Spotted Hyena Optimizer (SHO) algorithm. The use of SHO in capacitated vehicle routing problems (CVRP) is based on the results of research by the originator of SHO which is able to achieve convergent rate faster than other algorithms. SHO on CVRP produces better solutions or shorter total distances than genetic algorithms, ant colony, and particle swarm optimization by using the Augeraat dataset as a comparison of the final results in each algorithm.

Waste Bank Program for Households as A Means of Processing Inorganic Waste Anna Maria Sri Asih; Fitri Trapsilawati; Bertha Maya Sopha; Nur Mayke Eka Normasari
Jurnal Pengabdian kepada Masyarakat (Indonesian Journal of Community Engagement) Vol 8, No 4 (2022)
Publisher : Direktorat Pengabdian kepada Masyarakat Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jpkm.73409

Waste management is crucial in the present day, particularly due to the increase in trash production caused by population growth. To address this issue, the government has implemented the Waste Bank Program, which aims to reduce the amount of waste stored at disposal sites. This program has had a significant impact on the management of household waste, which makes up the majority of all waste generated in Indonesia. Despite its importance, participation in the Waste Bank program is low in many communities. To address this issue, a community activity was organized in Sleman, Yogyakarta Special Region to promote and implement the Waste Bank program in one of the 44-family Neighborhood Units. The focus of this activity was the management of inorganic trash. During the six-month period from April to October 2021, the Waste Bank program had a significant increase in participation, with the percentage of community members taking part rising from 27% to 60%. As a result of these efforts, a total of 1,084 kg of inorganic trash was collected. This waste was primarily composed of paper, followed by plastic, various other materials such as iron, aluminum, and used cooking oil, and a smaller amount of glass. The report summarizes the steps taken, challenges encountered, and potential solutions implemented during the initiation of the Waste Bank program. Additionally, the community was able to save 16% of the revenue generated from the collected trash through monthly environmental fees. These findings provide valuable insight into the current state of waste generation and the community’s situation, which can inform future efforts to reduce waste.

Klasifikasi Varietas Biji Kismis dengan Artificial Neural Network Hanifah Nabila Wismadi; Choirul Yofi; Thariq Faros Manumono; Fauzi Arsyad Hendrawan; Muhammad Raihan Hilmy; Afifa Puspitasari; Nur Mayke Eka Normasari; Achmad Pratama Rifai
Jurnal Optimasi Teknik Industri (JOTI) Vol 5, No 1 (2023)
Publisher : Teknik Industri Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/joti.v5i1.13951

Penerapan kecerdasan buatan pada industri kismis banyak dikembangkan sebagai upaya mengatasi human error pada penyortiran secara manual. Pada studi ini jaringan saraf tiruan atau artificial neural network (ANN) diterapkan untuk mengklasifikasikan kismis besni dan kismis kecimen. Studi ini menggunakan dataset dari UCI Machine Learning Repository. Data tersebut kemudian dilakukan pemrosesan awal dengan metode encoding categorical dan min max scaler. Studi ini membandingkan akurasi tes model ANN yang memiliki jumlah neuron yang berbeda. Terdapat lima level jumlah neuron yang masing-masing ditinjau dengan lima kali trial. Jumlah neuron yang diterapkan pada model penelitian ini adalah 10, 20, 30, 40, dan 50. Pada penelitian ini menggunakan input berupa tujuh variabel yang menggambarkan karakteristik ukuran dan bentuk kismis untuk membedakan antara kismis berjenis besni dan kecimen yaitu jumlah piksel dalam batas kismis, panjang sumbu utama, panjang sumbu kecil, ukuran eksentrisitas elips, jumlah piksel kulit cembung tekecil, rasio wilayah antara kismis dan kotak pembatas, dan jarak antara batas kismis dan piksel sekitarnya. Penyelesaian dilakukan menggunakan aplikasi dari MATLAB dengan algoritma scaled conjugate gradient. Diperoleh bahwa terdapat trend peningkatan rata-rata test accuracy seiring dengan bertambahnya jumlah neuron. Nilai rata-rata akurasi tes tertinggi sebesar 86.7% diperoleh pada jumlah neuron 50. Akan tetapi, akurasi tes tidak bertambah lagi secara signifikan pada penambahan jumlah neuron dari 40 ke 50. Dengan demikian, studi ini dapat membuktikan adanya hubungan antara jumlah neuron dengan akurasi dari model ANN.

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