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All Journal Jurnal Teknik Industri IPTEK Journal of Proceedings Series Prosiding Seminas Competitive Advantage REKAYASA ASRO JOURNAL - STTAL APPROACH: Jurnal Teknologi Penerbangan
Heri Awalul Ilhamsah
Universitas Trunojoyo Madura
Aerospace Engineering Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Physics

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Penyelesaian Vehicle Routing Problem with Time Windows (VRPTW) dengan Modified Differential Evolution Algorithm ilhamsah, heri awalul
Prosiding Seminas Competitive Advantage Vol 1, No 1 (2011): Seminas Competitive Advantage I
Publisher : Unipdu Jombang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (301.687 KB)

Abstract

ABSTRAK   Penelitian ini membahas modifikasi algoritma  Differential Evolution  untuk menyelesaikan permasalahan Vehicle Routing Problem with Time Windows (VRPTW). Pengembangan algoritma dilakukan dengan jalan menambahkan teknik pembangkitan inisial solusi. Teknik pembangkitan insial solusi yang pertama adalah dengan menggunakan fungsi  random,kemudian menggunakan neighbor berdasarkan nearest distance (jarak terminimum). Sedangkan teknik pembangkitan solusi selanjutnya adalah dengan insersi solomon. Hasil penelitian ini mengkonfirmasikan bahwa pengembangan algoritma yang dilakukan mampu menemukan solusi yang sama dengan best known solusi dari data yang digunakan sebagai data uji, baik dari jumlah kendaraan yang digunakan ataupun jarak yang dihasilkan. Algoritma modified differential evolution mampu bekerja kompetitif pada data test solomon C105, C106, C107, C108 dan C109 dengan nilai gap sebesar 0%. Kata kunci: algoritma modified differential evolution, vrptw, random, nearest neighbor, insersi solomon.   ABSTRACT This studydiscusses modification ofthe DifferentialEvolutionalgorithmto solve theVehicleRoutingProblem withTimeWindows(VRPTW). Algorithmdevelopmentis done byadding theinitialsolutiongeneratingtechnique. First initials solution generationtechniqueis  use arandomfunction, then based onnearestneighbordistance (minimum distance).  The next initials solution generationtechniqueis use solomon insertion. These resultsconfirmthat thedevelopment of algorithmscapable findingsolutionsthatdothe samewith thebestknownsolutions fromthe data usedasdata test, eitherthe number ofvehicles usedorthe resultingdistance. Modifieddifferentialevolutionalgorithmis able to workcompetitivelyin the solomon data test C105, C106, C107, C108 andC109with gapvalueof 0%. Keyword: modified differentialevolution algorithm, vrptw,  random, nearestneighbor, solomon insertion
PENYELESAIAN VEHICLE ROUTING PROBLEM WITH TIME WINDOWS (VRPTW) DENGAN MODIFIED DIFFERENTIAL EVOLUTION ALGORITHM ilhamsah, heri awalul
Prosiding Seminas Vol 1, No 1 (2011): Seminas Competitive Advantage I
Publisher : Unipdu Jombang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (301.687 KB)

Abstract

ABSTRAK   Penelitian ini membahas modifikasi algoritma  Differential Evolution  untuk menyelesaikan permasalahan Vehicle Routing Problem with Time Windows (VRPTW). Pengembangan algoritma dilakukan dengan jalan menambahkan teknik pembangkitan inisial solusi. Teknik pembangkitan insial solusi yang pertama adalah dengan menggunakan fungsi  random,kemudian menggunakan neighbor berdasarkan nearest distance (jarak terminimum). Sedangkan teknik pembangkitan solusi selanjutnya adalah dengan insersi solomon. Hasil penelitian ini mengkonfirmasikan bahwa pengembangan algoritma yang dilakukan mampu menemukan solusi yang sama dengan best known solusi dari data yang digunakan sebagai data uji, baik dari jumlah kendaraan yang digunakan ataupun jarak yang dihasilkan. Algoritma modified differential evolution mampu bekerja kompetitif pada data test solomon C105, C106, C107, C108 dan C109 dengan nilai gap sebesar 0%. Kata kunci: algoritma modified differential evolution, vrptw, random, nearest neighbor, insersi solomon.   ABSTRACT This studydiscusses modification ofthe DifferentialEvolutionalgorithmto solve theVehicleRoutingProblem withTimeWindows(VRPTW). Algorithmdevelopmentis done byadding theinitialsolutiongeneratingtechnique. First initials solution generationtechniqueis  use arandomfunction, then based onnearestneighbordistance (minimum distance).  The next initials solution generationtechniqueis use solomon insertion. These resultsconfirmthat thedevelopment of algorithmscapable findingsolutionsthatdothe samewith thebestknownsolutions fromthe data usedasdata test, eitherthe number ofvehicles usedorthe resultingdistance. Modifieddifferentialevolutionalgorithmis able to workcompetitivelyin the solomon data test C105, C106, C107, C108 andC109with gapvalueof 0%. Keyword: modified differentialevolution algorithm, vrptw,  random, nearestneighbor, solomon insertion
Development of Artificial Neural Network Model for Estimation of Salt Fields Productivity Cahyadi, Indra; Ilhamsah, Heri Awalul; Anna, Ika Deefi
Jurnal Teknik Industri Vol 20, No 2 (2019): August
Publisher : Department Industrial Engineering, University of Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (330.142 KB) | DOI: 10.22219/JTIUMM.Vol20.No2.152-160

Abstract

In recent years, Indonesia needs import million tons of salt to satisfy domestic industries demand. The production of salt in Indonesia is highly dependent on the weather. Therefore, this article aims to develop a prediction model by examining rainfall, humidity and wind speed data to estimate salt production. In this research, Artificial Neural Network (ANN) method is used to develop a model based on data collected from Kaliumenet Sumenep Madura.  The model analysis uses the full experimental factorial design to determine the effect of the ANN parameter differences. Then, the selected model performance compared with the estimate predictor of Holt-Winters. The results present that ANN-based models are more accurate and efficient for predicting salt field productivity.
OPTIMISASI PERAWATAN BERBASIS AGE REPLACEMENT DENGAN PENDEKATAN ALGORITMA BISECTION Anwar, Khairul; Mustajib, Mohammad Imron; Ilhamsah, Heri Awalul
Rekayasa Vol 5, No 1: April 2012
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (805.816 KB) | DOI: 10.21107/rys.v5i1.2106

Abstract

Makalah ini membahas tentang optimisasi menggunakan perawatan age replacement dengan pendekatan algoritma bisection. Objek penelitiannya adalah lini produksi kaca pada PT. Iglas (persero). Hasil pengambilan data didapat mesin produksi yang banyak mengalami kerusakan adalah mesin forming 1.1 dan mesin forming 1.2, dengan komponen krisisnya adalah arm neckring, dengan distribusi kerusakan dari komponen tersebut adalah lognormal dengan nilai mean 2,6 dan standart deviasi 1,36 pada mesin forming 1.1 dan mean 3 dan standart deviasi 2 untuk mesin forming 1.2. Berdasarkan optimisasi menggunakan metode bisection diperoleh  bahwa waktu optimum untuk melakukan tindakan age replacement pada komponen arm neckring rata-rata yaitu 28,125 hari = 675 jam untuk mesin forming 1.1 dan 20,15631 hari = 483,7514 jam untuk mesin forming 1.2.
Penyelesaian Vehicle Routing Problem with Time Windows (VRPTW) dengan Modified Differential Evolution Algorithm ilhamsah, heri awalul
Prosiding Seminas Vol 1, No 1 (2011): Seminas Competitive Advantage I
Publisher : Unipdu Jombang

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

Abstract

ABSTRAK   Penelitian ini membahas modifikasi algoritma  Differential Evolution  untuk menyelesaikan permasalahan Vehicle Routing Problem with Time Windows (VRPTW). Pengembangan algoritma dilakukan dengan jalan menambahkan teknik pembangkitan inisial solusi. Teknik pembangkitan insial solusi yang pertama adalah dengan menggunakan fungsi  random,kemudian menggunakan neighbor berdasarkan nearest distance (jarak terminimum). Sedangkan teknik pembangkitan solusi selanjutnya adalah dengan insersi solomon. Hasil penelitian ini mengkonfirmasikan bahwa pengembangan algoritma yang dilakukan mampu menemukan solusi yang sama dengan best known solusi dari data yang digunakan sebagai data uji, baik dari jumlah kendaraan yang digunakan ataupun jarak yang dihasilkan. Algoritma modified differential evolution mampu bekerja kompetitif pada data test solomon C105, C106, C107, C108 dan C109 dengan nilai gap sebesar 0%. Kata kunci: algoritma modified differential evolution, vrptw, random, nearest neighbor, insersi solomon.   ABSTRACT This studydiscusses modification ofthe DifferentialEvolutionalgorithmto solve theVehicleRoutingProblem withTimeWindows(VRPTW). Algorithmdevelopmentis done byadding theinitialsolutiongeneratingtechnique. First initials solution generationtechniqueis  use arandomfunction, then based onnearestneighbordistance (minimum distance).  The next initials solution generationtechniqueis use solomon insertion. These resultsconfirmthat thedevelopment of algorithmscapable findingsolutionsthatdothe samewith thebestknownsolutions fromthe data usedasdata test, eitherthe number ofvehicles usedorthe resultingdistance. Modifieddifferentialevolutionalgorithmis able to workcompetitivelyin the solomon data test C105, C106, C107, C108 andC109with gapvalueof 0%. Keyword: modified differentialevolution algorithm, vrptw,  random, nearestneighbor, solomon insertion
Development of Artificial Neural Network Model for Estimation of Salt Fields Productivity Indra Cahyadi; Heri Awalul Ilhamsah; Ika Deefi Anna
Jurnal Teknik Industri Vol. 20 No. 2 (2019): August
Publisher : Department Industrial Engineering, University of Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (331.617 KB) | DOI: 10.22219/JTIUMM.Vol20.No2.152-160

Abstract

In recent years, Indonesia needs import millions of tons of salt to satisfy domestic industries' demand. The production of salt in Indonesia is highly dependent on the weather. Therefore, this article aims to develop a prediction model by examining rainfall, humidity, and wind speed data to estimate salt production. In this research, Artificial Neural Network (ANN) method was used to develop a model based on data collected from Sumenep Madura Indonesia.  The model analysis used the complete experimental factorial design to determine the effect of the ANN parameter differences. Furthermore, the selected model performance compared with the estimate predictor of Holt-Winters. The results presented that ANN-based models were more accurate and efficient for predicting salt field productivity.
Salt Fields Productivity Forecasting Based On Sunlight Duration, Wind Speed and Temperature Data Indra Cahyadi; Heri Awalul Ilhamsah; Ika Deefi Anna
IPTEK Journal of Proceedings Series No 5 (2019): The 1st International Conference on Business and Management of Technology (IConBMT)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (704.629 KB) | DOI: 10.12962/j23546026.y2019i5.6294

Abstract

Once a major salt producer, Indonesia has imported million tons of salt in recent years to meet domestic demands of chemical industries. Indonesia’s salt-producing potential has been hindered by lack of competitiveness and unsynchronized production data. The salt supply chain process is typically finished on a monthly basis, yet the uncertainty of weather conditions often leads to erratic production yields. Since heavy reliance on the weather can bring negative consequences for salt farmers around the country, accurate salt field productivity forecasting is of great importance. This study aims at examining sunlight duration, wind speed and temperature data to predict salt field productivity in Kalianget Sumenep Madura. The predictive model is developed using Artificial Neural Network (ANN) method because it has a low risk of fault to solve nonlinear relationships. The effects of different learning rate and momentum values are analyzed by full factorial design of experiment and evaluated based on the lowest root mean square error (RMSE). Then, the optimal model is used to test and compare the forecasting performance based on ANN and Holt-Winters predictors. The result demonstrates that the proposed model is accurate and efficient to represent a good solution to predict salt field productivity in the region
PERENCANAAN PERSEDIAAN BAHAN BAKU DENGAN METODE ECONOMIQ ORDER QUANTITY (EOQ) MENGGUNAKAN ALGORITMA GENETIKA (AG) (STUDI KASUS: PT. XYZ) Heri Awalul Ilhamsah; Ade Novaliana Sari; Mu’alim Mu’alim
Approach : Jurnal Teknologi Penerbangan Vol. 4 No. 1 (2020): April 2020
Publisher : Politeknik Penerbangan Surabaya

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

Abstract

The PT. Refindo Intiselaras Indonesia is a manufacturing company that produces underground mining equipment. Rock Bolt is one of the main products produced. The problem that occurred in 2019 was that there was a delay in the production process because the material or raw material stock at PT.RII was lacking or not there, this could not happen to goods or service companies. This study uses the Economiq Order Quantity (EOQ) method approach with a genetic algorithm (AG) to solve the problems that occur. This study aims to minimize production delays, by purchasing optimal raw materials. Resulted in this research for the optimal purchase of raw materials in 2020, from January to August the required requirement for 2.5 mm is 18,186 Kg, 3.2 mm is 17,289 Kg, 3,4 mm is 19,740 Kg with a distance between orders for 3 months with a total purchase transaction of Rp. 26,783,237,193. The results of this study indicate that the total purchase of inventories generated by the Economiq Order Quantity (EOQ) method using a genetic algorithm (GA) is smaller than the company's total purchase cost of Rp. 28,662,000,000 thus saving costs of Rp. 1,878,762,807.
A GENETIC ALGORITHM APPROACH FOR SOLVING INBOARD OUTER FIXED LEADING EDGE-DRIVE RIB 1 PRODUCTION SCHEDULING AT PT DIRGANTARA INDONESIA Heri Awalul Ilhamsah; Indra Cahyadi; Ari Yulianto
JOURNAL ASRO Vol 9 No 1 (2018): International Journal of ASRO
Publisher : Indonesian Naval Technology College - Sekolah Tinggi Teknologi Angkatan Laut - STTAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (386.552 KB) | DOI: 10.37875/asro.v9i1.109

Abstract

The scheduling of production floor is a sophisticated problem which seeks the optimal task allocation to certain resources under a number of constraints. The use of optimization techniques facilitates the determination of acceptable solutions that considered optimized for a specific problem. This paper proposes production scheduling solution based on job priority in a Non-Deterministic Polynomial-time hard (NP-hard) problem. The case study was taken from the Spirit Aerosystem Project, particularly in the Inboard Outer Fixed Leading Egde - Drive Rib 1 component production process. The problem consists of finding the machine operations schedule, taking into account the precedence constraints. The main objective is to minimize total delays or tardiness. The genetic algorithm was employed to determine the optimized production scheduling solution. The parameter for genetic operators in this study consists of a roulette wheel selection, 1 elitist chromosome, partially-mapped crossover mutation and 1 point mutation. The termination condition was achieved when there has been no improvement in the population for 30 iterations.The results show that the algorithm is capable to generate optimum production schedule with minimum tardiness for the given problem. Keywords: Genetic algorithm, job shop problem, scheduling problem
Co-Authors Ade Novaliana Sari Ari Yulianto Ika Deefi Anna Ika Deefi Anna Ika Deefi Anna, Ika Deefi Indra Cahyadi Indra Cahyadi Indra Cahyadi INDRA CAHYADI, INDRA Khairul Anwar Mohamad Mustajib, Mohamad Mu’alim Mu’alim