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All Journal Jurnal Manajemen Teknologi EIGEN MATHEMATICS JOURNAL
Gabriel, Djoko Sihono
University Of Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Mathematics

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Perancangan Peta Jalan Pengembangunan Industri Hasil Pertanian pada Wilayah Kabupaten dengan Metode VRISA dan Rantai Nilai Gabriel, Djoko Sihono; Nurcahyo, Rahmat; Muslim, Erlinda; Sumaedi, Sik
Jurnal Manajemen Teknologi Vol 13, No 1 (2014)
Publisher : SBM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12695/jmt.2014.13.1.4

Abstract

Abstrak.Salah satu alternatif untuk meningkatkan kesejahteraan penduduk pada suatu wilayah adalah dengan mengembangkan industri. Penelitian ini merancang peta jalan (road map) pengembangan industri hasil pertanian dengan studi kasus Kabupaten Bengkayang, Kalimantan Barat. Metode yang digunakan adalah kerangka VRISA (Value, Rare, In-imitabillity, Substitutability dan Appropriability) untuk menentukan produk industri yang akan dikembangkan. Hasil penelitian ini berupa peta jalan bagi pengembangan industri berbasis jagung bagi Kabupaten Bengkayang. Sesuai dengan pendekatan rantai nilai (value chain), strategi dibagi dua yaitu strategi rantai nilai utama dan strategi rantai nilai pendukung. Hasil penelitian menunjukkan bahwa jagung merupakan pilihan menurut kerangka pengembangan VRISA, sehingga perlu dikembangkan sebagai industri, bukan hanya sebagai hasil pertanian. Tahapan pengembangan industri jagung di Kabupaten Bengkayang dilakukan melalui tiga tahap, yaitu tahap awal (basic foundation establishment), tahap utama (implementasi), serta tahap akhir (harvesting) yang memerlukan waktu lima tahun. Kata kunci: Pengembangan Industri, Kerangka VRISA, Rantai Nilai, Peta Jalan, Wilayah Kabupaten Abstract.Industry development is an alternative in social welfare improvement of a region. This research was conducted to develop a road map of industry development in Kabupaten Bengkayang, West Kalimantan. VRISA (Value, Rare, In-imitabillity, Substitutability and Appropriability) framework used to determine appropriate industrial products to be developed. Based on value chain method, the development strategy was constructed into main value chain and supporting value chain strategy. Output of analysis showed that corn-based product was preferred by VRISA framework, so it needs to be developed as appropriate industry for Kabupaten Bengkayang. There are three stages of industrial development in the corn-based industry, namely initial phase (basic foundation establishment), main phase (implementation), and final stage (harvesting). Time frame for all stages takes five years.Keywords: Industrial Development, VRISA Framework, Value Chain, Road Map, Regency Area 
Peramalan Penjualan Kendaraan Mobil Segmen B2B dengan Metode Regresi Linear Berganda, Jaringan Saraf Tiruan dan Jaringan Saraf Tiruan – Algoritma Genetika Muhammad Agung Nugraha; Farizal Farizal; Djoko Sihono Gabriel
Eigen Mathematics Journal VOL. 3 NO. 2 DESEMBER 2020
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v3i2.80

Abstract

This study aims to create an effective forecasting model in predicting sales of car products in the B2B segment (Business to Business) to obtain estimates of product sales in the future. This research uses multiple linear regression and artificial neural networks that are optimized by genetic algorithms. Forecasting factors for car sales are generally issued by total national car sales, the Consumer Price Index, the Consumer Confidence Index, the Inflation Rate, Gross Domestic Product (GDP), and Fuel Oil Price. The author has also gotten the factors that play a role in the sale of B2B segment by diverting the survey to 106 DMU (Decision Making Unit) who decide to purchase cars in their company. Then we evaluate the results of the questionnaire in training data and simulations on the Artificial Neural Network. Optimized Artificial Neural Networks with Genetic Algorithms can improve B2B segment car sales' accuracy when comparing error values in the ordinary Artificial Neural Network and Multiple Linear Regression.
Optimasi Penyaluran Bahan Bakar Minyak di Wilayah Maluku Indonesia Rini Dian Sari; Farizal Farizal; Djoko Sihono Gabriel
Eigen Mathematics Journal VOL. 3 NO. 2 DESEMBER 2020
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v3i2.81

Abstract

Fossil fuel (BBM) is a vital commodity and has a strategic value for people's lives. On the demand side, the need for BBM tends to increase along with the increasing energy demand for people's lives. Therefore, the distribution system for BBM has to be optimized in order to fulfill the people’s demand. The aim of this paper is to optimize vehicle route for BBM distribution in Maluku so that it has minimum cost, distance, and time. The optimization method in this paper is Mix Integer Linear Programming (MILP). Decision variables in this paper are chosen from the most significant variables for BBM distribution in Maluku.
Co-Authors Erlinda Muslim Farizal Farizal Muhammad Agung Nugraha Rahmat Nurcahyo Rini Dian Sari Sik Sumaedi