Pengembangan Model Optimasi Suplai Tandan Buah Segar dengan Goal Programming di PKS Tanjung Seumantoh PTPN I

Industri kelapa sawit merupakan sektor yang penting bagi perekonomian nasional Indonesia. Kelapa sawit dipahami sebagai salah satu komoditas pertanian yang strategis sehingga segala aspek yang mampu meningkatkan produksi kelapa sawit beserta produk turunannya menarik untuk diteliti. Penelitian ini fokus pada produksi Crude Palm Oil (CPO), Palm Kernel (PK), dan pendapatan Pabrik Kelapa Sawit (PKS) khususnya di Tanjung Seumantoh dengan memperhatikan suplai bahan baku berupa Tandan Buah Segar (TBS). Melihat bahwa pada periode Januari-Desember 2020, capaian produksi CPO dan PK lebih kecil dibandingkan target yang disebabkan oleh minimnya pasokan TBS dari masing-masing penyulai (supplier) sehingga dibutuhkan optimasi sistem produksi. Didahului dengan pengembangan model matematis yang menggambarkan keadaan nyata di lapangan, kemudian dilakukan sejumlah eksperimen dan uji skenario untuk mengetahui skema yang paling sesuai dalam kerangka pemenuhan target produksi PTPN I area Sumatera Utara. Ada 2 skenario yang diujikan dimana skenario 1 mempertimbangkan rendemen realisasi sedangkan skenario 2 menggunakan rendemen target pada model. Mengingat ada lebih dari 1 objektif model yang ingin dicapai maka digunakan metode goal programming untuk mengolah data dengan software LINGO. Dari hasil eksperimen, diketahui bahwa penerapan skenario 2 yang paling baik untuk memenuhi target produksi, dengan nilai penyimpangan lebih kecil dibandingkan pada skenario 1. Lalu pada skenario 2, diketahui juga bahwa ada kebutuhan peningkatan suplai TBS untuk satu tahun sebagai berikut: 16% dari kebun sendiri, 12% dari pembelian perkebunan rakyat dan 8% dari Kerja Sama Operasional (KSO)

Analisis Pengendalian Persediaan Menggunakan Metode EOQ untuk Optimalisasi Persediaan Bahan Baku Penolong (Studi Kasus: PT. Petrokimia Gresik)

The availability of auxiliary materials is one of the important elements in the production process. Running out of these materials causes the product not to meet the product standards. Therefore, it is necessary to control the supply of auxiliary materials. PT. Petrokimia Gresik, in the process of making fertilizer, used auxiliary materials including Bentonite, Brucite, Red Clay, and Na/K-CO3. In this study, a comparison was made between the min-max method and Economic Order Quantity (EOQ) method. The data collected for this study include data on the use of auxiliary materials in 2021, holding costs, ordering costs, Consumption Rate (CR), lead time (LT), safety factor (SF), and unit cost. The results obtained that the use of the EOQ method can reduce the frequency of ordering auxiliary materials and provide savings in total inventory costs of up to 3% compared to the current min-max method. In addition, based on the calculation provide information that Brucite should be put on priority because it provides the highest total inventory cost compared to other auxiliary materials.Ketersediaan bahan baku penolong merupakan salah satu elemen penting dalam proses produksi pada perusahaan. Ketiadaan bahan baku menyebabkan produk yang dihasilkan tidak memenuhi standar yang diiginkan oleh pasar. Oleh karena itu, perlu dilakukan pengendalian persediaan terhadap bahan baku penolong tersebut, agar produk yang dihasilkan bermutu baik. PT. Petrokimia Gresik, dalam proses pembuatan pupuk membutuhkan bahan baku penolong yaitu: Bentonite, Brucite, Clay Merah, dan Na/K-CO3. Pada penelitian ini, dilakukan perbandingan terhadap metode pengendalian persediaan min-max yang digunakan oleh perusahaan dengan metode Economic Order Quantity (EOQ). Data yang digunakan adalah data penggunaan bahan baku penolong di tahun 2021, biaya penyimpanan, biaya pemesanan, Consumption Rate (CR), lead time (LT), safety factor (SF), dan biaya pembelian bahan baku penolong. Hasil dan kesimpulan yang didapatkan adalah bahwa penggunaan metode EOQ dapat menurunkan frekuensi pemesanan bahan baku penolong serta memberikan penghematan total biaya persediaan hingga 3% dibandingkan menggunakan metode min-max saat ini. Selain itu, dari perhitungan kedua model sama-sama memberikan informasi bahwa bahan baku penolong jenis Brucite perlu mendapat perhatian karena memberikan total biaya persediaan yang paling tinggi dibandingkan dengan bahan baku penolong lainnya

Optimization of Blood Bag Distribution Routes Using AMPL Software and Nearest Neighbor Algorithm (Case Study of the Indonesian Red Cross Jakarta)

The process of distributing blood bags by the Indonesian Red Cross (PMI) DKI Jakarta uses route selection preferences by ambulance drivers. Basically, this routing problem can impact other aspects such as additional costs, distribution time, fuel use, carbon emissions, and others, so this research needs to propose the best route to minimize travel distance. There are several Hospital Blood Banks (BDRS) in Jakarta that do not receive blood bags at the right time. As an organization authorized to provide blood bag supply, the PMI must distribute blood bag using the 7R concept (Right Time, Right Place, Right Quantity, Right Quality, Right Cost, Right Condition, and Right People). The PMI also has to consider that blood bags are classified as perishable items that need to require fast and precise handling. Therefore, it is necessary to optimize the blood distribution by minimizing travel distance. The optimization model used is the Vehicle Routing Problem (VRP) with AMPL software comparing with the Nearest Neighbor (NN) algorithm. After 4 hours of running the trial, this research has revealed that AMPL software gives the best combination of travel distance than the Nearest Neighbor algorithm, with the differences being approximately 11.52 km

Optimizing of the installed capacity of hybrid renewable energy with a modified MPPT model

The lack of wind speed capacity and the emission of photons from sunlight are the problem in a hybrid system of photovoltaic (PV) panels and wind turbines. To overcome this shortcoming, the incremental conductance (IC) algorithm is applied that could control the converter work cycle and the switching of the buck boost therefore maximum efficiency of maximum power point tracking (MPPT) is reached. The operation of the PV-wind hybrid system, consisting of a 100 W PV array device and a 400 W wind subsystem, 12 V/100 Ah battery energy storage and LED, the PV-wind system requires a hybrid controller for battery charging and usage and load lamp and it’s conducted in experimental setup. The experimental has shown that an average increase in power generated was 38.8% compared to a single system of PV panels or a single wind turbine sub-system. Therefore, the potential opportunities for increasing power production in the tropics wheather could be carried out and applied with this model

Challenge in Household Energy Conservation Program: Analysis from Socio-Demographic Factors

A large proportion of Indonesia’s electricity consumption is used by households. Indonesian electricity usage in household sector has been found covering 42.34% of total consumption and tend to increase in the future. Therefore, household has been identified as important target group for energy efficiency and conservation program. This paper explores the relationship between household electricity use and socio-demographic variables. The study was conducted among 2045 Indonesian households residing in five largest administrative regions for electricity consumers in Indonesia. Cluster sampling method was used to determine the number of sampling and the data analysis was done using Kruskal Wallis test. The results show that occupation was the main sociodemographics factor explaining variability in electricity consumption behavior at residential sector while other factors seemed have weaker correlation. These findings indicate that more comprehensive studies are needed on Indonesian household energy consumption behavior before designing energy efficiency scenarios for conservation policy

Perancangan Fasilitas Gudang Dalam Sistem Logistik (Pendekatan Berbasis Laboratorium)

All of automotive companies around the world are aggressively producing large number of motorized vehicles, especially cars. A car is a transportation mode that is widely used by the middle and upper class. The large number of cars uses cannot be separated from the needs for maintenance of the vehicle itself. Lubricant is the core of engine maintenance on vehicles. Therefore, the demand for lubricants continues to increase due to the increasing demand for cars. Bandar Lampung, for the example, is increasing in the term of the city’s population that is affecting its number of people who own cars. This phenomenon caused the demand for lubricants to increase significantly, so that many lubricant distributors were overwhelmed by this demand. Seeing this opportunity, the RWM Logistics, which is a new Third Party Logistics (3PL) company with value added service is lubricant packaging, has a plan to build a lubricant storage facility in Bandar Lampung. In designing the facility, the company has to decide the layout design, area requirements, material handling planning, and the operational costs. The development of this facility is expected to help the company to meet the demand of lubricant products that were not covered by other distributors

Urban Energy Consumption in a City of Indonesia: General Overview

This paper aims to investigate the energy consumption pattern in four sectors of Padang, Indonesia: residential, commercial, industrial and transportation sectors, under different urban population scenarios using a cohort model and statistical data. The analysis shows that the energy consumed in the residential sector has the major share in the total energy consumption in Padang. Details on energy consumption and the main driving forces in the four sectors have been presented. Decreasing urban energy consumption could be achieved by increasing efficiency of home appliances, promoting electricity saving behavior, increasing of public awareness for saving energy, and applying energy efficiency labeling for home appliances. Keywords: Urban energy consumption; Cohort model; Residential; Transportation; Commercial and Industrial sectors JEL Classifications: Q40; N7