Dorina Hetharia
Jurusan Teknik Industri, FTI, Universitas Trisakti Jl. Kyai Tapa No 1, Grogol, Jakarta Barat, 11440 Telp. 021- 5663232 ext. 407

Published : 13 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 7 Documents
Search
Journal : JURNAL TEKNIK INDUSTRI

RANCANG BANGUN MODEL PRODUCTION PRODUCTIVITY IMPROVEMENT DENGAN MENGGUNAKAN LEAN TPM DAN SISTEM DINAMIS Intan Emeralda; Dorina Hetharia; Iveline Anne Marie
JURNAL TEKNIK INDUSTRI Vol. 6 No. 1 (2016): Volume 6 No 1 Maret 2016
Publisher : Jurusan Teknik Industri, Fakultas Teknologi Indusri Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (485.184 KB) | DOI: 10.25105/jti.v6i1.1531

Abstract

Increasing productivity and quality is one of the key to make company stay competitive. LeanTPM approach is one of the way to increase productivity. Problem that usually occur at PT. XYZ is thedown time from each line of process production that causing actual production did not reach the target.It is dominantly cause by material shortage, process defect, and machine breakdown. This purpose ofstudy is to develop a production productivity improvement model with Lean TPM approach by usingdynamic system. This study is started by measuring the Loss time value, OEE (Overall EquipmentEffectiveness) value, and making VSM (Value Stream Mapping) to see the flow of material and waste.This is done to measure the actual condition. With this measurement, we can track which one cause thehighest % loss. After that, using the FTA (Fault Tree Analysis) to find the root cause of downtime andwaste produced. It needed to construct the existing dynamic model because the problem are complexsand dynamic. In that model, analytical system is done to indentified and imitated the characteristic ofthose complex systems and also to make the alternative troubleshooting repair solution.
PREDIKSI PRODUKSI JAGUNG DALAM MODEL PENYEDIAAN TEPUNG JAGUNG PADA RANTAI PASOK JAGUNG Dorina Hetharia; M. Syamsul Maarif; Yandra Arkeman; Titi Candra S.
JURNAL TEKNIK INDUSTRI Vol. 6 No. 3 (2016): Volume 6 No 3 November 2016
Publisher : Jurusan Teknik Industri, Fakultas Teknologi Indusri Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (159.865 KB) | DOI: 10.25105/jti.v6i3.1547

Abstract

Corn flour as one of the products made from corn is an intermediate product. This productcan be consumed directly, also can be used as raw materials in the food industry, feedindustry and other industrial raw materials. In the supply chain system, corn flour industry isa part of the maize supply chain . To maintain the continuity of the flow of raw materials inthe supply chain , the industry needs to provide corn flour that meets quantity with goodquality according to consumer demand . It is closely related to the supply of corn as a rawmaterial for corn flour. The provision of corn are also closely related to the availability ofthe amount of corn production obtained from the farmers. This paper discussed aboutprediction of maize production using artificial neural networks and a statistical forecasting .The input variables of corn production forecast in causal models were land and rainfall,while the output variable was the amount of corn production per month . The forecastingresults would be used as input for the corn flour industry.
MODEL PEMILIHAN INDUSTRI KOMPONEN OTOMOTIF YANG RAMAH LINGKUNGAN Triwulandari S Dewayana; Dedy Sugiarto; Dorina Hetharia
JURNAL TEKNIK INDUSTRI Vol. 3 No. 3 (2013): Volume 3 No 3 November 2013
Publisher : Jurusan Teknik Industri, Fakultas Teknologi Indusri Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (146.653 KB) | DOI: 10.25105/jti.v3i3.1564

Abstract

Penelitian ini bertujuan untuk merancang model pemilihan industri komponen otomotifyang ramah lingkungan. Pendekatan yang digunakan dalam merancang model adalah proseshirarki analitik, adapun identifikasi kriteria dan sub kriteria menggunakan pendekatan FuzzyDelphi Method. Sumber data yang digunakan yaitu data sekunder terkait dengan perancanganmodel dan data primer dari pakar untuk pemilihan kriteria, sub kriteria, dan perbandinganberpasangan antar faktor, kriteria, dan sub kriteria. Model yang dihasilkan menggunakan 5(lima) level hirarki yaitu level 1 merupakan tujuan, level 2 terdiri dari 3 (tiga) faktor, level 3terdiri dari 11 (sebelas) kriteria, level 4 terdiri dari 22 (dua puluh dua) sub kriteria, dan level 5terdiri dari 6 (enam) alternatif pilihan. Berdasarkan bobot faktor yang diperoleh, modelpemilihan industri komponen otomotif yang ramah lingkungan lebih memprioritaskan padafaktor pengelolaan limbah / emisi dengan bobot sebesar 0,6370. Pada faktor tersebut, kriteriaprogram penurunan emisi CO2 merupakan prioritas utama dengan bobot sebesar 0,6480.Prioritas berikutnya adalah pada faktor proses produksi dengan bobot sebesar 0,2580. Padafaktor proses produksi, kriteria teknologi proses merupakan prioritas utama dengan bobot faktorsebesar 0.3860. Sedangkan untuk sub criteria dari kriteria teknologi proses, bobot terbesaradalah penerapan Reduce, Reuse, Recycle (3R) yaitu 0,7172. Oleh karena itu, upayapenurunan emisi CO2 dan penerapan Reduce, Reuse, Recycle (3R) akan menjadi penentu bagiindustri komponen otomotif untuk masuk dalam kategori industri yang ramah lingkungan.
PREDIKSI PRODUKSI JAGUNG DALAM MODEL PENYEDIAAN TEPUNG JAGUNG PADA RANTAI PASOK JAGUNG Dorina Hetharia; M. Syamsul Ma’arif; Yandra Arkeman; Titi Candra S
JURNAL TEKNIK INDUSTRI Vol. 7 No. 1 (2017): Volume 7 Nomor 1 Maret 2017
Publisher : Jurusan Teknik Industri, Fakultas Teknologi Indusri Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (417.882 KB) | DOI: 10.25105/jti.v7i1.2202

Abstract

Corn flour as one of the products made from corn is an intermediate product. This product can be consumed directly, also can be used as raw materials in the food industry, feed industry and other industrial raw materials. In the supply chain system, corn flour industry is a part of the maize supply chain . To maintain the continuity of the flow of raw materials in the supply chain , the industry needs to provide corn flour that meets quantity with good quality according to consumer demand . It is closely related to the supply of corn as a raw material for corn flour. The provision of corn are also closely related to the availability of the amount of corn production obtained from the farmers. This paper discussed about prediction of maize production using artificial neural networks and a statistical forecasting . The input variables of corn production forecast in causal models were land and rainfall, while the output variable was the amount of corn production per month . The forecasting results would be used as input for the corn flour industry
PENGEMBANGAN DAN PENERAPAN MANAJEMEN PENGETAHUAN SEBAGAI STRATEGI PENDUKUNG KEGIATAN MEDIS NON-BEDAH (STUDI KASUS KLINIK PETUKANGAN MEDICAL CENTER) Randy Andy; Dedy Sugiarto; Dorina Hetharia
JURNAL TEKNIK INDUSTRI Vol. 2 No. 3 (2012): Volume 2 No 3 November 2012
Publisher : Jurusan Teknik Industri, Fakultas Teknologi Indusri Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (241.313 KB) | DOI: 10.25105/jti.v2i3.7039

Abstract

On a new core competency-based industries, mutual information is the main asset in thecompetitive value to the business processes of an industry. The medical industry uses theinformation as a critical factor in every aspect of perform a clinic or hospital management. Theinformation of knowledge should been packaged in a process that is known as knowledgemanagement. Bennefit knowledge management in the medical industry is to improve the quality ofthe medical officer. It aims to minimize the malpractice cases occurrence that often occurs due tolack of knowledge between medical officer. The lack of knowledge often occurs because of gap ofknowledge between the members of the medical officer. Application of knowledge managementsystems that really serves transfer of knowledge from senior medical officer for a new medicalofficer. Failure of any expert (senior medical officer) in making decisions at the time of medicaltreatment can also be minimized by the knowledge management system.
Peningkatan Kualitas Pelayanan Facility Management Menggunakan Metode Servqual dan Gap Analysis Di PT. GMF AeroAsia Juni Purwo Widadi; Dadan Umar Daihani; Dorina Hetharia
JURNAL TEKNIK INDUSTRI Vol. 10 No. 2 (2020): Volume 10 No 2 Juli 2020
Publisher : Jurusan Teknik Industri, Fakultas Teknologi Indusri Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (466.33 KB) | DOI: 10.25105/jti.v10i2.8402

Abstract

Intisari— GMF AeroAsia merupakan Garuda Maintenance Facility Support Center, yang bertugas sebagai pusat maintenance pesawat terbang dengan berbagai tipe dan register pesawat. Saat proses maintenance pesawat tidak ditinggal tanpa pendampingan, namun akan ada personil yang menetap untuk memantau proses maintenance. Untuk mendukung kegiatan operasional maintenance dibutuhkan layanan untuk non-operasional untuk memfasilitasi personil pelanggan yang menetap sementara waktu di PT. GMF AeroAsia selama proses maintenance pesawatnya dilaksanakan. Selama pelayanan, Facility Management belum dapat memenuhi target perusahaan pada pelayanan non-operasional yang ditetapkan pada poin 4.5. Menanggapi hal tersebut, Facility Management mencoba untuk melakukan peningkatan pelayanan dengan melengkapi fasilitas dan pelayanan yang ada. Penambahan fasilitas yang akan diberikan termasuk penambahan karyawan yang bertanggung jawab untuk pelayanan non-operasional. Dilakukan peningkatan dan penambahan karyawan pada divisi sektor pelayanan non-operasional dengan menyerahkannya pada pihak outsourcing. Penambahaan tenaga kerja melalui outsourcing terbukti meningkatkan kinerja dari pelayanan non-operasional PT. GMF AeroAsia. Namun peningkatan tersebut masih belum dapat memenuhi target perusahaan yang menginginkan pelayanan dapat mencapat 4.5. Penelitian ini bertujuan untuk mengetahui kondisi saat ini terhadap layanan outsourcing terhadap pelanggan pada saat melakukan maintenance pesawat di PT. GMF Aeroasia menggunakan metode servqual, serta menentukan sistem standar layanan outsourcing berdasarkan skala prioritas melalui metode gap analysis. Berdasarkan hasil dari penelitian, dimensi tangibles memiliki skor yang paling rendah dibandingkan keempat dimensi yang lain. Sehingga diperlukan adanya penambahan dan pemenuhan fasilitas pelayanan yang dibutuhkan oleh pelanggan selama proses mantenance pesawat berlangsung.Abstract— PT. GMF AeroAsia is the Garuda Maintenance Facility Support Center, which serves as an aircraft maintenance center with various types and aircraft registers. When the aircraft maintenance process, it is not left without assistance but there will be personnel who stay to monitor the maintenance process. To support operational maintenance activities, non-operational services are needed to facilitate customer personnel who remain temporarily at PT. GMF AeroAsia during the process of maintaining aircraft carried out. During the service, Facility Management has not been able to meet the company's targets for non-operational services set in point 4.5 and only reach 3.9. In response, Facility Management tries to improve services by complementing existing facilities and services. Additional facilities to be provided include the addition of employees responsible for non-operational services. Increased and added employees in the non-operational service sector division by handing it over to the outsourcing party. The addition of labor through outsourcing has been proven to improve the performance of PT. GMF AeroAsia. But the increase is still not able to meet the target companies who want services can achieve 4.5. This study aims to determine the current condition of outsourcing services to customers when performing aircraft maintenance at PT. GMF Aeroasia uses the servqual method, and determines a standard system for outsourcing services based on a priority scale through the gap analysis method. Based on the results of the study, the dimensions of tangibles have the lowest score compared to the other four dimensions. So it is necessary to add and fulfill the service facilities needed by customers during the aircraft maintenance process.
Perbaikan Kualitas Produk Nestable 100 di PT. Cahaya Metal Perkasa Danu Dananjaya; Dorina Hetharia; Sucipto Adisuwiryo
JURNAL TEKNIK INDUSTRI Vol. 10 No. 3 (2020): Volume 10 No 3 November 2020
Publisher : Jurusan Teknik Industri, Fakultas Teknologi Indusri Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (569.107 KB) | DOI: 10.25105/jti.v10i3.8427

Abstract

Intisari- Kualitas produk merupakan faktor yang penting dalam meningkatkan profit bagi perusahaan dan merupakan daya saing dengan perusahaan sejenis. Makalah ini mengkaji tentang perbaikan kualitas produk yang dihasilkan industri manufaktur. Kajian ini dilakukan di PT. Cahaya Metal Perkasa yang memproduksi Nestable 100. Persentase cacat produk Nestable 100 ini cukup besar sehingga perlu dilakukan perbaikan kualitas untuk mengurangi produk cacat tersebut. Tujuan penelitian ini adalah mengurangi cacat pada produk Nestable 100 menggunakan konsep Six Sigma melalui tahapan Define-Measure-Analyze-Improve-Control (DMAIC). Identifikasi Critical to Quality dan pendefinisian proses dengan menggunakan diagram Supplier-Input-Process-Output-Customer dilakukan pada tahap Define.. Uji stabilitas proses dengan menggunakan peta kendali dan menghitung tingkat sigma dilakukan pada tahap measure. Tingkat sigma yang diperoleh pada tahap measure sebesar 2,7 sigma. Dengan menggunakan diagram pareto pada tahap Analyze diperoleh tiga jenis cacat yang paling dominan yaitu Flange NG, Punch NG dan Corrugasi NG. Identifikasi penyebab kegagalan terjadinya jenis cacat pada tahap analyze menggunakan Failure Mode and Effect Analysis (FMEA) dan dilanjutkan dengan Fault Tree Analysis (FTA). Hasil Fault Tree Analysis yaitu terjadinya pencetakan corrugasi yang meleset dengan nilai probabilitas 0,517, gelombang dies tidak sama dengan nilai probabilitas 0,572 dan stopper bergeser dengan nilai probablitas 0,360. Usulan perbaikan yang diberikan adalah membuat Checksheet, membuat Record card, dan membuat Jig. Usulan perbaikan diimplementasikan pada tahap control, dan tingkat sigma pada tahap ini naik menjadi 3,04 sigma.Abstract- Product quality is an important factor in increasing profit for the company and is the competitiveness of similar companies. This paper examines the improvement of product quality produced by the manufacturing industry. This study was conducted at PT. Cahaya Metal Perkasa which produces Nestable 100. The defect percentage of Nestable 100 products is quite large, so it is necessary to improve the quality to reduce these defective products. The purpose of this study was to reduce defects in Nestable 100 products using the Six Sigma concept through the Define-Measure-Analyze-Improve-Control (DMAIC) stages. Identification of Critical to Quality and defining the process using the Supplier-Input-Process-Output-Customer diagram is carried out at the Define stage. Process stability testing using a control chart and calculating the sigma level is carried out at the measure stage. The sigma level obtained at the measure stage is 2.7 sigma. By using the Pareto diagram at the Analyze stage, the three most dominant types of defects are Flange NG, Punch NG and Corrugation NG. Identification of the cause of the failure of the defect type at analyze stage using Failure Mode and Effect Analysis (FMEA) and continued with Fault Tree Analysis (FTA). The results of the Fault Tree Analysis were the occurrence of incorrect corrugation printing with a probability value of 0.517, the dies wave was not the same as the probability value of 0.572 and the stopper shifted with a probability value of 0.360. The suggested improvements are to make a Check sheet, create a Record card, and make a Jig. Proposed improvements are implemented at the control stage, and the sigma level at this stage increases to 3.04 sigma.