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Decision Support System Scheme Using Forward Chaining And Simple Multi Attribute Rating Technique For Best Quality Cocoa Beans Selection Putra, Januar Adi; Galwargan, Agustinus Mariano; Adiwijaya, Nelly Oktavia
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (516.53 KB) | DOI: 10.11591/eecsi.v5.1699

Abstract

Cocoa is a crop plantation originating from the tropical forests of Central America and northern part of South America. In general, cocoa grouped into three types namely Forastero, Criollo, and Trinitario which is the result of a cross between Forastero with Criollo. Cocoa (Theobroma cacao L.) is one of the comodity that has an important role in the Indonesian economy. The Indonesian's processing directorate, and the programs related to the 2015-2019 development are the Increased Production and Productivity of Sustainable Plantation Crops. This program is conducted to increase the production, productivity of cocoa and other plantation crops. One of the focus activities is Inventory of postharvest data of plantation. In the selection of cocoa beans based on the best quality, Indonesian Coffee and Cocoa Research Center is often missed so that there are some cocoa beans that should not pass the quality but still processed into processed products. In that case we proposed a new scheme for Decision Support System by using Forward Chaining method and Simple Multi Attribute Rating Technique (SMART). The combination of these two methods proved to be able to do a very good selection of cocoa beans. Where the selection is done with two stages proven can really filter the cocoa beans are good for health.
Sugar Production Forecasting System in PTPN XI Semboro Jember using Autoregressive Integrated Moving Average (ARIMA) Method Putra, Januar Adi; Bukhori, Saiful; Basbeth, Faishal
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.1988

Abstract

There is a lot of entrepreneurial competition in the production of goods or services in the world, especially in Indonesia, especially the production of staple goods, namely sugar. The problem that is often faced at Sugar Factory PTPN XI Semboro Jember is the lack of management that is neatly organized and efficient, which makes this company less working optimally. Often there is a lack and excess of sugar production which makes the sugar does not have the maximum value, the sugar has been damaged, and sales at a reduced price because the sugar is not as efficient as the initial product. From these various problems, it can reduce profits from the company. From these problems it can be concluded that the company needs a system that can organize the management of the company, and is able to forecast production in the future. In this research will make a forecasting system using the method of Autoregressive Integrated Moving Average (ARIMA), where this method is divided into three methods, namely the Autoregressive (AR) method, the Moving Average (MA) method, and the Autoregressive Integrated Moving Average (ARIMA) method, which preceded by checking stationary data, and modeling the Autoregressive Integrated Moving Average (ARIMA) method. Forecasting is done using production data for the previous 12 years from the company. The system is made to facilitate management that is less organized and displays predictions for the next production period. The results of this forecasting system are to determine the amount of production each year needed in this company. From the results of the ARIMA method modeling, the right ARIMA method is obtained by the ARIMA / AR (1,0,0), ARIMA / MA (0,0,1), and ARIMA (1,0,1) methods. The test results found that the average value of Mean Absolute Percentage Error (MAPE) in the Autoregressive (AR) method was 17%, the Moving Average (MA) method was 19%, and the Autoregressive Integrated Moving Average (ARIMA) method was 15%.
Decision Support System Scheme Using Forward Chaining And Simple Multi Attribute Rating Technique For Best Quality Cocoa Beans Selection Januar Adi Putra; Agustinus Mariano Galwargan; Nelly Oktavia Adiwijaya
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (516.53 KB) | DOI: 10.11591/eecsi.v5.1699

Abstract

Cocoa is a crop plantation originating from the tropical forests of Central America and northern part of South America. In general, cocoa grouped into three types namely Forastero, Criollo, and Trinitario which is the result of a cross between Forastero with Criollo. Cocoa (Theobroma cacao L.) is one of the comodity that has an important role in the Indonesian economy. The Indonesian's processing directorate, and the programs related to the 2015-2019 development are the Increased Production and Productivity of Sustainable Plantation Crops. This program is conducted to increase the production, productivity of cocoa and other plantation crops. One of the focus activities is Inventory of postharvest data of plantation. In the selection of cocoa beans based on the best quality, Indonesian Coffee and Cocoa Research Center is often missed so that there are some cocoa beans that should not pass the quality but still processed into processed products. In that case we proposed a new scheme for Decision Support System by using Forward Chaining method and Simple Multi Attribute Rating Technique (SMART). The combination of these two methods proved to be able to do a very good selection of cocoa beans. Where the selection is done with two stages proven can really filter the cocoa beans are good for health.
Sugar Production Forecasting System in PTPN XI Semboro Jember using Autoregressive Integrated Moving Average (ARIMA) Method Januar Adi Putra; Saiful Bukhori; Faishal Basbeth
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.1988

Abstract

There is a lot of entrepreneurial competition in the production of goods or services in the world, especially in Indonesia, especially the production of staple goods, namely sugar. The problem that is often faced at Sugar Factory PTPN XI Semboro Jember is the lack of management that is neatly organized and efficient, which makes this company less working optimally. Often there is a lack and excess of sugar production which makes the sugar does not have the maximum value, the sugar has been damaged, and sales at a reduced price because the sugar is not as efficient as the initial product. From these various problems, it can reduce profits from the company. From these problems it can be concluded that the company needs a system that can organize the management of the company, and is able to forecast production in the future. In this research will make a forecasting system using the method of Autoregressive Integrated Moving Average (ARIMA), where this method is divided into three methods, namely the Autoregressive (AR) method, the Moving Average (MA) method, and the Autoregressive Integrated Moving Average (ARIMA) method, which preceded by checking stationary data, and modeling the Autoregressive Integrated Moving Average (ARIMA) method. Forecasting is done using production data for the previous 12 years from the company. The system is made to facilitate management that is less organized and displays predictions for the next production period. The results of this forecasting system are to determine the amount of production each year needed in this company. From the results of the ARIMA method modeling, the right ARIMA method is obtained by the ARIMA / AR (1,0,0), ARIMA / MA (0,0,1), and ARIMA (1,0,1) methods. The test results found that the average value of Mean Absolute Percentage Error (MAPE) in the Autoregressive (AR) method was 17%, the Moving Average (MA) method was 19%, and the Autoregressive Integrated Moving Average (ARIMA) method was 15%.
Social Media Sentiment Analysis to Measure Community Response in the Millennial Road Safety Festival Program Using TF-IDF and Support Vector Machine Saiful Bukhori; Sonya Sulistyono; Antonius Cahya Prihandoko; Januar Adi Putra; Windi Eka Yulia Retnani; Umroh Makhmudah; Muhammad Noor Dwi Eldianto
Journal of Indonesia Road Safety Vol 3 No 2 (2020): Journal of Indonesia Road Safety
Publisher : Traffic Accident Research Center, Indonesia Traffic Police Corps and University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/korlantas-jirs.v3i2.16768

Abstract

This Sentiment Analysis is a combination of data mining and text mining. Sentiment Analysis itself is used to process various opinions that the public or experts have given through a variety of existing media. The argument is given to a product, service, or agency. Sentiment Analysis has three types of opinions: negative opinions, positive opinions, and neutral opinions. Based on the test results, the resulting model achieves the highest accuracy of 83.33% when using 80:20 scenario data, while the lowest accuracy of 80.00% is achieved when using the 60:40 scenario data. The higher the precision that will be obtained, whereas using less training data will be slightly unstable. ABSTRAK Sentiment Analysis merupakan perpaduan dari data mining dan teks mining, dimana Sentiment Analysis sendiri digunakan untuk mengolah berbagai macam opini yang telah diberikan oleh masyarakat atau para pakar melalui berbagai media yang ada, opini tersebut diberikan untuk sebuah produk, jasa maupun sebuah instansi. Pada Sentiment Analysis terdapat 3 jenis opini, yaitu opini negatif, opini positif dan opini netral. Berdasarkan hasil pengujian, model yang dihasilkan mencapai akurasi tertinggi yaitu 83,33% saat menggunakan data skenario 80:20, sedangkan akurasi terendah 80,00% dicapai ketika menggunakan skenario data 60:40 Skenario data dapat memengaruhi tingkat akurasi semakin banyak jumlah data pelatihan yang diberikan, semakin tinggi akurasi yang akan diperoleh, sedangkan jika menggunakan lebih sedikit data pelatihan, hasilnya akan sedikit tidak stabil.
Pengenalan Ekspresi Emosi pada Citra Wajah Menggunakan Extreme Learning Machine Studi Kasus Dataset Publik JAFFE: Emotional Expressions Recognition in Facial Images Using Extreme Machine Learning Case Study of JAFFE Public Dataset Shasha Nur Faadhilah; Saiful Bukhori; Januar Adi Putra
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 2 No. 2 (2022): MALCOM October 2022
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (640.308 KB) | DOI: 10.57152/malcom.v2i2.363

Abstract

Era teknologi informasi semakin berkembang dengan cepat dan kompleks, kehandalan sistem mengolah data dengan baik akan menghasilkan informasi yang baik pula. Face Recognition merupakan topik yang ramai dibicarakan dan banyak diteliti, penemuan-penemuan dibidang ini pun banyak menghasilkan temuan yang digunakan sebagai acuan untuk Face Recognition, salah satunya Facial Expression. Sistem pengenalan emosi merupakan salah satu contoh pemrosesan citra yang termasuk pada ranah computer vision. Dalam dunia computer vision, penelitian mengenai ekspresi wajah telah dilakukan sebelumnya oleh Chinese Academy of Sciences Micro-Expression (CASME). Pada kasus micro-expressions wajah, penelitian ini fokus pada satu area yaitu lower face yang dijadikan acuan untuk fitur wajah yang digunakan. Untuk lower face area yang dijadikan ROI khusus diwilayah mulut (lower face). Untuk melakukan ROI pada area tersebut, metode yang digunakan algoritma Viola-Jones pada cascade object detector dengan menentukan wilayah khusus yang dicrop atau batasan area berdasarkan fitur lower face yang bisa disebut sebagai deteksi area mulut (mouth detection). Kemudian dilakukan proses ekstraksi menggunakan Local Binary Pattern. Setelah itu hasil dari proses ekstraksi dijadikan acuan untuk menentukan deteksi ekspresi emosi. Nantinya deteksinya akan memanfaatkan ELM sebagai metode klasifikasi yang dijadikan kelas-kelas ekspresi emosi.
E-SuKet: Peningkatan Kualitas Layanan Desa Tenggarang Kecamatan Tenggarang Kabupaten Bondowoso melalui Implementasi Layanan Surat Keterangan Berbasis Elektronik Januar Adi Putra; Beny Prasetyo; Lutfie Ariefianto
Jurnal Pengabdian Masyarakat Vol 3 No 2 (2022): Jurnal Pengabdian Masyarakat
Publisher : LP2M Institut Teknologi dan Bisnis Asia Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32815/jpm.v3i2.1100

Abstract

Pelayanan publik yang baik bagi seluruh masyarakat merupakan tuntutan yang harus dipenuhi oleh seluruh lembaga pemerintahan. Hal ini sebagai bagian dari perwujudan tata kelola pemerintahan yang baik (good government governance). Berdasarkan data yang dihimpun oleh Lembaga Penelitian dan Pengabdian Masyarakat(LP2M) Universitas Jember (UNEJ), Desa Tenggarang yang terletak di Kecamatan Tenggarang Kabupaten Bondowoso memiliki beberapa masalah yang berkaitan dengan kualitas pelayanan publik bagi masyarakat. Tidak adanya media sebagai wadah pengaduan keluhan/aspirasi masyarakat & pengurusan surat izin/keterangan yang masih dilakukan dengan cara manual membutuhkan waktu lama. Kondisi ini membuat permasalahan yang dialami warga tidak dapat tertangani dengan baik. Jarak pemukiman antar warga dan dengan balai desa cukup jauh. Hal ini menyebabkan masyarakat malas untuk menyampaikan permasalahan / aspirasinya karena dibutuhkan usaha yang cukup besar untuk mencapai balai desa, pengurusan surat izin yang masih dilakukan secara manual juga sangat menyita waktu masyarakat. Sementara disisi lain banyak kebutuhan pada masyarakat perlu penanganan/respon yang cepat
Perancangan UI/UX pada Aplikasi Taspen Otentikasi Berbasis Mobile Dengan Menggunakan Metode Design Thinking Arif Febrian; Fahrobby Adnan; Januar Adi Putra
JTIM : Jurnal Teknologi Informasi dan Multimedia Vol 4 No 4 (2023): February
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v4i4.259

Abstract

Along with the development of today's technology, the role of information system services becomes very important in overcoming various kinds of community problems effectively and efficiently. Taspen Authentication is an example of an information system service aimed at retired civil servants (PNS). However, there are still problems with the taspen authentication application that make it difficult for some users to run it. The majority of users of this application are the elderly group aged ≥ 60 years and have limited physical function and cognitive function. Based on the results of initial observations and interviews of researchers involving Taspen and several users in the elderly category, it was found that there were problems that caused the lack of efficiency in using the taspen authentication application in terms of UI/UX. The purpose of this research is to design a UI/UX that suits the needs of users, especially the elderly, using the design thinking method. In addition to using the design thinking method, researchers also use User Experience Questionnaire (UEQ) at the testing stage to determine the feasibility of the application prototype that has been designed and get feedback from the target user. The results of the study show that the new interface design provides a very good user experience as evidenced by the results of the 6 UEQ scales which are of excellent value. So the researcher concludes that the UI/UX design on the taspen authentication application that uses the design thinking method is able to provide a description of user needs, especially for the elderly.