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Indexia : Informatics and Computational Intelligent Journal
Published by Universitas Muhammadiyah Gresik
ISSN : 26570432     EISSN : 26570424     DOI : http://dx.doi.org/10.30587/indexia.v3i1
Core Subject : Science,
Computer Science & IT
Jurnal Informatic and Computational Intelligent (INDEXIA) merupakan jurnal nasional yang diterbitkan oleh Program Studi Teknik Informatika Fakultas Teknik (FT), Universitas Muhammadiyah Gresik (UMG) sejak tahun 2019. INDEXIA memuat artikel hasil-hasil penelitian di bidang Informatika dan Kecerdasan Komputasi. INDEXIA berkomitmen untuk menjadi salah satu jurnal nasional berkualitas dengan mempublikasikan artikel penelitian dengan bahasa indonesia sebagai sumber rujukan dan publikasi bagi para peneliti untuk pengembangan ilmu pengetahuan khususnya di bidang Informatika dan Kecerdasan Komputasi.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 54 Documents
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APLIKASI PENDUKUNG KEPUTUSAN PENENTUAN PROMOSI JABATAN MENGGUNAKAN METODE PROFILE MATCHING (STUDI KASUS DI PT. PETROKIMIA GRESIK) Wimpi Sancaka
Indexia : Informatics and Computational Intelligent Journal Vol 1 No 1 (2019)
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30587/indexia.v1i1.819

Abstract

Human resources play an essential role in helping companies to achieve their vision and mission. As a large scale company, PT Petrokimia Gresik obviously needs to invest in Employees’ Performance Assessment System. It could act as a decision-making tool or a measure to evaluate and assess employees' performance at work so that theemployees’ promotion would be moreobjective and organized. Decision support system could be used to reduce the subjectivity in decision-making process. The decision support system that uses profile matching method or competency gap analysis was created based on the data which refers to the decree of the board of directors issued by PT Petrokimia Gresik. This system analyzes and assesses employee’s competencies by grouping and calculating core factors and secondary factors in each variable. The output of the calculation is a ranking of the candidates. By implementing decision support system which uses Profile Matching method, it assists company decision-making process in promotion decision based on employees’ competency scores more optimally.
KLASIFIKASI UMUR LAHAN PERKEBUNAN KELAPA SAWIT PADA CITRA FOTO UDARA BERDASARKAN TEKSTUR MENGGUNAKAN METODE NAÏVE BAYES Elin , Rosalina; Soffiana Agustin
Indexia : Informatics and Computational Intelligent Journal Vol 1 No 1 (2019)
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (533.019 KB) | DOI: 10.30587/indexia.v1i1.820

Abstract

Abstract Developments and advancements in the field of Technology and Information have a considerable influence in the world of image analysis. At present, the process of image manipulation is easier to do, one of the factors in the emergence of various methods in image segmentation. Image segmentation is the first step in doing image processing, pattern recognition, computer vision, because most image processing processes depend on the results of the enhancement operation or image repair process. This final project will be implemented in the process of determining the type of oil palm plantation land using the Naïve Bayes method. The repair process starts from the RGB image to Greyscale, then proceed to the histogram equalization process, then proceed with the inverse image process. The feature extraction process is carried out after image repair operations using the co-occurrence matrix method. The extraction process of the co-occurrence matrix features 6 features, namely angular second moment value, contrast, correlation, varience, inverse different moment, and entropy. The Naïve Bayes process is one process for classifying a class data. There are four classes used in this system test, namely Young Palm Oil, Mature Palm Oil, and Old Palm Oil. Class determination is based on the largest value as the appropriate class. Based on the above objectives, a system can be created using the Matlab R2011b application program. The computation is done by using image images of various types of oil palm trees on plantations in Kalimantan which are taken from aerial photographs which are then cropped to be sampled with a pixel size of 60X60 in 400 images.
PENGELOMPOKAN KABUPATEN/KOTA DI JAWA TIMUR BERDASARKAN INDIKATOR INDEKS PEMBANGUNAN MANUSIA MENGGUNAKAN METODE SOM Ahmad Mushonnif
Indexia : Informatics and Computational Intelligent Journal Vol 1 No 1 (2019)
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (537.637 KB) | DOI: 10.30587/indexia.v1i1.821

Abstract

Human Development Index (HDI) explains how residents can access development results in obtaining income, health, education, and so forth. HDI is based on indicators of health, education and decent living standards. In 2010 to 2014, the achievement of HDI of East Java province rose by 2.78 points from 65.36 into 68.14. But behind the development achievements of HDI, East Java province was ranked 21 out of 34 provinces in Indonesia. Three indicators have relevance in forming HDI value formation. In East Java province high and low HDI regencies or cities are shown only through a composite index, but it was not indicated where the dominant indicator of high or low rank on the HDI. Clustering regencies or cities based on indicators IPM needs to be done to ascertain the achievement of each indicator. Clustering method that can be used are Self-Organizing Maps (SOM). Based on the results of research and discussion conducted, for health indicator, 6 regency/city in the group of low, 12 regency/city in the group of medium, 16 regency/city in the group of high, and 4 regency/city in the group of very high. For educational indicator, 2 regency/city in the group of low, 15 regency/city in the group of medium, 13 regency/city in the group of high, and 8 regency/city in the group of very high. For educational indicator, 2 regency/city in the group of low, 15 regency/city in the group of medium, 13 regency/city in the group of high, and 8 regency/city in the group of very high. For decent living standard indicators, 2 regency/city in the group of low, 15 regency/city in the group of medium, 13 regency/city in the group of high, and 8 regency/city in the group of very high. For educational indicator, 4 regency/city in the group of low, 21 regency/city in the group of medium, 10 regency/city in the group of high, and 3 regency/city in the group of very high.
SISTEM INFORMASI TRACER STUDY ALUMNI PADA PRODI TEKNIK INFORMATIKA UNIVERSITAS MUHAMMADIYAH GRESIK BERBASIS WEB Choyr Mukhlasin Candra Sakti; Soffiana Agustin; Harunur Rosyid
Indexia : Informatics and Computational Intelligent Journal Vol 1 No 1 (2019)
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (485.366 KB) | DOI: 10.30587/indexia.v1i1.822

Abstract

The name of the Higher Education Institution will be big, because of the alumni. However, the Informatics Engineering University of Muhammadiyah Gresik (UMG) continues to be required to always improve the quality of its educational process accompanied by efforts to increase its relevance in the context of global competition. Efforts to make improvements both in the academic and infrastructure fields have been carried out. The management of alumni data at Muhammadiyah Gresik University especially Information Engineering has not been overlooked and is still done manually. Alumni data is only stored in piles of paper in the administrative space, this can cause data damage and even data loss. The UMG Informatics Engineering tracer study activity provides an increase in education in teaching and learning activities so that it can improve the subsequent learning process. Therefore, to get information on the indications of lack of implementation of the study program the success of professionalism (career, status, and income) of alumni is needed. The Web-based Tracer Study Information System in Informatics Engineering Muhammadiyah Gresik University will be made easier for study programs to get information on relevant knowledge and expertise (the relationship between knowledge and expertise with work requirements, work scope, professional position) of the alumni. The value of the convenience obtained from the application questionnaire by users is 75.95% rounded up to 76%.
SISTEM PENDUKUNG KEPUTUSAN UNTUK DETEKSI DINI RISIKO PENYAKIT STROKE MENGGUNAKAN LEARNING VECTOR QUANTIZATION Sugarwanto Atmaja
Indexia : Informatics and Computational Intelligent Journal Vol 1 No 1 (2019)
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (488.515 KB) | DOI: 10.30587/indexia.v1i1.823

Abstract

Stroke is any sudden neurologic disorder that occurs as a result of restriction or cessation of blood flow through brain arteries supply system. Stroke is the leading cause of death in Indonesia. Services pre-stroke is early detection activities, discovery and monitoring of risk factors for stroke in healthy individuals and at-risk communities that can be performed by physicians, nurses and health workers. Based on the results of the study said that when control stroke risk factors to do with the approach would reduce the number of defects by 60-90%. Works doctor for diagnosis process is not easy because of the many risk factors vary and affect each other, for example Low Density Lipoprotein cholesterol can lead to heart disease can also affect blood pressure, gender can affect the value of uric acid, uric acid can also influence blood pressure and sugar levels can affect blood pressure. Classification method is one solution that is deemed able to handle the process of classifying the status of early detection of the risk of stroke. Mechanical classification using Learning Vector Quantization (LVQ) has excess generating an error value is smaller than other artificial neural networks. Based on the results of research and discussion conducted, algorithms LVQ can recognize patterns and are able to predict the status of early risk of stroke using a variable blood pressure, blood sugar, total cholesterol, Low Density Lipoprotein, age, gender, gout, Blood Urea Nitrogen and creatinine with a total value of up to 82% accuracy.
SISTEM PREDIKSI PENGGUNAAN LISTRIK PELANGGAN DI PT.PLN (PERSERO) RAYON LAMONGAN AREA BOJONEGORO DENGAN METODE TRIPLE EXPONENTIAL SMOOTHING (BROWN) Maslucha Maslucha
Indexia : Informatics and Computational Intelligent Journal Vol 1 No 1 (2019)
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (824.118 KB) | DOI: 10.30587/indexia.v1i1.824

Abstract

Electricity is one of the means of fulfilling the needs of human life which is very important in this era. Excessive use of electricity will have an impact on the high use of electricity kWh. The process of recording kWh on the customer meter is carried out by officers from PLN who routinely visit the customer's homes once a month. The meter recording clerk cannot record when the customer's house cannot be reached resulting in empty customer kWh data. Prediction System Using Electricity Customers at PT. PLN Lamongan aims to determine the amount of electricity usage kWh of the customer for the next period. This research uses the Triple Exponential Smoothing method (Brown). The calculation is done on 10 different customers with 24 data, namely the use of electric kWh per period from January 2015 to December 2016 with 9 different alpha values, namely alpha 0.1 - 0.9 and uses a reference of 3 months, 6 months and 12 months before. Prediction results will be compared with the actual data of kWh to determine the failure value or error value in predictions using mean absolute deviaton (MAD) and mean absolute percentage error (MAPE). From the third average forecasting test analysis, it produces an average MAPE value of 3 months reference with an average value of 2.922%, 6 months reference with an average value of 3.092% and a 12-month reference with an average value of 4.175%. The smallest MAPE, which is a test using a 6-month reference, produces a value of 1.886% with alpha 0.1.
SISTEM PREDIKSI PENJUALAN BARANG BEKAS FABRIKASI DI CV. INDRO JAYA DENGAN METODE SINGLE MOVING AVERAGE Achmad Rifki Rusady
Indexia : Informatics and Computational Intelligent Journal Vol 1 No 2 (2019): Vol 1 No 2 (2019)
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1021.059 KB) | DOI: 10.30587/indexia.v1i2.2537

Abstract

CV.IndroJaya merupakan jasa steel fabrication di area fabrikasi PT Varia Usaha Gresik. Melayani penjualan barang bekas fabrikasi. CV.IndroJaya dalam hal produksi barang jadi pada bulan berikutnya tidak tahu berapa penjualan barang produksi jadi yang nantinya akan dibutuhkan. Jika terjadi kekurangan persediaan penjualan akan menghambat proses penjualan dari jadwal yang sudah ditentukan. CV.IndroJaya memproduksi barang jadi hanya memperkirakan jumlah produksi tanpa memprediksi permintaan barang produksi. Persediaan, stok dan produksi merupakan salah satu faktor penting dalam menunjang keberlangsungan operasional, untuk mengetahui jumlah produksi pada bulan berikutnya, penelitian ini menggunakan metode Single Moving Average. pengujian berdasarkan orde 3x3 (3 bulan sebelumnya) menghasilkan nilai MAD = 55.407 dan MAPE = 13%, pengujian kedua dengan orde 4x4 (6 bulan sebelumnya) menghasilkan nilai MAD = 44.907 dan MAPE = 11,9%, pengujian ketiga dengan orde 6x6 (12 bulan sebelumnya) menghasilkan nilai MAD = 35.75 dan MAPE 12%.
SISTEM ANALISIS FINANSIAL USAHA BUDIDAYA IKAN LELE DENGAN METODE FUZZY TSUKAMOTO Ricky Mahendra Putra
Indexia : Informatics and Computational Intelligent Journal Vol 1 No 2 (2019): Vol 1 No 2 (2019)
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (837.795 KB) | DOI: 10.30587/indexia.v1i2.2538

Abstract

Pada kelompok budidaya ikan dimana pembudidaya ikan lele akan memilih kebutuhan perikanan yang sesuai kebutuhannya. Permasalahanya akhir-akhir ini pembudidaya ikan lele sering mengalami kerugian tiap panennya. Agar mendapatkan keuntungan, pembudidaya disarankankan memilih bahan baku seperti bibit, pakan, obat, populasi, & luas kolam yang sesuai dengan kebutuhan pembudidaya. Penelitian ini menerapkan data mining dengan menggunakan metode Fuzzy Tsukamoto untuk menentukan untung dan rugi budidaya ikan lele. Atribut yang digunakan pada penelitian ini terdiri dari 6 variabel, yaitu musim, populasi, bibit, obat, pakan, dan luas kolam. .Pengujian sistem dilakukan sebanyak tiga kali pengujian. Berdasarkan pengujian yang telah dilakukan diperoleh : hasil prediksi musim hujan, bibit sangkuriang, pakan LP, obat boster, populasi 4000, luas kolam 16 M2 yang dapat menguntungkan pembudidaya. Dari semua hasil penelitian akurasi tertinggi terdapat pada pengujian kedua yaitu dengan nilai prediksi 68,56%.
ANALISIS PERFORMANSI ROUTING PROTOKOL DSR, DSDV DAN ZRP PADA MANET MENGGUNAKAN NETWORK SIMULATOR 2 Aris Dwi Ismail
Indexia : Informatics and Computational Intelligent Journal Vol 1 No 2 (2019): Vol 1 No 2 (2019)
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (915.832 KB) | DOI: 10.30587/indexia.v1i2.2539

Abstract

Routing protokol adalah aturan atau cara pencarian jalur terbaik yang digunakan untuk mengirimkan paket data dari node pengirim ke node penerima. Paket akan melewati beberapa node penghubung melalui mekanisme pembentukan tabel routing. Simulasi dengan menggunakan tools Network Simulator-2 diharapkan dapat membantu menganalisis kemampuan atau kinerja dari masing-masing jenis routing protokol pada kondisi lingkungan jaringan tertentu. Yang nantinya akan didapatkan nilai parameter pengukuran dari routing protokol DSR, DSDV dan ZRP yaitu berupa : Packet Delivery Ratio (PDR), Delay, Konsumsi Energi, Packet Loss, dan Routing Overhead. Analisis performansi dengan melakukan simulasi menggunakan Network Simulator 2 didapatkan hasil parameter konsumsi energi paling hemat pada routing protokol DSDV skenario 10 node dengan 0,9701 joule. Untuk parameter delay mendapatkan hasil 0 m/s. Sedangkan pada parameter routing overhead pada skenario 100 node mendapatkan hasil 4,6707 %. Pada hasil parameter Packet Delivery Ratio (PDR), ZRP memiliki nilai tertinggi pada parameter ini yaitu pada skenario 20, 50 dan 100 node dengan hasil 100 %. Berarti dalam hal keberhasilan routing protokol ZRP dalam mengirimkan paket sangat maksimal, sehingga secara otomatis parameter packet loss akan rendah yaitu 0 %.
EFISIENSI RUTE PADA ROUTING AODV MENGGUNAKAN ALGORITMA PATH AWARE SHORT Saiful Hamim
Indexia : Informatics and Computational Intelligent Journal Vol 1 No 2 (2019): Vol 1 No 2 (2019)
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (908.709 KB) | DOI: 10.30587/indexia.v1i2.2540

Abstract

Node-node pada MANET dapat berhubungan satu sama lain apabila mereka berada pada jangkauan transmisinya. Apabila bergerak menjauh diluar jangkauan transmisi maka link antara dua buah node dapat terputus pada saat proses pengiriman route request (RREQ). Dengan terputusnya suatu link, maka akan menyebabkan terputusnya sebuah rute yang ada dan juga dengan terputusnya link tertentu menyebabkan proses route discovery perlu dilakukan kembali sehingga mobilitas pada node merupakan masalah yang perlu untuk diperhatikan apabila ingin membentuk jaringan yang stabil. Efisiensi rute pada routing AODV menggunakan algoritma path aware short dengan parameter average End-to-end delay, energy, dan packet delivery ratio (PDR). efisiensi rute menggunakan path aware short mengalami keberhasilan dengan parameter average end to end delay untuk 100 node dengan network area 500 m2 x 500 m2 yaitu 5,1087 m/s. Karena selang waktu yang dibutuhkan lebih pendek dan tidak membebani link (kemungkinan kecil terputus). Dampak yang didapat dari efisiensi delay mengakibatkan semakin banyak paket RREQ yang dikirim, mengakibatkan peluang tabrakan antar paket semakin besar, menyebabkan hilangnya paket data yang drop, dikarenakan node pengirim akan lebih banyak melakukan broadcast paket routing pada proses route discovery (RREQ dan RREP) untuk mendapatkan rute yang baru. Dapat dilihat pada parameter packet delivery ratio nilai terbaik pada routing AODV dengan 50 node area 500x500, 100 node area 500x500, 50 node area 1000x1000 dengan nilai 100%. Sedangkan Untuk parameter energy yang sedikit dalam konsumsi energy yaitu pada protokol routing AODV dengan 100 node area 1000x1500 dengan nilai 10,7794 joule.

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