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All Journal Jurnal MEKANIKAL MEANS (Media Informasi Analisa dan Sistem)
Abdul Ajiz, Abdul
Department of Mechanical Engineering, Andalas University, Limau Manis-Pauh, Padang, 25137, Indonesia
Computer Science & IT Mechanical Engineering

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PENGARUH SHORT-TIME SOLUTION TREATMENT AND AGING TERHADAP STRUKTUR MIKRO DAN KEKERASAN PADUAN TITANIUM TI-6Al-4V UNTUK APLIKASI IMPLAN BIOMEDIS ajiz, Abdul; Gunawarman, Gunawarman; Affi, Jon
Jurnal MEKANIKAL Vol 6, No 2 (2015): JM Vol. 6 No. 2 Juli 2015
Publisher : Jurnal MEKANIKAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (551.131 KB)

Abstract

Penelitian ini dilakukan untuk memeriksa pengaruh dari short-time solution treatment dan short-time aging terhadap struktur mikro dan kekerasan paduan titanium Ti-6Al-4V. Tujuan dari penelitian ini adalah untuk mendapatkan biomaterial paduan Ti-6Al-4V yang kompatibel untuk penggunaan implan biomedis. Proses perlakuan panas yang digunakan dalam penelitian ini terdiri dari short-time solution treatment dan short-time aging lebih lanjut (st-STA) pada temperatur 490-530 oC, selama 40-60 s. Perlakuan Short-time solution treatment (st-STQ) telah merubah sebagian dari fasa prior β menjadi fasa martensit acicular α'. Perlakuan short-time aging memunculkan presipitat fasa α dalam fasa metastabil β. Perubahan struktur mikro mengakibatkan peningkatan kekerasan paduan  hingga 369 HV. Peningkatan tertinggi terdapat pada paduan yang diberi perlakuan short-time aging lebih lanjut (st-STA) pada temperatur 490 oC (763 K) selama 50 s. Hasil ini menunjukkan bahwa kekerasan paduan Ti‐6Al‐4V sangat tergantung dengan perubahan struktur mikro.
RANCANG BANGUN APLIKASI PENGAJUAN PEMBUATAN KTP ONLINE BERBASIS WEB DI KELURAHAN ARGASUNYA KOTA CIREBON Kencana, Junaedi Surya; Dwilestari, Gifthera; Dana, Raditya Danar; Ajiz, Abdul; Kaslani
MEANS (Media Informasi Analisa dan Sistem) Volume 7 Nomor 1
Publisher : LPPM UNIKA Santo Thomas Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (722.038 KB) | DOI: 10.54367/means.v7i1.1825

Abstract

Argasunya village is an institution responsible for the management of community data in a government environment. The need for public service will involve the state as a public service provider and individual citizens as recipients. But there is no application about the design of the application for the creation of E-KTP online, for that the author tried to make the Final Task regarding the Application for Submission of E-KTP Online which until now has not existed in Argasunya Village. In the process of collecting data with the aim to solve the problem, the author uses methods with data collection techniques, namely by observation and interview. And to design the application, the author used prototype development methods. In order to solve the problem, an application was made to make E-KTP Online. The final result obtained in this study is an application that can make it easier for people to create E-KTP. With some of the advantages that this application has, the application for the creation of E-KTP Online should be able to further alleviate the tasks given to the village. It is expected that this application will always be well controlled in terms of accuracy and data validation can be accounted for so that the information generated will be even better.
Clustering Data Persediaan Barang Dengan Menggunakan Metode K-Means Ramdhan, Dadan; Dwilestari, Gifthera; Dana, Raditya Danar; Ajiz, Abdul; Kaslani
MEANS (Media Informasi Analisa dan Sistem) Volume 7 Nomor 1
Publisher : LPPM UNIKA Santo Thomas Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1056.632 KB) | DOI: 10.54367/means.v7i1.1826

Abstract

UD. Anugerah Sukses Mandiri merupakan perusahaan yang bergerak dibidang distribusi food dan non food. Transaksi barang yang berjalan terus meningkat, sehingga perusahaan mengalami permasalahan dalam menentukan jumlah persediaan barang, dikarenakan jumlah permintaan barang yang dibutuhkan selalu berubah setiap waktu. Persediaan barang merupakan suatu aktivitas lancar yang meliputi barang-barang milik perusahaan dengan maksud dijual kembali pada suatu periode usaha normal. Data mining merupakan proses yang menggunakan teknik statistik, matematika, kecerdasan buatan dan machine learning untuk mengekstraksi dan mengidentifikasi informasi yang terkait dari berbagai warehouse. Tujuan penelitian ini dengan memanfaatkan data mining yaitu untuk melakukan pengelompokan barang dan meningkatkan akurasi klasterisasi data persediaan barang dengan menggunakan metode K-Means Clustering. Dengan metode K-Means ini dapat mempartisi data ke dalam kelompok sehingga data berkarakteristik sama akan dimasukan ke dalam satu kelompok yang sama dan data yang berkarakteristik berbeda dikelompokan kedalam kelompok yang lain, karena metode ini menggunakan centroid (rata-rata) sebagai model dari cluster. Hasil penelitian yang didapat berupa pengelompokan data menjadi 2 kluster yaitu data dengan kluster terendah/sedikit dan kluster tertinggi/terbanyak. Sehingga mendapatkan kesimpulan bahwa clustering persediaan barang dengan menggunakan metode K-Means ini cukup baik dari sisi nilai average within distance dan kompleksitas waktu. Keyword : Data Mining, K-Means Clustering, Persediaan barang
Penerapan Algoritma Decision Tree Dalam Penentuan Karyawan Kontrak Alibasyah, Aziz; Ajiz, Abdul; Dwilestari, Gifthera; Kaslani; Wahyudin, Edi
MEANS (Media Informasi Analisa dan Sistem) Volume 7 Nomor 1
Publisher : LPPM UNIKA Santo Thomas Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (736.756 KB) | DOI: 10.54367/means.v7i1.1844

Abstract

The problem that arises at this time is a complicated evaluation (assessment) process, meaning that what often happens now is that contract employees who get promoted to permanent employees are only seen on one criterion, but the employee is not necessarily superior on several other criteria. but still get promotions for permanent employees. And there are several problems that exist today, namely the process of evaluating contract employees which is still subjective. Data mining using the decision tree method is widely used to deal with problems with large amounts of data. This decision tree method is a classification method that is widely used because its construction is relatively fast, the results of the model built are easy to understand and the prediction results are very strong so that they can assist in decision making. This study uses 4 criteria, namely Achievement, Ability, Personality and Results. Prediction results accuracy obtained is 91.54% with the following details. Prediction results are accepted and it turns out to be true, 72 data are accepted. Prediction Result Accepted and it turns out True Not Accepted for 14 Data. Prediction Results Not Accepted and it turns out True Accepted 1 Data. Prediction Results Not Accepted and in fact True Not Accepted Amounting to 91 Data.
Co-Authors Abdullah Syafii Alibasyah, Aziz G Gunawarman, G Gifthera Dwilestari Jon Affi, Jon Kaslani Kencana, Junaedi Surya Raditya Danar Dana Ramdhan, Dadan Wahyudin, Edi