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Digital Enterprise Architecture for Green SPBE in Indonesia Indri Sudanawati Rozas; Khalid Khalid; Nita Yalina; Noor Wahyudi; Dwi Rolliawati
CCIT Journal Vol 15 No 1 (2022): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1438.208 KB) | DOI: 10.33050/ccit.v15i1.1366

Abstract

SPBE (Electronic Based Government System) is a legal protection as new breakthroughs in the reform of Indonesian government bureaucracy. The issuance of Presidential Regulation (Perpres) 95/2018 concerning SPBE is expected to be a reference for the transformation from e-Government into i-Government (integrated Government). In the meantime, the government through the Ministry of Administrative and Bureaucratic Reform (PANRB) is drafting an academic paper on the SPBE Bill. Of the 10 elements contained in Presidential Regulation (Perpres) 95/2018, the second element namely SPBE architecture is a concept known in the world of Information Systems as Enterprise Architecture.Enterprise architecture is a conceptual framework that describes how an enterprise is constructed by defining its primary components and the relationships among these components. In SPBE, the main component is defined as domain, consisting of 6 parts, namely: business process architecture domain, data and information, infrastructure, SPBE applications, security, and SPBE services. Unfortunately, the Presidential Regulation (Perpres) 95/2018 has not regulated the concept of Digital Enterprise Architecture, since between Enterprise Architecture (EA) and Digital Enterprise Architecture (DEA) are two things that are significantly different. If EA merely focuses on structuring the company based on the main frame of reference, then DEA focuses on utilizing digital repositories to create living documents as according to the EA framework so that they are easily accessed, modified and managed at any time following the company's development. This study created a DEA model for SPBE in Indonesia. The model created is adapted to the SPBE architecture by carrying out the concept of a digital repository. With digital repositories, time efficiency, paper savings and change management will be easier to achieve. The model created in this study is expected to be utilized to make SPBE much more efficient and green-minded.
DIGITAL QUOTIENT TOOL: ALAT UKUR KECERDASAN DIGITAL Indri Sudanawati Rozas; Khalid Khalid; Widya Veronica; Andhy Permadi; Muhammad Andik Izzuddin
Jurnal Ilmiah Teknologi Informasi dan Robotika Vol 3 No 1 (2021): Juni 2021
Publisher : Program Studi Teknik Informatika Fakultas Ilmu Komputer Universitas Pembangunan Nasional "Veteran" Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/jifti.v3i1.51

Abstract

Abstrak— Sejak bertahun lalu, hasil tes IQ menjadi patokan untuk mengukur kecerdasan seseorang. IQ (Intellectual Quotient) sering diartikan sebagai kemampuan kognitif, bakat, intelektual, kemampuan berpikir, dan kemampuan menggunakan logika secara umum. Namun seiring perkembangan jaman, penelitian mengatakan bahwa EQ (Emotional Quotient) atau juga disebut dengan Emotional Intelligence lebih berpengaruh pada etos kerja dan kemampuan seseorang berbaur dengan tim. Sehingga istilah ini menjadi sangat populer dalam dunia kerja. Baik IQ maupun EQ memililki tool/alat ukurnya masing-masing. Sehingga seseorang dapat dikategorikan ke dalam rentang kurang, rata-rata, atau superior. Belakangan ini, dengan adanya disrupsi teknologi, muncul lagi istilah kecerdasan baru yang disebut dengan Digital Quotient (DQ) yang menunjukkan sebuah set kompetensi manusia terkait dunia digital. Menurut Digital Institute, DQ memiliki 8 variabel inti yaitu; Digital Identity, Digital Use, Digital Safety, Digital Security, Digital Emotional Intelligence, Digital Communication, Digital Literacy, dan Digital Right. Jika dahulu dunia digital hanya milik mereka yang berkecimpung di dunia teknologi dan informasi (segmented) maka saat ini tidak lagi. Semua orang mesti cerdas digital, karena jika tidak cerdas memahami situasi, bisa jadi diri mereka sendiri yang terugikan, misalkan terkait dengan keamanan data pribadi atau bahkan pencurian uang di rekening bank. Untuk itu perlu untuk membuat alat ukur guna mengetahui tingkat kecerdasan digital sebuah individu. Dalam penelitian ini alat ukur tersebut diberi nama DQ tool. Harapannya DQ tool yang dihasilkan mampu menggambarkan skor DQ yang seseorang saat tes dilakukan. Dari hasil pengujian terhadap 72 indikator dalam DQ tool, semua indikator dinyatakan valid. Namun ketika dilakukan uji reliabilitas, ada 6 area yang masih belum reliabel dan memerlukan penelitian lebih lanjut.
Trends and Patterns of The Internet Use During School Holidays Khalid Khalid; Indri Sudanawati Rozas; Dwi Rolliawati
Journal of Information Systems Engineering and Business Intelligence Vol. 6 No. 2 (2020): October
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jisebi.6.2.89-98

Abstract

Background: The Internet use according to Indonesian Internet Services Provider Association (APJII) can be an indicator for parents and educators to monitor students’ mental development and learning behaviors.Objective: This study aims to analyze trends and patterns of the Internet use among students during the school holidays.Methods: This study uses data from XYZ operator, one of the most affordable mobile service providers in Indonesia in 2019. The data was analyzed by using Online Analytical Processing (OLAP).Result: The results shows that the use of 3G and 4G data increased significantly during the school holidays, compared to school days. The highest increase of the Internet traffic is during the semester break, occurred at the rate of 22 to 24 hours a day, with the peak reaching 20.87% at 10:00.Conclusion: The research findings can inform relevant parties, both parents and school teachers in guiding their children to use the Internet.
Topic Modeling Pada Abstrak Skripsi Menggunakan Metode Latent Semantic Analysis Rifqi Hakim; Khalid Khalid; Dwi Rolliawati
FORMAT Vol 11, No 1 (2022)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/10.22441/format.2022.v11.i1.009

Abstract

Abstrak – Skripsi merupakan penelitian akhir bagi mahasiswa strata-1. Dengan semakin bertambahnya dokumen skripsi, maka akan terbentuk informasi dari kumpulan dokumen tersebut. Penelitian ini dilakukan untuk menentukan pemodelan topik dan analisis tren topik dari kumpulan abstrak skripsi Program Studi Sastra Ingris UINSA tahun 2014 sampai 2019. Dari 720 dataset abstrak skripsi dilakukan pemodelan topik dengan metode Latent Semantic Analysis yang meliputi preprocessing, pembobotan term, dan perhitungan Singular Value Decomposition. Pemodelan Topik menghasilkan 20 topik linguistik dan 17 topik literatur. Kemudian pada analisis tren topik, diperoleh 7 tren topik untuk setiap jenis penelitian. Penelitian didominasi oleh penelitian linguistik tindak tutur yang termasuk dalam bidang sosiolinguistik. Berdasarkan hasil analisis jenis penelitian dibandingkan dengan data real jenis penelitian Program Studi Sastra Inggris UINSA, menghasilkan hasil analisis penelitian linguistik memiliki presisi 80% dan recall 90%, sedangkan jumlah penelitian literatur memiliki presisi 74% dan recall 57%, tingkat akurasi analisis jenis penelitian memiliki rata-rata 79%
Seleksi Fitur Dua Tahap Menggunakan Information Gain dan Artificial Bee Colony untuk Kategorisasi Teks Berbasis Support Vector Machine Khalid Khalid; Bagus Setya Rintyarna; Agus Zainal Arifin
Systemic: Information System and Informatics Journal Vol. 1 No. 2 (2015): Desember
Publisher : Program Studi Sistem Informasi Fakultas Sains dan Teknologi, UIN Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (357.391 KB) | DOI: 10.29080/systemic.v1i2.273

Abstract

Salah satu problem yang dihadapi dalam kategorisasi teks adalah dimensi data yang besar yang menyebabkan terjadinya inefisiensi dalam aspek waktu komputasi. Untuk mengatasi hal tersebut, salah satu hal yang bisa dilakukan adalah seleksi fitur pada tahap pre- processing. Pada penelitian ini diusulkan seleksi fitur dua tahap dengan Information Gain dan Artificial Bee Colony. Kategorisasi teks dilakukan dengan Support Vector Machine. Hasil uji coba pada Dataset Reuter21578 menunjukkan adanya peningkatan Precision sebesar rata-rata 15% dan Recall sebesar rata-rata 13% dibandingkan metode pembanding yaitu PSO-SVM.
Metode Hibridasi Artificial Bee Colony dan Fuzzy K-Modes untuk Klasterisasi Data Kategorikal Khalid Khalid
Systemic: Information System and Informatics Journal Vol. 4 No. 2 (2018): Desember
Publisher : Program Studi Sistem Informasi Fakultas Sains dan Teknologi, UIN Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1678.33 KB) | DOI: 10.29080/systemic.v4i2.466

Abstract

Fuzzy K-Modes is an effective method for clustering categorical data. This method is as extensions of fuzzy k-means algorithm by using modes in the process of matching the dissimilarity measure to update centroid of the cluster and to obtain the optimal solution. Nevertheless, Fuzzy K-Modes has the disadvantage of the possibility of stopping in the optimal local solution. Artificial Bee Colony (ABC) is an optimization method that has been proven effective and has the ability to obtain global solutions. This study proposes a hybridization between the Artificial Bee Colony algorithm and Fuzzy K-Modes for clustering categorical data. The implementation of hybridization between Artifical Bee Colony and Fuzzy K-Modes (ABC-FKMO) has been proven to be able to improve the performance of categorical data clustering especially in the aspects of Objective Function, F-Measure, and Accuracy. The test results with datasets of the Soybean Disease, Breast Cancer and Congressional Voting Records from the UCI data repository, showed the Accuracy averages of 0.991, 0.615, and 0.867. Objective Function is better at an average of 2.73%, F-Measure is better at an average of 4.31% and Accuracy is better at an average of 5.16%.
Implementasi Dashboard Akademik Bebasis Website Berdasarkan Instrumen Akreditasi Program Studi 4.0 Roby Ari Putra; Khalid Khalid; Dwi Rolliawati
Systemic: Information System and Informatics Journal Vol. 7 No. 1 (2021): Agustus
Publisher : Program Studi Sistem Informasi Fakultas Sains dan Teknologi, UIN Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29080/systemic.v7i1.1310

Abstract

Accreditation activities aim to evaluate the quality and feasibility of an institution based on the data it has. The accreditation process requires supporting data sources from various documents and different databases, therefore requiring a system for a fast and efficient data collection and visualization process. One of the systems that can be used is a dashboard system and a data warehouse. In this study, the development and implementation of a data warehouse and dashboard system was carried out based on the guidelines for the Department Accreditation Instrument 4.0 (IAPS 4.0) from BAN-PT using the prototyping development method. From the implementation results, 38 quantitative indicators were obtained which can be visualized into the dashboard system. From the testing process using the requirements traceability matrix and functional testing, it was found that all test items successfully passed the test and this system can be used for the accreditation process based on IAPS 4.0 BAN-PT. With this system, it is hoped that the campus department can use it to carry out an independent evaluation process before or during the study program accreditation process.
Comparison of Bagging and Adaboost Methods on C4.5 Algorithm for Stroke Prediction Nur Diana Saputri; Khalid Khalid; Dwi Rolliawati
Sistemasi: Jurnal Sistem Informasi Vol 11, No 3 (2022): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v11i3.1684

Abstract

Stroke is a non-communicable disease and is very dangerous because of functional disorders of the brain caused by blockage of blood circulation. This disease is classified as a cerebrovascular disease because it requires treatment for 24 hours, if not treated quickly it can cause death. The purpose of this research is to overcome this problem is to create a machine learning-based prediction model for medical experts in dealing with diseases to help reduce the risk of death. The method applied for this research is to apply the C4.5 algorithm classification method as well as the bagging and Adaboost methods from Ensemble Learning. Stroke data is processed using 2 stages of data processing, namely the data cleaning stage and the data transformation stage. In this study, a comparison will be made between the C4.5 algorithm, the bagging method + the C4.5 algorithm and the Adaboost method + the C4.5 algorithm using the confusion matrix, k-fold cross validation and validation test based on the values of TP, TN, FP, FN, recall, precision, F1-Score and accuracy. The results of the classification test using the Confusion Matrix and k-fold cross validation for the C4.5 algorithm resulted in an accuracy of 92.87%. Then the accuracy of the C4.5 algorithm with the bagging method increased to 95.02% and when combined with the Adaboost method the accuracy value also increased to 94.63%. From these results, it can be said that a single classifier algorithm, namely the C4.5 algorithm with the bagging and Adaboost methods, has been proven to improve classification performance.
Pemodelan dan Simulasi Produksi Gelang Merpati Pada Home Industry Ozon’s Ring Indah Kusumawati; Novita Khasanah; Aulia Cahya Rani; M. Rizal Abdan K; M. Iqbal Maulana; Dwi Rolliawati; Khalid Khalid
Journal of Economic, Management, Accounting and Technology (JEMATech) Vol 6 No 1 (2023): Februari
Publisher : Fakultas Teknik dan Ilmu Komputer, Universitas Sains Al-Qur'an (UNSIQ) Wonosobo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32500/jematech.v6i1.2375

Abstract

Home industry Ozon’s Ring adalah UMKM yang memproduksi gelang merpati dengan berbagai model. Produksi gelang beberapa kali mengalami overload pada event-event tertentu seperti harbolnas. Penyebabnya dari bahan utama yang kosong dan proses produksi yang lama sehingga permintaan tidak dapat terpenuhi secepatnya. Untuk itu, pemodelan simulasi memberikan alternatif solusi untuk menyelesaikan masalah tersebut. Tujuan dari penelitian ini adalah memaksimalkan produksi dengan mensimulasikan proses yang ada serta sumber daya yang digunakan agar dapat memenuhi target dengan tepat waktu. Dalam penelitian ini, metode empiris digunakan untuk mengumpulkan data dengan melakukan kegiatan wawancara kepada salah satu karyawan home industry. Analisis dilakukan dengan membuat model simulasi proses pembuatan gelang dan skenario simulasi menggunakan aplikasi Anylogic 7.2 Professional. Riset ini menghasilkan tiga skenario alternatif dalam proses produksi gelang merpati dan diperoleh satu skenario terbaik yang dapat meningkatkan kinerja produksi sebesar 164% yaitu maksimalisasi waktu proses jemur menjadi triangular (90, 100, 120) dengan kapasitas produk 110 pcs dalam sekali proses. Sehingga skenario yang disarankan dapat digunakan dengan untuk mengoptimalkan produksi dan meningkatkan kepuasan pelanggan.