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All Journal Telematika Sistemasi: Jurnal Sistem Informasi Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Indonesian Journal on Software Engineering (IJSE) Perspektif : Jurnal Ekonomi dan Manajemen Universitas Bina Sarana Informatika Jurnal Teknik Komputer AMIK BSI Paradigma Jurnal Komputasi JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Techno Nusa Mandiri Jurnal Manajemen Informatika dan Sistem Informasi JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Infortech Infotech: Jurnal Informatika & Teknologi Reputasi: Jurnal Rekayasa Perangkat Lunak JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Penelitian dan Pengabdian Masyarakat Jotika
Ali Mustopa, Ali
Universitas Bina Sarana Informatika
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Social Sciences Other

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Perancangan Prototipe Aplikasi Mobile Ikatan Alumni (Studi Kasus Universitas Bina Sarana Informatika) Sasongko, Agung; Mustopa, Ali; Risdiansyah, Deni
JUSTIN (Jurnal Sistem dan Teknologi Informasi) Vol 9, No 3 (2021)
Publisher : Jurusan Informatika Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1141.16 KB) | DOI: 10.26418/justin.v9i3.47096

Abstract

Pada penelitian ini membahasa mengenai aplikasi yang diperuntukkan kepada Alumni pada perguruan tinggi Universitas Bina Sarana Informatika untuk menyebarluaskan informasi dari perguruan tinggi maupun mengumpulkan informasi dari alumni.  Aplikasi dikembangkan berbasis mobile. Pengembangan aplikasi dilakukan dengan metode prototipe dengan cara mengumpulkan kebutuhan fungsional sistem dari pengalaman alumni serta komponen instrumen kebutuhan informasi yang berasal dari perguruan tinggi. Hasil analisa kebutuhan  fungsional dilanjutkan dengan  pembuatan desain Usecase dan deployment diagram. Komponen sistem yang dibuat terdari 5 komponen, yaitu: 1.Komponen informasi lowongan kerja dan informasi wirausaha, 2.Komponen rekam riwayat pekerjaan dan penghasilan, 3. Komponen kelola profile diri, 4. Komponen forum percakapan, 5. Komponen pengisian tracer study. Desain rancangan penelitian berdasarkan 5 komponen yang diperlukan menghasilkan 14 rancangan tampilan, yaitu: racangan tampilan Login, Beranda, Pengisian Tracer Study, BSI News, Career dan Enterpreneur News, Forum, Form kirim forum, Daftar Alumni, Daftar Lowongan Kerja, Kegiatan BCC, Profile Diri, daftar riwayat pengalaman kerja, form pengalaman kerja, dan sunting profile diri.
Sistem Pendukung Keputusan Pemilihan Tempat Usaha Potensial dengan Metode SAW (Studi Kasus : SahabatLink Tasikmalaya) Hendri Mahmud Nawawi; Yudhistira Yudhistira; Ali Mustopa; Siti Khotimatul Wildah; Sarifah Agustiani; Muhammad Iqbal
Indonesian Journal on Software Engineering (IJSE) Vol 7, No 1 (2021): IJSE 2021
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/ijse.v7i1.9990

Abstract

Memutuskan tempat untuk membuka usaha adalah hal yang sangat penting dan wajib diperhatikan saat akan memulai bisnis baru atau membuka cabang, sejumlah faktor penting diperhitungkan supaya dapat meminimalisir resiko kerugian di masa yang akan datang sehingga tujuan dari bisnis yaitu meningkatkan keuntungan bisa dicapai secara maksimal, pada penelitian ini sejumlah faktor dicatat dan dijadikan sebagai kriteria untuk menilai tempat usaha yang layak dan potensial berdasarkan hasil observasi dan pengamatan di lapangan pada tempat usaha dengan merk dagang SahabatLink dengan menggunakan metode Simple Additive Weight. Konsep metode SAW adalah mencari penjumlahan terbobot berdasarkan rating kinerja dari setiap alternatif yang ditambahkan dengan banyak kriteria.  Hal ini yang menjadikan metode ini tepat digunakan untuk menentukan keputusan memilih tempat usaha potensial dengan banyak kriteria diantaranya akses, visibilitas, lalu lintas,  persaingan, jarak ke tempat keramaian, tempat parkir, biaya sewa, ekspansi dan konduktivitas.  Hasil akhir dari penjumlahan kriteria inputan dengan metode SAW dapat menjadi rekomendasi bagi pihak manajemen untuk membuka tempat usaha berdasarkan nilai alternatif yang paling tinggi.
Penerapan Metode Pembelajaran Menggunakan Ekstraksi Fitur dan Algoritma Klasifikasi untuk Identifikasi Pengenalan Iris Rahmat Hidayat; Sarifah Agustiani; Siti Khotimatul Wildah; Ali Mustopa; Rizky Ade Safitri
JURNAL TEKNIK KOMPUTER AMIK BSI Vol 7, No 2 (2021): JTK-Periode Juli 2021
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (167.746 KB) | DOI: 10.31294/jtk.v7i2.10548

Abstract

Iris mata terletak di antara kornea mata dan lensa mata, yang berfungsi untuk mengontrol intensitas atau jumlah cahaya yang masuk dengan cara melebarkan dan mengecilkan pupil. Setiap orang memiliki iris yang berbeda dan memiliki stabilitas sepanjang hidup, kecuali terjadi kerusakan yang tidak disengaja pada iris seperti terjadi kecelakaan. Tujuan dari penelitian ini adalah untuk melakukan pengklasifikasian dan identifikasi pengenalan citra iris dengan menggunakan metode pembelajaran atau machine learning. Metode yang diusulkan dalam penelitian ini adalah penerapan ekstraksi fitur seperti HOG, Hu-Moments, dan Haralick dengan algoritma klasifikasi yang terdiri dari LR, LDA, KNN, RF, CART, NB, dan SVM. Berdasarkan hasil pengujian yang telah dilakukan dalam mengklasifikasikan iris dapat disimpulkan bahwa penggunaan ekstraksi fitur sangat berpengaruh pada nilai akurasi yang dihasilkan. Dalam hal ini nilai akurasi terbaik diperoleh dari penggabungan ekstraksi fitur HOG dan haralick pada algoritma Random Forest dengan nilai akurasi sebesar 81.38℅.
Pengaruh Media Terhadap Pengambilan Keputusan Dalam Menjalankan Program Keluarga Berencana Dengan Algoritma Decision Tree Ali Mustopa; Siti Khotimatul Wildah; Ganda Wijaya; Windu Gata; Sarifah Agustiani
Paradigma Vol 22, No 2 (2020): Periode September 2020
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (64.58 KB) | DOI: 10.31294/p.v22i2.8141

Abstract

Indonesia has become one of the countries with a diverse population so that it has the potential to experience social change, one of which is the influence of the media. Media is an information content that is almost a part of human life. One of the impacts of the media is in the health sector, one of which is in determining the Family Planning program. Family planning is one of the Indonesian government programs designed to reduce the speed of population growth. Since the implementation of the Family Planning Program in Indonesia many tools have been used to prevent pregnancy, namely contraception. Selection of a good contraction is certainly one important thing to plan. In determining good kotrasespi certainly there are influences from various things one of which is the media. Measurement of the influence of the media in determining the Family Planning program can be known by applying data mining. Research conducted with data mining uses a standard methodology called the Cross-Industry Center Process for Data Mining (CRISP-DM). The use of decissin tree in this study was done by comparing the same method by looking at the results of three models namely Split Validation, Cross Validation and Decision Tree Split. The results of Split Validation produce an accuracy of 90.50%, Cross Validation produces an accuracy of 91.58% and Decision Tree Split produces an accuracy of 89.83%. The best results are obtained by using cross validation where with the results of research on 1473 records the accuracy value is 91.58% and the AUC value is 0.690, where the results are obtained from the calculation of the True Positive (TP) 1328, False Negative (FN) ) 36, False Positive (FP) is 88 and True Negative (TN) 21. Exposure to the media is said to be good or influential if they do not have children and are Muslim and educate their husbands in junior high school with a low standard of living but the wife has a college education.  Keywords: Family Planning, Media Exposure, Data Mining, Decision Tree.
PENERAPAN ALGORITMA J48 UNTUK DETEKSI PENYAKIT TIROID Sarifah Agustiani; Ali Mustopa; Andi Saryoko; Windu Gata; Siti Khotimatul Wildah
Paradigma Vol 22, No 2 (2020): Periode September 2020
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1113.664 KB) | DOI: 10.31294/p.v22i2.8174

Abstract

Impaired thyroid function is often difficult to identify because the symptoms are not specific. The symptoms of thyroid disorder are very similar to various complaints due to modern lifestyles so it is often overlooked. As a result, patients often do not notice a problem and do not have to consult a doctor. Therefore, there is a study that implements methods to predict the disease which will facilitate the patient in diagnosing and early detection of thyroid levels. This research aims to predict against thyroid disease with the data used is the secondary data obtained from the UCI repository, this data is about the patient data affected by thyroid disease, while the method uses the J48 algorithm because in some studies, the J48 algorithm is proven to have good performance in detecting an illness, as well as producing high value of Accuasy and AUC. The stage of data analysis is based on the CRISP-DM method while algorithm testing is done with Weka tools. Results of the test obtained an accuracy value of 99.645%, and a AUC value of 0.992 thus the accuracy has Excellent Classification level.
Klasifikasi Penyakit Daun Padi menggunakan Random Forest dan Color Histogram Sarifah Agustiani; Yoseph Tajul Arifin; Agus Junaidi; Siti Khotimatul Wildah; Ali Mustopa
Jurnal Komputasi Vol 10, No 1 (2022)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/komputasi.v10i1.2961

Abstract

Indonesia is an agrarian country, which is a sector that plays an important role most of the Indonesian population makes agriculture the main focus, but the function of rice fields into housing or industry has resulted in a decrease in rice production, in addition to pests, diseases, unfavorable weather, Irrigation is not smooth resulting in less than the maximum yield. For this reason, it is necessary to have technology that can implement the process of detecting rice leaf disease in order to provide information to farmers about rice leaf damage. The most modern approach today can be done with machine learning or deep learning by using various algorithms to improve recognition and accuracy in the detection and diagnosis of plant diseases. Based on this, this study aims to propose a method of classifying rice leaf diseases in order to provide information to farmers about rice leaves which are expected to reduce the disease by detecting the disease early so as to increase rice production. In this study, the classification process is carried out using the augmented image, then the Color Histogram feature extraction method is applied, and the classification is carried out using the Random Forest algorithm. In addition, this study also conducted several comparisons, including feature extraction and yahoo to get the results, and the highest results reached 99.65% of the proposed method.
SISTEM INFORMASI REKAM MEDIS BERBASIS WEB PADA PUSKESMAS RASAU JAYA PONTIANAK MENGGUNAKAN FRAMEWORK LARAVEL 5.6 Lady Agustin Fitriana; Abdul Latif; Ali Mustopa; Ahmad Fachrurozi
Jurnal Infortech Vol 1, No 2 (2019): Desember 2019
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (285.987 KB) | DOI: 10.31294/infortech.v1i2.7117

Abstract

Era komputerisasi saat ini membuat dunia kesehatan memanfaatkan teknologi untuk kegiatan yang ada di rumah sakit maupun puskesmas. Namun pada sistem rekam medis yang sedang berjalan dipuskesmas terdapat kekurangan yang menghambat proses rekam medis dibagian pelaporan kunjungan terbanyak menggunakan perhitungan data-data secara langsung dengan melihat data sebelumnya yang sudah dicetak dan penyimpanan identitas pasien dicetak dan diarsipkan kedalam folder. Maka diperlukanlah sistem yang dapat memudahkan agar keakuratan data lebih terjamin dan adanya sistem maka pelayanan menjadi lebih efektif. Dalam pembuatan rekam medis ini, penulis menggunakan framework laravel yang memudahkan programmer dalam membuat dan mengembangkan aplikasi karena memiliki fungsi-fungsi yang sudah di organisasikan untuk membuat program dengan cepat. Buku yang berjudul “Sistem Informasi Rekam Medis (SIRAM) dengan LARAVEL 5.6” ini menjelaskan langkah membuat aplikasi,dimulai dari analisis kebutuhan, rancangan diagramnya seperti use case, activity diagram, ERD dan LRS, class diagram, sequence diagram, serta rancangan lengkap aplikasi seperti rancangan form master, pengolahan rekam medis dan laporan. Buku ini juga membuat kebutuhan dari pengguna aplikasi rekam medis dimana penggunanya terdapat beberapa user yang dapat menjalankan fungsi-fungsi sesuai dengan kebutuhannya.
Analisis Niat Pembelian Pada Instagram Online Shopping Menggunakan Information Acceptance Model (IACM) Wahyutama Fitri Hidayat; Rangga Sanjaya; Ali Mustopa
Bianglala Informatika Vol 8, No 1 (2020): Bianglala Informatika 2020
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (308.472 KB) | DOI: 10.31294/bi.v8i1.7837

Abstract

Along with the development of technology and information, it also has an impact on the product sales media, one of which is through Instagram online shopping. The results of the surf show that comments (electronic word of mount) are on Instagram online shopping. This study aims to analyze the effect of the electronic word of month (EWOM) on purchase intentions using the Information Acceptance Model (IACM) model. The method used in this research is descriptive quantitative to find out the cause and effect relationship of IACM variables. The population in this research is Instagram users who have seen product promotions through Instagram. The sampling technique used is incidental sampling by distributing questionnaires online. The data analysis technique used is multiple linear regression analysis. Based on the results of the research, it can be concluded that the electronic word of mount found on Instagram online shopping has a significant partial effect on purchase intention. This can be seen from the results of the calculation of all the t-count variables 0.191 and the  significance level 0.05. Based on the results of the calculation of the determination coefficient (R2), the magnitude of the effect on the benefits of information is information quality 19.5%, information credibility 41.3%, information needs 13.9%, and attitudes towards information 28.6%. The results of information adoption are affected by 11.2% of the benefits of information. Other lts show that 24.9% of information adoption affects purchase intentions. While attitudes toward information affect 38.9% of purchase intentions.
ALGORITMA KLASIFIKASI NAIVE BAYES DAN SUPPORT VECTOR MACHINE DALAM LAYANAN KOMPLAIN MAHASISWA Hermanto Hermanto; Ali Mustopa; Antonius Yadi Kuntoro
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 5 No 2 (2020): JITK Issue February 2020
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1425.875 KB) | DOI: 10.33480/jitk.v5i2.1181

Abstract

Service in the world of education is an important element for the creation of an academic atmosphere that is conducive to the implementation of a successful teaching and learning process. The process of service to students there is a tendency to be implemented not following the minimum service standards that must be provided to students so that students tend to complain about the services provided. Submission of criticism, complaints, input, or suggestions for dissatisfaction and problems that exist in the university environment is still very limited. Complaints can be constructive if submitted to the right place and party. In this research the data processing of email complaints from students conducted at the academic student body (students.bsi.ac.id). Student complaint data that will be processed is data in the form of * .xls complaint file. Before text data is analyzed using text mining methods, the pre-processing text needs to be done including tokenizing, case folding, stopwords, and stemming. After pre-processing, the classification method is then performed in classifying each complaint category and dividing the status into two parts, namely complaint and not complaint so that the status becomes a normal condition in text mining research. The purpose of this study is to obtain the most accurate algorithm in the classification of student complaints and can find out the results of the classification of the Naïve Bayes algorithm method and Support vector Machine used and compared. In this study, the results of testing by measuring the performance of these two algorithms using Cross-Validation, Confusion Matrix, and ROC Curves. The obtained Support vector Machine algorithm has the highest accuracy value compared to Naïve Bayes. AUC value = 0.922. for the Support vector machine method using the student academic data collection dataset (students.bsi.ac.id) has 84.45%, from the Naïve Bayes algorithm has an accuracy rate of about 69.75% and AUC value = 0.679.
MOBILE-BASED ONLINE EXAM APPLICATIONS USING PROBLEM WEIGHT CLASSIFICATION TECHNIQUES, GROUPING AND RANDOMIZING Muhammad Iqbal; Abdul Hamid; Nuraeni Herlinawati; Mochammad Abdul Azis; Muhammad Rezki; Ali Mustopa
Techno Nusa Mandiri: Journal of Computing and Information Technology Vol 17 No 1 (2020): TECHNO Period of March 2020
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1360.688 KB) | DOI: 10.33480/techno.v17i1.1229

Abstract

Education is an agenda for designing the country's development. Implementation in the field of education is a joint responsibility of both the government and the community, educational institutions are one that plays an important role in the ongoing learning process activities one of which is the examination activities. The test is an evaluation of the learning process to obtain learning outcomes as a form of achievement recognition or completion in an educational unit. The test is still cheating, it is triggered by the lack of confidence in working on the exam questions and the same type of exam questions will provide an opportunity to chat and work together. The author aims to provide a solution in the form of the application of online-based online test applications using question weight classification techniques, grouping and randomization. This mobile-based online exam application was developed using the waterfall model. The results obtained from research on this mobile-based exam application has features to prevent screen capture or screenshots, prevent video recording or video recorder and prevent switching applications that can run multiplatform on Android and iOS. This application has been through the process of testing the user and distributing questionnaires to determine the feasibility of using the weight classification technique with a percentage of 80% so it is suitable for use in examination activities.
Co-Authors Abdul Hamid Abdul Latif Abdul Latif Abdul Latif Agung Sasongko Agus Junaidi Agustiani, Sarifah Ahmad Fachrurozi Andi Saryoko Antonius Yadi Kuntoro Ganda Wijaya Hendri Mahmud Nawawi Hermanto Hermanto Lady Agustin Fitriana Laksono Trisnantoro M Rangga Ramadhan Saelan Maysaroh, Maysaroh Mochammad Abdul Azis Muhammad Fahmi Julianto Muhammad Iqbal Muhammad Iqbal Muhammad Rezki Muhammad Sony Maulana Nanik Wuryani Nuraeni Herlinawati Pribadi, Denny Rabiatus Sa’adah Rahmat Hidayat Rangga Sanjaya Risdiansyah, Deni Rizky Ade Safitri Rusda Wajhillah Siti Khotimatul Wildah Sopiyan Dalis Suharyanto Suharyanto Umi Khultsum Wahyu Nugraha Wahyutama Fitri Hidayat Windu Gata Windu Gata Yoseph Tajul Arifin Yudhistira Yudhistira Yudhistira