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All Journal MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Jurnal EECCIS Jurnal Teknologi Informasi dan Ilmu Komputer Format : Jurnal Imiah Teknik Informatika Network Engineering Research Operation [NERO] Indonesian Journal of Artificial Intelligence and Data Mining JURTEKSI Systemic: Information System and Informatics Journal Jurnal Ilmu Komputer dan Desain Komunikasi Visual Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Jurnal Manajemen Informatika dan Sistem Informasi JATI (Jurnal Mahasiswa Teknik Informatika) Scientific Journal of Informatics Journal of Innovation in Educational and Cultural Research Jurnal Inovasi Informatika International Journal of Computer and Information System (IJCIS) Journal of Informatics Management and Information Technology Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Jurnal Sistem Informasi dan Bisnis Cerdas Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) IPSIKOM Jurnal Manajemen Informatika, Sistem Informasi dan Teknologi Komputer (JUMISTIK) Jurnal Bisnis Digital dan Enterpreneur (BISENTER) JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Mujib Ridwan
Universitas Islam Negeri Sunan Ampel Surabaya
Arts Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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Analisis Risiko Pada Pelayanan Percetakan Pass Bandara Menggunakan ISO 31000 Sayyida, Anggy Claudy; Ridwan, Mujib; Wibowo, Achmad Teguh; Rolliawati, Dwi
Jurnal Bisnis Digital dan Enterpreneur (BISENTER) Vol. 3 No. 1 (2025): Jurnal Bisnis Digital dan Enterpreneur
Publisher : STMIK Amika Soppeng

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70247/bisenter.v3i1.132

Abstract

Artikel ini membahas analisis risiko pada pelayanan percetakan pass bandara dengan menggunakan kerangka kerja ISO 31000. Analisis dilakukan untuk mengidentifikasi potensi risiko yang mungkin terjadi, menilai dampaknya, serta merekomendasikan tindakan mitigasi yang diperlukan. Risiko yang diidentifikasi mencakup keterlambatan penerbitan pass, kegagalan sistem teknologi informasi, dan kesalahan dalam penanganan data. Dengan penerapan ISO 31000, sistem manajemen risiko dapat lebih terstruktur, membantu meningkatkan efisiensi dan kualitas layanan. Hasil analisis menunjukkan bahwa beberapa risiko berada pada level tinggi hingga rendah, yang memerlukan tindakan segera untuk meminimalkan dampak negatif terhadap pelayanan.
Komparasi Metode SMOTE dan ADASYN dalam Meningkatkan Performa Klasifikasi Herregistrasi Mahasiswa Baru Risky Agung Nurdian; Mujib Ridwan; Ahmad Yusuf
Jurnal Teknik Informatika dan Sistem Informasi Vol 8 No 1 (2022): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v8i1.4004

Abstract

Universities annually accept new students at the beginning of the new school year. In the acceptance of prospective students on the Seleksi Prestasi Akademik Nasional Perguruan Tinggi Keagamaan Islam Negeri (SPAN PTKIN) di State Islamic University Of Sunan Ampel Surabaya, many prospective students who do not register will have an impact on income of the State Islamic University Of Sunan Ampel Surabaya institution. If the institution can find out early on the probability of a prospective student who will resign, then the management can take action to retain the prospective student. To overcome this, data mining classification can be carried out. The methods used in this classification are decision trees and naïve bayes. The number of students who did not re register compared to reregister resulted in the data being imbalanced. Data imbalances can affect the accuracy of the classification results. The imbalance of the data used can result in an unsuitable model. The solution to handle the data imbalance is to use the SMOTE and ADASYN oversampling methods. The purpose of this study was to compare performance of the SMOTE and ADASYN methods. The results show that the SMOTE method can balance the data in a balanced way compared to ADASYN. From the test results, the SMOTE method is more suitable to use than the ADASYN method because the ROCAUC SMOTE value is higher than ADASYN.  
Penentuan Ekstrakurikuler Siswa Sesuai Minat Bakat dengan Case-Based Reasoning dan Certainty Factor Arjun Sirojul Anam; Faris Muslihul Amin; Mujib Ridwan
Jurnal Teknik Informatika dan Sistem Informasi Vol 7 No 3 (2021): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v7i3.4011

Abstract

Extracurricular activities at MAN 1 Lamongan are still determined without any support from the system. Students are only given extracurricular information and can register according to the conditions if interested. This makes the extracurricular that students have chosen does not fully match their abilities. The result is a decrease in the number of members who are active in extracurricular activities due to loss of interest. A web-based system was developed to assist MAN 1 Lamongan in determining extracurricular according to interests and talents. Case-Based Reasoning (CBR) is the system framework and Certainty Factor (CF) is the algorithm for determining the certainty value. The result is that with test data of 68 students, the system recommends extracurricular well. Testing with Confusion Matrix obtained precision level of 96.03% (high), recall of 99.4% (high), accuracy of 95.76% (high)
ANALISA SERVICE OPERATION TERHADAP APLIKASI GOJEK MENGGUNAKAN ITIL V3 Rahmansyah, Jafa; Ardhani, Alvina; Septiana, Rochmah; Ridwan, Mujib
Jurnal Manajemen Informatika dan Sistem Informasi Vol. 8 No. 2 (2025): MISI Juni 2025
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/misi.v8i2.1383

Abstract

Studi ini bertujuan menganalisis manajemen layanan TI dalam aplikasi Gojek menggunakan kerangka kerja ITIL V3, dengan fokus pada domain operasi layanan. Berdasarkan evaluasi, tingkat kedewasaan (maturity level) dari proses Pengelolaan Acara, Pengelolaan Insiden, Pemenuhan Permohonan, Pengelolaan Masalah, dan Manajemen Akses berada pada Tingkat 4 (Terkelola dan Terukur). Namun, gap analysis menunjukkan kesenjangan pada setiap subdomain, dengan gap tertinggi pada Event Management (0,91) dan terendah pada Access Management (0,67). Untuk mengatasi kesenjangan ini, penelitian merekomendasikan langkah-langkah strategis, seperti meningkatkan monitoring real-time hingga 30%, otomatisasi proses untuk efisiensi hingga 25%, analisis akar masalah untuk meminimalkan insiden berulang, dan penguatan keamanan akses melalui autentikasi dua faktor. Implementasi langkah ini diharapkan dapat meningkatkan kualitas layanan hingga 20%, mengoptimalkan kinerja operasional, dan memperkuat daya saing Gojek di pasar digital.
Analisis Sentimen Pengunjung terhadap Objek Wisata Kabupaten Gresik Menggunakan Support Vector Machine (SVM) dan Linear Discriminant Analysis (LDA) Muhammad Hanafi; Mujib Ridwan; Subhan Nooriansyah
Jurnal Ilmu Komputer dan Desain Komunikasi Visual Vol 10 No 1 (2025): Jurnal Ilmu Komputer dan Desain Komunikasi Visual
Publisher : Fakultas Ilmu Komputer Universitas Nahdlatul Ulama Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55732/t4w4fg43

Abstract

 The tourism sector on the island of Java dominates the flow of domestic travel in Indonesia. East Java contributed the highest number with 198.91 million trips. However, this condition is still not evenly distributed across all regions. Based on the Online Tourist Visit Data (DAKUWISON), it was noted that there was a decrease in tourist visitors in Gresik Regency in 2023. This is not following the PPKM policy that was eliminated in the previous year. This research purposes to analyze the sentiment of reviews using the SVM-LDA classification method to determine their perceptions as an additional data-based opinion for tourism managers. Support Vector Machine (SVM) as a Supervised Learning method is applied in research, besides improving classification by adding the Linear Discriminant Analysis (LDA) dimension reduction method. Data collection from Google Maps with a web scraping technique obtained 3460 reviews. The results of research from the evaluation comparison of each model show that the SVM model with LDA is better than the SVM model without LDA. The f1-score value of the SVM model with LDA is 66% higher than the SVM model without LDA, with an f1-score value of 53%. Based on the results of sentiment classification on 2023 data, it shows that visitor sentiment tends to be positive, with 511 reviews, 456 positive sentiments, 33 negative sentiments, and 22 neutral sentiments obtained.
Improving the Effectiveness of Help Desk Service Management in the Self-Service System at the UIN Sunan Ampel Surabaya Academic Library Al Ghifary, Muhammad Fawaid; Amin, Faris Mushlihul; Ridwan, Mujib; Solakhudin, Muhammad Rafi
Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) Vol 12 No 1 (2025): Jurnal Ecotipe, April 2025
Publisher : Jurusan Teknik Elektro, Universitas Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33019/jurnalecotipe.v12i1.4550

Abstract

The increasing reliance on self-service systems in academic libraries necessitates robust service desk man-agement to ensure user satisfaction and operational efficiency. At the UIN Sunan Ampel Library, self-service systems provide convenient access to various services, but their performance remains underexplored. Evaluat-ing the library's service desk management using the ITIL V4 framework reveals critical insights into its effec-tiveness and areas for improvement. The framework’s Service Desk Practice Success Factors (PSF)—Acknowledge, Classify, Own, and Act—are used to assess how well self-service systems align with ITIL best practices. This research adopts a qualitative descriptive methodology, utilizing interviews and data analysis to evaluate service desk processes. The findings indicate significant benefits in accessibility and user empower-ment through self-service features. However, challenges persist, including manual acknowledgment workflows, insufficient SLA implementation, and limited real-time monitoring capabilities. These issues hinder optimal service delivery and responsiveness. To address these gaps, the study recommends integrating automation for acknowledgment tasks, developing measurable SLA policies, and implementing comprehensive training for library staff. Additionally, real-time tracking tools should be incorporated to enhance system efficiency and user experience. Despite these challenges, the study underscores the potential of ITIL V4 to improve library service desk management, ultimately fostering better user satisfaction and operational excellence.
Perbandingan Pelabelan Otomatis Textblob Dan Vader Lexicon Terhadap Sentimen Ulasan Mobile Banking Livin’ By Mandiri Permadi, Sulton Bagus; Ridwan, Mujib; Yusuf, Ahmad
Systemic: Information System and Informatics Journal Vol. 11 No. 1 (2025): 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.v11i1.2173

Abstract

Salah satu produk mobile banking Livin’ by Mandiri mengalami kelonjakan jumlah pengguna aktif selama periode 3 tahun terakhir. Ulasan yang diberikan oleh para nasabah atau pengguna Livin’ by Mandiri bisa ditinjau dengan memanfaatkan fitur Google Play Store. Tujuan dilakukannya penelitian ini adalah demi mengetahui sentimen terhadap Livin’ by Mandiri dengan membandingkan pengukuran unsupervised learning yakni TextBlob dan Vader Lexicon. Data yang diperoleh dari proses scrapping google play sebanyak 7.952 ulasan dari tanggal 6 Oktober 2023 sampai 5 Maret 2024. Hasil yang diperoleh setelah dibandingkan dengan rating, akurasi pelabelan TextBlob sebesar 44%, sedangkan pelabelan Vader Lexicon sedikit lebih tinggi sebesar 53%. Terjadinya perbedaan pelabelan sebesar 30%, sedangkan persamaan pelabelan sebesar 70%. Frekuensi kata “tidak” cukup tinggi, tidak hanya ada pada ulasan yang berlabel negatif saja, melainkan berlabel positif dan netral juga.
Perancangan Ulang User Experience Website Audit Checklist Menggunakan Metode User Centered Design Maharani, Angelina Putri; Ridwan, Mujib; Wibowo, Achmad Teguh
Jurnal Bisnis Digital dan Enterpreneur (BISENTER) Vol. 3 No. 1 (2025): Jurnal Bisnis Digital dan Enterpreneur
Publisher : STMIK Amika Soppeng

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70247/bisenter.v3i1.129

Abstract

Peningkatan pengalaman pengguna (User Experience) pada website audit checklist PT XYZ dilakukan dengan menerapkan metode User Centered Design (UCD). Dalam era digitalisasi yang pesat, teknologi informasi semakin penting dalam dunia bisnis, terutama dalam proses audit internal yang kompleks. Meskipun website audit telah diluncurkan, banyak fitur yang masih belum memenuhi kebutuhan pengguna, sehingga mengurangi efektivitasnya. Untuk mengatasi tantangan tersebut, langkah-langkah sistematis telah diambil. Proses dimulai dengan identifikasi konteks pengguna, di mana tim mengamati perilaku dan interaksi pengguna dengan website. Selanjutnya, analisis kebutuhan pengguna dilakukan untuk memahami apa yang mereka cari dalam alat audit. Setelah itu, solusi yang dirancang secara inovatif dirumuskan, diikuti oleh evaluasi desain yang melibatkan umpan balik langsung dari pengguna. Hasil dari penerapan UCD menunjukkan bahwa desain website kini lebih sesuai dengan kebutuhan pengguna, yang meningkatkan efektivitas dan efisiensi dalam proses audit. Pengujian fungsionalitas juga menunjukkan peningkatan signifikan, dengan fitur-fitur baru yang lebih intuitif dan mudah digunakan. Dengan demikian, PT XYZ berhasil menciptakan pengalaman pengguna yang lebih baik, meningkatkan kepuasan dan produktivitas tim audit secara keseluruhan.
Implementasi Algoritma Convolutional Neural Network (CNN) Untuk Klasifikasi Kerapihan Ruangan Mahameru, Irfan Andito; Ravly Dwi Septian; Dwi Rolliawati; Mujib Ridwan
Jurnal Komputer Teknologi Informasi Sistem Informasi (JUKTISI) Vol. 4 No. 2 (2025): September 2025
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v4i2.606

Abstract

This study implements a Convolutional NeurallNetwork (CNN) to classify room images into two categories: messy and clean. The model utilizes VGG16 as a feature extractor, followed by fully connected layers and a sigmoid activation function in the output layer. This approach is simpler compared to the softmax scheme, which is commonly used for multi-class classification. The dataset was augmented to enhance the model's generalization. Evaluation results show a validation accuracy of 98,63%, indicating the effectiveness of the model in binary classification tasks
Prediksi Kesiapan Sekolah Menggunakan Machine Learning Berbasis Kombinasi Adam dan Nesterov Momentum Rahayu, Indah Mustika; Yusuf, Ahmad; Ridwan, Mujib
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 9 No 6: Desember 2022
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2022955442

Abstract

Kesiapan sekolah adalah aspek perkembangan anak yang berperan pada kemampuan anak untuk beradaptasi dalam sistematika pendidikan tingkat dasar. Berdasarkan Permendikbud, usia 7 tahun adalah usia yang tepat bagi anak masuk Sekolah Dasar, karena anak telah memiliki kesiapan fisik dan psikis untuk mengikuti proses pendidikan formal. Namun, setiap anak tidak memiliki kondisi yang sama pada usia tertentu. Sehingga, diperlukan Nijmeegse Schoolbekwaamheids Test (NST) untuk mengukur kesiapan sekolah. Instrumen NST hanya dapat digunakan oleh Biro Psikologi yang mempunyai kemampuan dalam melakukan asesmen psikologis. Sedangkan, guru serta orang tua yang memiliki peran dalam bentuk pemberian dukungan dan stimulasi pada anak tidak dapat menggunakan instrumen tersebut. Machine learning adalah teknik yang menggunakan algoritma untuk menemukan pola yang berguna dalam data. Berdasarkan data NST terdahulu, dapat dirancang model prediksi kesiapan sekolah yang akan memudahkan guru dan orang tua dalam mengetahui kesiapan anak untuk masuk Sekolah Dasar. Data penelitian adalah data administratif 225 siswa yang telah mengikuti tes kesiapan sekolah berbasis NST yang diselenggarakan oleh TK Ar-Rasyid pada tahun 2012-2018. Data administratif NST terdiri dari umur, jenis kelamin, urutan anak, jumlah saudara, status TK, pendidikan ayah, pendidikan ibu dan hasil kesiapan sekolah. Berdasarkan korelasi Chi-Square, variabel yang memiliki hubungan signifikan kuat terhadap hasil tes kesiapan sekolah adalah status TK, jumlah saudara dan umur anak dengan nilai p<.05. Penelitian menggunakan algoritma Artificial Neural Network dengan metode optimasi kombinasi Adam dan Nesterov Momentum. Pengujian menggunakan skenario 5-fold cross validation. Hasil penelitian menunjukkan bahwa kombinasi Adam dan Nesterov Momentum memiliki kinerja lebih baik daripada classical Adam dalam memprediksi kesiapan sekolah dengan akurasi 96% dan loss 0.06 dalam 1.98 seconds pada 10 neuron dan 1000 epochs. AbstractSchool readiness is an aspect of child development that plays a role in the child's ability to adapt in the systematics of elementary level education. Based on the Minister of Education and Culture, 7 years is the right age for children to enter elementary school, because children already have physical and psychological readiness to take part in the formal education process. However, every child does not have the same condition at a certain age. Thus, the Nijmeegse Schoolbekwaamheids Test (NST) is needed to measure school readiness. The NST instrument can only be used by the Psychology Bureau who has the ability to carry out psychological assessments. Meanwhile, teachers and parents who have a role in providing support and stimulation to children cannot use these instrument. Machine learning is a technique that uses algorithms to find useful patterns in data. Based on previous NST data, it can be designed as a school readiness prediction model that will facilitate teachers and parents in knowing the readiness of children to enter elementary school. Research data is administrative data of 225 students who have taken the NST-based school readiness test conducted by TK Ar-Rasyid in 2012-2018. NST administrative data consists of age, gender, child position, number of siblings, pre-elementary status, father education, mother education and school readiness results. Based on the Chi-Square correlation, variables that have a strong significant relationship to school readiness test results are pre-elementary status, number of siblings and age with p<.05. The research used Artificial Neural Network algorithms with a combination of Adam and Nesterov Momentum optimization method. Model testing used a 5-fold cross validation scenario. The results showed that the combination of Adam and Nesterov Momentum performed better than classical Adam in predicting school readiness with 96% accuracy and 0.06 loss in 1.98 seconds on 10 neurons and 1000 epochs.
Co-Authors Achmad Teguh Wibowo Ahmad Yusuf Al Ghifary, Muhammad Fawaid Amin, Faris Mushlihul Amin, Faris Muslihul Anam, Arjun Sirojul Anang Kunaefi, Anang Ardhani, Alvina Arjun Sirojul Anam Audi Cahya Lucky Ramadhan Bakti, Satria Wira Bayu Adhi Nugroho Cahyani Fitonah, Rizki Dwi Rolliawati Evi Fatimatur Rusydiyah Faris Mushlihul Amin Hikmah Rossyta Virgiannada Izzah Islamiyyah, Daffah Thoriqotul Izzuddin, Andik Izzuddin, Muhammad Andik Jeffri Dian Asmoro Khalid Khunaefi, Anang Kusnul Prianto, Kusnul M. Machrush Aliy Sirojjam Mushlich Mahameru, Irfan Andito Maharani, Angelina Putri Maula, Muhammad Faruq Rahman Moechammad Sarosa Moh. Rifqi Rahman Mohammad Fauzi Muhammad Hanafi Nurdian, Risky Agung Permadi, Sulton Bagus Pratama, Rakadian Audiga Rahayu, Indah Mustika Rahmansyah, Jafa Ravly Dwi Septian Risky Agung Nurdian Rizka Putri Utami Rolliawati, Dwi Rudi Setiawan Salsabila Nasution, Amanda Sayyida, Anggy Claudy Septiana, Rochmah Siti Murni Rochmatin Solakhudin, Muhammad Rafi Subhan Nooriansyah Sururin Darina Suyono, Hadi Ulumiyyah, Ikrimatul Utama, Arya Prayogi Yalina, Nita Yulianto, Novin Ardian Yunita Ardilla Yusuf Amrozi Zainul Abidin