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All Journal Jurnal Informatika dan Teknik Elektro Terapan KOPERTIP: Jurnal Ilmiah Manajemen Informatika dan Komputer Jurnal Teknik Informatika UNIKA Santo Thomas Jurnal ICT : Information Communication & Technology Infotekmesin Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer JCOSE Jurnal Bimbingan dan Konseling JATI (Jurnal Mahasiswa Teknik Informatika) REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Journal of Computer System and Informatics (JoSYC) MEANS (Media Informasi Analisa dan Sistem) JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Journal of Artificial Intelligence and Engineering Applications (JAIEA) BULLET : Jurnal Multidisiplin Ilmu AMMA : Jurnal Pengabdian Masyarakat Scientica: Jurnal Ilmiah Sains dan Teknologi Jurnal Sistem Informasi dan Manajemen INTERNAL (Information System Journal)

Kaslani

STMIK IKMI Cirebon

Author-ID : 3762985

Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Nursing Social Sciences Other

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Improving Student Achievement Clustering Model Using K-Means Algorithm in Pasundan Majalaya Vocational School Abdul mukhsyi, Sopian; Irma Purnamaari, Ade; Bahtiar, Agus; Kaslani
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 2 (2025): February 2025
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i2.793

This study analyzes and enhances the student achievement clustering model at SMK Pasundan Majalaya using the K-Means algorithm. The Knowledge Discovery in Databases (KDD) method and RapidMiner AI Studio 2024.1.0 were used to process data from 125 students based on 15 metrics, including academic scores and attendance rates. For group evaluation, the Elbow method and Davies-Bouldin Index (DBI) were employed. The results showed optimal clustering with 2 groups and a DBI value of 0.893. Analysis results revealed significant differences in characteristics between the two groups. Cluster_1 consists of 38 students and has lower score patterns (60-80), with attendance rates of 94-100%, and a positive correlation between attendance and academic achievement. On the other hand, Cluster_0 consists of 86 students and shows higher score patterns (67.5-87.5), with attendance rates of 80-100%, and demonstrates a positive correlation between attendance and academic achievement. Schools can use this clustering model to create learning approaches that are better suited to each student group.

Penguatan Kompetensi Lulusan SMK Kota Cirebon Melalui Pelatihan Junior Network Administrator Ali, Irfan; Kaslani; Ayuningsih, Sri; Pardiana, Firda
AMMA : Jurnal Pengabdian Masyarakat Vol. 3 No. 3 : April (2024): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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In today's increasingly advanced digital era, the need for skilled personnel in network administration is growing. This Community Partnership Program aims to provide junior network administrator training for graduates of Vocational High Schools (SMK) in Cirebon City. This training is designed to equip participants with essential basic knowledge and skills in managing and maintaining computer network infrastructure. The material presented includes basic network concepts, network device configuration, fundamental network security principles, and common troubleshooting techniques. It is hoped that this program can enhance the competence of SMK graduates, making them more prepared to enter the workforce in the field of information technology.

Implementasi Dan Analisis Perbandingan Algoritma ID3 Dan C4.5 Dalam Pengukuran Kepuasan Konsumen Kaslani; Nurdiawan, Odi; Muhalim, Alvy
BULLET : Jurnal Multidisiplin Ilmu Vol. 3 No. 1 (2024): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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− Excellent service in order to achieve the goal, to achieve this it is necessary to improve services to these consumers, because these services are still not measured effectively and the services are still not using a method, to assess the services provided to consumers. The main purpose of the consumer satisfaction survey is to calculate customer satisfaction on CV. Bintang Terang Sejahtera by providing questionnaires that have been filled out by consumers, this is to improve and measure the extent of consumer satisfaction. The results of the accuracy of the ID3 algorithm obtained are 99.13% with details, namely Prediction Results Satisfied and Turns True Satisfied with 164 Data, Prediction Results Satisfied and turns True Dissatisfied with 2 Data, Prediction Results Dissatisfied and Turns True Satisfied with 0 Data, Prediction results are not satisfied and it turns out to be true, dissatisfied with 63 data. The results of the accuracy of the algorithm obtained are 95.63% with details, namely the Prediction Results Satisfied and it turns out True Satisfied with 160 Data, Prediction Results Satisfied and turns out to be True Dissatisfied with 6 Data, Predictions Results Dissatisfied and turns True Satisfied with 4 Data, Results Prediction is not satisfied and turns out to be true, dissatisfied with 59 data. comparison of the results of the algorithm, it can be seen from the table that the ID3 algorithm is 99.13% and the Decision Tree Algorithm is 95.63%, meaning that the ID algorithm is better than the decision tree algorithm.

Evaluasi Efektivitas Sistem Rekomendasi Pembelajaran Adaptif Berbasis Deep Learning Dalam Meningkatkan Performa Siswa Kaslani; Anam, Khaerul
BULLET : Jurnal Multidisiplin Ilmu Vol. 2 No. 1 (2023): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Artificial intelligence (AI)-based adaptive learning systems have shown great potential in enhancing the personalization and effectiveness of the learning process. This study evaluates the effectiveness of an adaptive learning recommendation system that utilizes deep learning models, specifically Bi-directional Long Short-Term Memory (BiLSTM), in improving student performance. The model is developed to analyze student interaction patterns on a Learning Management System (LMS) and provide personalized learning material recommendations. The study was conducted through an experiment involving 120 high school students divided into experimental and control groups. The evaluation results indicate that students using the system experienced significant improvements in final scores and completion rates. These findings support the integration of deep learning technology into adaptive learning systems to enhance the effectiveness and personalization of education.

Clustering Analysis of Administrative Service Types Using K-Means (Study Case: Village bojongsalam) Wafiq Azizah; Ade Irma Purnamasari; Agus Bahtiar; Kaslani
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 2 (2025): February 2025
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i2.867

Advances in information technology present significant opportunities for the improvement of public services, especially in relation to the administrative functions of Bojongsalam Village. Reliance on traditional methods often leads to inefficiencies and inaccuracies in administrative processes. This research uses the K-Means algorithm to categorize administrative service data based on service type, document number, printing date, and accompanying remarks. Utilizing the Knowledge Discovery in Databases (KDD) framework, the analysis includes data selection, pre-processing, transformation, and clustering analysis conducted through RapidMiner software. The dataset consisted of 718 administrative records that had undergone a rigorous cleaning process, including attribute normalization. The analysis resulted in an optimal Davies-Bouldin Index (DBI) value of -0.498 at K = 4, with each cluster representing a different service utilization pattern. The issuance of Family Cards (KK) and Birth Certificates showed higher demand compared to other available services. This classification promotes workload optimization, fair resource allocation, and formulation of effective operational strategies. The application of the K-Means algorithm demonstrated its effectiveness in data clustering and made a significant contribution to technology-based administrative management. The findings lay a basic framework for addressing the needs of the community in a timely manner.

Pengembangan Sistem Informasi Management Transaksi Pembayaran Pondok Pesantren Hayati, Umi; Purnama Sari, Ade Irma; Kaslani; Fathurrohman
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 6 No. 2 : Tahun 2021
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54367/jtiust.v6i2.1478

Seluruh transaksi pembayran yang terdapat pada pondok pesantren Nurul Fajri dialihkan menggunakan metode baru menggunakan aplikasi (SIMPONI) pada desktop yang mana seluruh data disimpan secara online untuk mencegah kehilangan data dan memungkinkan pemilik pondok pesantren dapat melihat data transaksi secara real time. Tujuan dari seluruh rangkaian sistem yang dibangun adalah untuk mempermudah proses transaksi dan juga mempercepat proses laporan, baik harian, mingguan bahkan bulanan dengan tingkat kesalahan yang rendah serta tingkat ketepatan yang tinggi. Selain dari tujuan tersebut aplikasi SIMPONI akan menyimpan seluruh proses transaksi yang telah dilakukan secara aman yang memungkinkan dapat di cetak kembali di kemudian hari jika dibutuhkan. Dengan diimplementasikanya Sistem Informasi Management Pembayaran Pondok Pesantren (SIMPONI) ini diharapkan dapat menyelesaikan semua kendala yang didapati pada sistem yang digunakan sebelumnya, baik dari segi ketepatan data maupun kecepatan proses yang dilalui selama melakukan transaksi.

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

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

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

Pemesanan Paket Wedding Organizer pada Cahaya Bridal Decoration Berbasis Web Sukabumi Faturachman, Rifcki Aziz; Rahaningsih, Nining; Basysyar, Fadil M; Kaslani; Tohidi, Edi
MEANS (Media Informasi Analisa dan Sistem) Volume 7 Nomor 1
Publisher : LPPM UNIKA Santo Thomas Medan

The Wedding Organizer package ordering information system is made by utilizing web-lined information technology, with the aim of expanding the area of promotion and sales of wedding packages and simplifying the ordering process. so the author tries to make a Final Project on the Website-Based Website-Based Information System for ordering wedding organizer packages. In the process of collecting data with the aim of solving problems, the authors use data sources (Observation and Interview). The authors Wedding Organizer package ordering information system uses the PHP and MySQL programming languages. For system design, the author uses the Prototype method. The final result obtained in this study is a website-based Information System, which can provide information about several wedding organizer packages, wedding organizer package prices and the contents of wedding organizer packages available at Cahaya Bridal Decoration. With several advantages of website technology as an information medium, the Website-Based Information System for ordering wedding organizer packages is expected to expand the reach of information dissemination to all aspects

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

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 Abdul Ajiz Abdul Ajiz, Abdul Abdul Koda Abdul mukhsyi, Sopian Abi Fajar Ahmad Fauzi Ade Irma Purnamasari Ade Irma Purnamasari agus bahtiar Ahmad Faqih Alibasyah, Aziz Amalia, Dita Rizki Amir Rudin, Rizki Anana Rafly Andi Setiawan Andi Setiawan Andia, Rita Anwar Pauji Anwari, Saeful Aprilyani, Wiwin Aria Pratama Ayuningsih, Sri Bachtiar, Agus Bakri, Saeful Basysyar, Fadhil Muhammad Basysyar, Fadil M Burhanudin, Haris Cep Lukman Rohmat Deffan Febrian Dirmanthara Delisah Destriyanah, Riska Dian Ade Kurnia Dilla Eka Lusiana Dodi Solihin Edi Tohidi Edi Tohidi Edi Wahyudin Edi Wahyudin Ega Salsa Nugraha Eka Permana, Sandy Fansuri, Rafly Fathurrohman Fathurrohman Fathurrohman, Fathurrohman Fatihanursari, Fatihanursari Faturachman, Rifcki Aziz Faturrohman, Faturrohman Fauziah, Irfa Mulhimah Fitriyah, Anis Garsandi, Akmal Maulana Gifthera Dwilestari Haidar Fakhri Hamonangan, Ryan Handayani, Tineka Hartini, Tuti Hayati, Umi Herdiana, Ruli Hermawan, Eman Hery Widijanto Hilman Rifa'i Hira Wahyuni Azizah Iin, Iin Iqbal Agis Junizar Irfan Ali Irfan Ali, Irfan Irma Purnamaari, Ade Irma Purnamasari, Ade Jayawarsa, A.A. Ketut Kencana, Junaedi Surya Muhalim, Alvy Muhammad Aji Pratama Mulyawan Mulyawan Mulyawan, Mulyawan Nining Rahaningsih Nur Atikah Odi Nurdiawan Oktaviani Putri , Farra Oktaviani Putri, Farra Pardiana, Firda Perdana Herdiansyah, Reza Pratama, Denni Puji Rahayu Purnama Sari, Ade Irma Purnamasari, Ade Irma Purnamasari, Ade Purnamasari Putri Siti Nur Hajijah, Regi Raditya Danar Dana Ramdhan, Dadan Rano Rifqi Aqila, Mochammad Rizki Fahrezi Maulana Rizki Lesmana, Ghali Rizky Wahyudi, Febri Rohmat, Cep Lukman Rudi Kurniawan Ryan Hamonangan Salsabila, Putri SANJAYA, RIKI siti azhar Sobari, Syahrul Subhiyanto, Fajar Sukma Maula, Intan Tati Suprapti Tengku Riza Zarzani N Tio Prasetya Tohidi, Edi Tohodi, Edi Tuti Hartati Umi Hayati Vibrianti, Vera Wafiq Azizah Wahyudi, Edi Wahyudin, Edi Wilda Rusmiati Rahayu Zapar, Rizky

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