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All Journal Jurnal Ilmiah KOMPUTASI JITK (Jurnal Ilmu Pengetahuan dan Komputer) International Journal of Supply Chain Management Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Abdi: Jurnal Pengabdian dan Pemberdayaan Masyarakat International Journal of Business, Economics, and Social Development International Journal of Electronics and Communications Systems JSEP (Journal of Science Education and Practice) Journal of Engineering and Information Technology for Community Service Jurnal Pemberdayaan Masyarakat Kenduri: Jurnal Pengabdian Dan Pemberdayaan Masyarakat ABDIMAS Iqtishadia Indonesian Journal of Statistics and Its Applications Jurnal Pengabdian Masyarakat Inovatif Jurnal Pengabdian Masyarakat Inovatif
Asep Saepulrohman
Universitas Pakuan
Religion Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Medicine & Pharmacology Public Health Social Sciences Transportation Other

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Implementation of Earth Structure Learning Applications Using Markerless Augmented Reality Using Surface Tracking Method Saepulrohman, Asep; Zuraiyah, Tjut Awaliyah; Prastio, Agung Dwi
JOURNAL OF SCIENCE EDUCATION AND PRACTICE Vol 7, No 1 (2023): June 2023
Publisher : Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/jsep.v7i1.7354

Abstract

In science lessons at school there are materials that are taught, one of which is a lesson about the layers of the earth. As an alternative learning media, Augmented Reality technology is needed which can help teachers have a variety of learning media, so that they can accommodate the learning needs of students who have various types of learning characteristics. In this study the authors made augmented reality using markerless so that they could display or show how the structure of the earth's layers looks like seeing directly without markers or markers. Using EasyAR as a Software Development Kit (SDK) because it has many features and methods that can be used for creating augmented reality.  
Pendampingan Integrasi Kearifan Lokal Kampung Urug ke dalam Bahan Ajar Suci Siti Lathifah; Stella Talitha; Asep Saepulrohman; Eka Suhardi; Sandi Budiana; Surti Kurniasih
ABDI: Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol 6 No 4 (2024): Abdi: Jurnal Pengabdian dan Pemberdayaan Masyarakat
Publisher : Labor Jurusan Sosiologi, Fakultas Ilmu Sosial, Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/abdi.v6i4.973

Abstract

Penerapan Kurikulum Merdeka di Indonesia menekankan pentingnya integrasi kearifan lokal dalam proses pembelajaran untuk meningkatkan relevansi dan efektivitas pendidikan. Tujuan dari kegiatan ini adalah untuk meningkatkan pemahaman dan keterampilan guru dalam menggunakan elemen-elemen budaya lokal dalam materi pembelajaran, serta untuk menciptakan bahan ajar yang lebih kontekstual dan menarik bagi siswa. Metode yang digunakan mencakup pemetaan kearifan lokal Kampung Urug, pelatihan dan workshop untuk guru, pengembangan bahan ajar digital, serta evaluasi dan tindak lanjut. Sebanyak 80% guru yang terlibat dalam pelatihan melaporkan peningkatan pengetahuan tentang kearifan lokal Kampung Urug dan kemampuan untuk menggunakan alat digital dalam pembuatan materi ajar. Peserta juga menunjukkan antusiasme dalam menerapkan teknik-teknik baru yang diperoleh selama workshop, dengan beberapa di antaranya sudah mulai mengembangkan materi ajar yang mengintegrasikan elemen lokal. Hal tersebut didukung dengan hasil angket yang menyatakan bahwa semua guru termotivasi untuk membuat bahan ajar digital berbasis kearifan lokal untuk dapat diimplementasikan dalam proses pembelajaran.
Penerapan Algoritma Deep Learning Pada Robot Deteksi Botol Ismangil, Agus; Gandhy, Abel; Saepulrohman, Asep; Putra, Gustian Rama; Drajar, Muhamamd Bintang; Taufiq, Muhammad; Azha, Arrazy
Jurnal Ilmiah Komputasi Vol. 23 No. 4 (2024): Jurnal Ilmiah Komputasi : Vol. 23 No 4, Desember 2024
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32409/jikstik.23.4.3759

Abstract

Dalam penelitian ini, algoritma deep learning digunakan untuk robot otonom yang mendeteksi botol. Pengembangan robot yang mampu berinteraksi dengan lingkungan bergantung pada kemampuan robot untuk mendeteksi objek. Dalam penelitian ini, algoritma deep learning digunakan untuk mengidentifikasi dan mendeteksi botol dalam berbagai kondisi pencahayaan dan sudut pengambilan gambar. Algoritma ini terutama menggunakan model berbasis jaringan saraf tiruan (neural networks), seperti Convolutional Neural Networks (CNN). Studi ini menunjukkan bahwa penggunaan model deep learning meningkatkan akurasi deteksi botol hingga 95%. Ini menunjukkan bahwa model ini dapat digunakan dengan baik dalam sistem robotika kontemporer
Expert System for Early Diagnosis of Epilepsy Using the Web-Based Dempster Shafer Method Zulfa, Rulla Aliyah; Saepulrohman, Asep; Karlitasari, Lita
International Journal of Business, Economics, and Social Development Vol 5, No 3 (2024)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijbesd.v5i3.735

Abstract

The development of information and communication technology is currently very extensive in its use, especially technology in the field of computers. Expert Systems are one of the sciences in the field of computers that can help in diagnosing various diseases, one of which is epilepsy. The estimated number of epilepsy sufferers in Indonesia is 1.5 million with a prevalence of 0.5-0.6% of the Indonesian population. The expert system method used to diagnose epilepsy early is the Dempster Shafer method. The Dempster Shafer method is used to combine separate pieces of information or evidence to calculate the probability of an event. This study used 7 types of epilepsy, including in the Focal Epilepsy category consisting of Simple Partial and Complex Partial, while in the General Epilepsy category consisting of Absence, Atonic, Myoclonic, Tonic-Clonic, and Clonic. This study produces a website-based application for early diagnosis of epilepsy using the Dempster Shafer method with the PHP programming language and MySQL database. By using this application, it can provide convenience to the medical community and patients in early diagnosis of epilepsy experienced by sufferers. From the results of this study, it was found that the highest level of accuracy was found in Tonic-Clonic seizures which are included in the General Epilepsy category, namely 92.78%.
Segmentation and Positioning of Lecturers in the Department of Computer Science at Pakuan University Based on Student Assessment: Segmentasi dan Positioning Dosen Jurusan Ilmu Komputer Universitas Pakuan Berdasarkan Penialian Mahasiswa Yusma Yanti; Asep Saepulrohman
Indonesian Journal of Statistics and Applications Vol 5 No 1 (2021)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v5i1p92-104

Abstract

Determining the segmentation and positioning of the lecturers in selecting the thesis supervisor is very important to do. It is because, with this information, the supervision process in thesis writing can run well. This study intends to analyze the segmentation and positioning of lecturers related to determine the thesis supervisor using the Clusterwise Bilinear Spatial Multidimensional Scaling Model (CBSMSM) method. The data used is survey data for fifth-semester bachelor students of the 2019/2020 academic year of the Department of Computer Science, Pakuan University. One hundred sixty-one student observations provide an assessment of 10 attributes regarding the characteristics of 32 lecturers of the department. Furthermore, the estimation of the segment coordinate parameters, lecturer coordinates, dimensions, and attributes simultaneously uses the alternating least square (ALS) algorithm. The number of segments and dimensions are selected based on the smallest sum square error (SSE) value for combining segments and other dimensions. As a result, we get four segments and four dimensions with an SSE value of 4864.003. Furthermore, the department can use this result to illustrate student assessments of their lecturers' characteristics regarding thesis supervision.
OUTSOURCED EMPLOYEE RECRUITMENT DECISION SUPPORT SYSTEM WITH FUZZY TOPSIS INTEGRATED REST API METHOD Asep Denih; Asep Saepulrohman; Febri Febriansyah
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 10 No. 3 (2025): JITK Issue February 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v10i3.5521

Abstract

PT Dina Mika Muda Mandiri is a logistics and transportation company that is facing challenges in recruiting outsourced employees to meet the company's standards with complex assessment criteria. In overcoming this problem, the research developed a decision support system that is integrated with Rest API and the Fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The system aims to improve the efficiency and accuracy of candidate selection by evaluating criteria such as interviews, knowledge, testing, curriculum vitae (CV), processing time, and salary. Two case studies were conducted involving 36 applicants for a website upgrade project and 24 applicants for an outsourced goods transit system. The results demonstrate that the decision support system integrated with Fuzzy TOPSIS significantly enhanced the selection process, improving accuracy by 91% for the website upgrade project and 97% for the goods transit system when compared to traditional human resource development (HRD) decision criteria. This demonstrates the system's effectiveness in aligning with HRD standards, making the recruitment process more effective, accurate and efficient. Future research should explore methods to refine the weighting of criteria and integrate expert opinions or more sophisticated machine learning algorithms to support more objective decision support systems in outsourcing employee recruitment.
Alih Teknologi PKM Penjahit dengan Peningkatan Kualitas Pelayanan melalui CRM Saepulrohman, Asep; ismangil, Agus; Heliawati, Leny
ABDIMAS Iqtishadia Vol. 1 No. 2 (2023): ABDIMAS Iqtishadia
Publisher : Prodi Ekonomi Syariah Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/iqtis.v1i2.37338

Abstract

Dunia usaha dalam bentuk jasa merupakan salah satu bentuk bisnis yang memerlukan marketing untuk tetap dapat berjalan atau meningkatkan omset yang lebih baik lagi. UMKM Sarinah Tailor merupakan salah satu UMKM yang mengalami dampak penurunan ekonomi yang luar biasa sejak  pademi Covid-19. Kreativitas dan inovasi harus dimunculkan  sebagai wujud eksistensi di tengah pasca wabah pandemik yang masih ada sampai saat ini untuk tetap bertahan harus melakukan berbagai berbagai kreativitas. Salah satunya, digitalisasi sistem pemasaran, update trend fashion, memperbanyak relasi, memberikan layanan terbaik, bekerjasama dengan instansi, dan lain-lain. Metode dalam Pemberdayaan Kemitraan Masyarakt (PKM) ini difokuskan pada digiitalisasi sistem dan pengembangan konsep relasi dengan metode Customer Relation Management (CRM) yang memadukan bisnis antara porses, manusia dan teknologi. Hasil dari pemberdyaaan tersebut terbantunya mitradalam bidang marketing secara digital dan manajemen perubahan sistem pemsaran yang bersfiat kombinasi antara konsep pemaran sebelumnya dan sistem berbasis online. Hasil yang diperoleh membantu menarik prospek penjualan dan mengkonversi pelanggan yang sudah ada tetap loyal dan puas dengan pelayanan bisnis yang dijalankan oleh mitra.
The Effect of Cerium Doping on LiTaO3 Thin Film on Band Gap Energy Ismangil, Agus; Subiyanto, Subiyanto; Sudradjat, Sudradjat; Prakoso, Wahyu Gendam; Saepulrohman, Asep
International Journal of Electronics and Communications Systems Vol. 1 No. 2 (2021): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v1i2.7906

Abstract

Lithium tantalite LiTaO3 was grown on a Si Type-P (100) substrate by chemical solution deposition and spin coating methods at a speed of 3000 rpm for 30 seconds with an annealing temperature of 800 ° C, 900 ° C. This study aims to determine the effect of temperature variations on the band gap energy. The results show that the energy band gap value of the thin film has a significant impact on the interpretation of annealing temperature. It can be seen that a high energy band gap peak occurs at an annealing temperature of 900 ° C and a time of 15 hours of the energy band gap of 1,49 eV. This shows the effect of temperature variations on the energy band gap to move from the valence band to the conduction band, which will produce current.
Data integrity and security of digital signatures on electronic systems using the digital signature algorithm (DSA) Saepulrohman, Asep; Ismangil, Agus
International Journal of Electronics and Communications Systems Vol. 1 No. 1 (2021): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v1i1.7923

Abstract

The digital signature generation process begins with the creation of a public key and a private key. A public key is generated and published to verify the signature and calculate the hash value of the received document. At present, in the very fast development of information technology, quantum computers have emerged the ability to solve very large and complex amounts of data calculated by qubits, which when compared to quantum computers can work 10 minutes to work on a process that takes 1025 years on a computer. Therefore, the research focuses on how electronic signatures on documents have a reliable security system. The Digital Signature Algorithm (DSA) is a key algorithm used for digital signatures, which uses the Secure Hash Algorithm (SHA-1) to convert messages into message digest and parameters based on the ElGamal signature algorithm. The author also shows an example of digital signature encryption and decryption process by taking any numbers p = 59419 and q = 3301 to prove that the message can be formed and verified its authenticity.
Optimization of Stock Price Prediction Using Long Short-Term Memory (LSTM) Algorithm and Cross-Industry Standard Process Approach for Data Mining (CRISP-DM) Saepulrohman, Asep; Chairunnas, Andi; Denih, Asep; Safitri Yasibang, Nurdiana Dini
International Journal of Electronics and Communications Systems Vol. 5 No. 1 (2025): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v5i1.26727

Abstract

Predicting stock prices accurately is an integral part of investment analysis as it permits forecasting movements in the financial markets and tailoring strategies accordingly. In this study, the LSTM (Long Short-Term Memory) algorithm is used with the aim of improving predictive accuracy, particularly the forecasting of stock price movements. This research follows the CRISP-DM framework or Cross-Industry Standard Process for Data Mining, which incorporates six defined steps including: understanding the business context, data understanding, data preparation, model building, evaluation, and implementation. Stock price data for the ticker symbol “ANTM.JK” was sourced from Yahoo Finance for the date range of October 29, 2005 to July 11, 2024. Along with the consistency, several model accuracy enhancing preprocessing steps such as data cleaning, feature selection, and normalization with Python were performed before modeling. Hyperparameter tuning to reduce the error margins on predictions was conducted after training the LSTM model. Testing the hypotheses showed that the LSTM model demonstrated a low Root Mean Square Error (RMSE) on the test dataset indicating outstanding forecasting accuracy. The ability of the model to outperform conventional time series forecasting techniques is attributed to its ability to effectively retain nonlinear time-series relationships and long-term dependencies. These findings suggest that the LSTM algorithm can serve as a reliable tool for stock price forecasting in emerging markets. This study provides practical insights for investors and lays the groundwork for future research on hybrid or ensemble models to further improve prediction robustness and accuracy
Co-Authors Adinda Adriansyah, Putri Nabila Adriana Sari Aryani Agita Tiara Putri Agung Prajuhana Putra Agus Ismangil Andi Chairunnas Arie Qur’ania Arief Rachman Hakim Asep Denih Asep Denih Azha, Arrazy Deden Ardiansyah Drajar, Muhamamd Bintang Eka Suhardi Endang Soeryana Hasbullah Erna Selviyanti Febri Febriansyah Gandhy, Abel Gesa Rizky N Gustian Rama Putra Gustian Rama Putra Gustian Rama Putra Hermawan Hermawan Hidayatulah, Syarif I Wayan Sriyasa I Wayan Sriyasa Kotim Subandi Lathifah, Suci Siti Layung Paramesti Martha Leny Heliawati Lita Karlitasari Lusi Agus Setiani Muhammad Taufiq Nabila Adinda Adriansyah, Putri Negara, Teguh Puja Oktavian Nursetiaji Olandina Cahyani P Prastio, Agung Dwi Puspa Citra Putra, Gustian Rama Putri Nabila Adinda Adriansyah Safitri Yasibang, Nurdiana Dini Sandi Budiana Sri Setyaningsih Stella Talitha Subiyanto Subiyanto Sudradjat Sudradjat Sudradjat Sudradjat Sukono . Surti Kurniasih Suyudi, Mochammad Syarif Hidayatullah Taruma Leo Wijaya Tjut Awaliyah Zuraiyah Tri Aminingsih Victor Ilyas Sugara Wahyu Gendam Prakoso Wahyu Gendam Prakoso, Wahyu Gendam Wahyu Sardjono Wahyu Sardjono Yusma Yanti Zulfa, Rulla Aliyah