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All Journal Jurnal Ilmu Komputer dan Informasi Jurnal F. Teknik : RESULTAN Techno.Com: Jurnal Teknologi Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Teknik Komputer AMIK BSI Cakrawala : Jurnal Humaniora Bina Sarana Informatika Paradigma Jurnal Ilmiah FIFO Bina Insani ICT Journal Jurnal Pilar Nusa Mandiri Information System for Educators and Professionals : Journal of Information System Jurnal Mahasiswa Bina Insani Informatics for Educators and Professional : Journal of Informatics Information Management For Educators And Professionals (IMBI) Jurnal Teknik Informatika STMIK Antar Bangsa Techno Nusa Mandiri : Journal of Computing and Information Technology Jurnal Komtika (Komputasi dan Informatika) IKRA-ITH EKONOMIKA Jurnal ICT : Information Communication & Technology JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Kajian Ilmiah Jurnal Sistem Informasi Jurnal ABDIMAS (Pengabdian kepada Masyarakat) UBJ Jurnal Sains Teknologi dalam Pemberdayaan Masyarakat Journal of Students‘ Research in Computer Science (JSRCS) PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer Jurnal Pengabdian Masyarakat Information Technology (JPM ITech) INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS : Journal of Information System Journal of Computer Science Contributions (Jucosco) Jurnal Komtika (Komputasi dan Informatika)
Herlawati Herlawati
Fakultas Ilmu Komputer, Universitas Bhayangkara Jakarta Raya
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Social Sciences Other

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PENERAPAN MICOROSOFT EXCEL PADA METODE KUANTITATIF BISNIS DENGAN ANALYTICAL HIERARCHY PROCESS (PROSES ANALITIS HIERARKIS) Herlawati, Herlawati
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 1 No. 1 (2013): Januari 2013
Publisher : LPPM Universitas Islam 45 Bekasi

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Abstract

ABSTRAK Pengamatan mendasar tentang sifat manusia, pemikiran analitik, dan pengukuran membawa pada pengembangan suatu model yang berguna untuk memecahkan persoalan secara kuantitatif. Analytical Hierarchy Process (AHP) merupakan suatu model yang luwes yang mampu memberikan kesempatan bagi perorangan atau kelompok untuk membangun gagasan-gagasan dan mendefinisikan persoalan dengan cara membuat asumsi mereka masing-masing dan memperoleh pemecahan yang diinginkan darinya. Proses ini juga memungkinkan orang menguji kepekaan hasilnya terhadap perubahan informasi. Beberapa keuntungan penggunaan metode AHP adalah kesatuan, kompleksitas, saling ketergantungan, penyusunan hierarki, pengukuran, konsistensi, síntesis, tawar menawar, penilaian dan konsensus serta pengulangan proses. AHP merupakan salah satu tools dalam pemecahan masalah yang bersifat strategis, dalam hal ini digunakan software Microsoft Excel. Kata Kunci : AHP, kuantitatif, hierarki, excel ABSTRACT Basic research about human characteristic, especially in analythical thinking and measurement bring to a model that usefull for solving quatitativ problems. Analytical Heararchy Proces (AHP) is a model that flexibly can give the opportunity for individual or community to build the idea and define a problem with their assumption. This process also suitable for someone to give a test in regards to sensitivity of information change. Some benefits of AHP are: integrity, complexity, inter dependency, hierarchy position of information, consistency, synthesis, bargaining, checking and consensus, and process iterative. AHP is a tool for solving strategic problem that using Microsoft Excel in this paper. Keyword : AHP, quantitative, hierarchy, excel
KLASIFIKASI DINAMIS DENGAN MODIFIKASI ALGORITMA FUZZY C-MEANS (FCM) Herlawati, Herlawati; Handayanto, Rahmadya Trias
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 1 No. 2 (2013): September 2013
Publisher : LPPM Universitas Islam 45 Bekasi

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Abstract

ABSTRACTAside forecasting, classification is an important process in the data mining field. Nowdays, theclassification usually use soft computing algorithms, such as Fuzzy Inference System (FIS), NeuralNetworks (NNs), and Genetic Algorithms (GAs). Different from K-Means, the fuzzy-based classification issometimes is said soft clustering. Some dynamic method has been research using K-Means for obtaining theoptimal number of cluster. This paper try to implement this method for FCM algoritms because thisalgorithms run better than K-Means. Similar to Dynamic Clustering using K-Means, for FCM everyelements of cluster are counted the distance from the center. Key Workds : Fuzzy C-Means Clustering (FCM), Cluster Quality, Dynamic Classification ABSTRAKSelain peramalan, klasifikasi merupakan salah satu proses penting dalam bidang data mining. Saat iniklasifikasi banyak dilakukan dengan algoritma-algoritma yang berbasis soft computing seperti fuzzy,jaringan syaraf tiruan (JST) ataupun algoritma genetik. Berbeda dengan K-Means, klasifikasi berbasis fuzzyyang sering disebut fuzzy C-Means (FCM) merupakan klasifikasi halus (soft clustering). Beberapa metodedinamis dengan memodifikasi algoritma K-Means telah banyak dilakukan dan terbukti memiliki hasil yangoptimal. Tulisan ini bermaksud menerapkan metode dinamis itu pada algoritma FCM mengingat FCMmemiliki keunggulan tertentu dibanding K-Means. Seperti pada K-Means, klasifikasi dinamis pada FCMmenunjukkan perbaikan pada nilai intra dan inter dimana nilai-nilai tersebut menunjukkan kedekatan antarelemen tiap kluster dan seberapa jauh jarak pisah antar pusat-pusat kluster. Kata Kunci : Fuzzy C-Means Clustering (FCM), Kualitas Kluster, Klasifikasi Dinamis
Strategy Planning for Rice Seed Producer’s Information System Using Anita Cassidy Method Jaja, Jaja; Purwanti, Santi; Herlawati, Herlawati
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 8 No. 2 (2020): September 2020
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v8i2.2277

Abstract

Strategic planning of information systems on seed producers is an action that needs to be taken in order to maintain and make the business grow faster. However, such information system usually been created through the system development life cycle (SDLC) or other methods that appropriate for business. This study used Anita Cassidy method for strategic planning of rice seed producer’s information systems in XYZ Ltd., as case study. The following stages has been done, i.e. visioning, analysis, direction, and recommendations. The final results of the stages carried out recommend business applications that can be implemented, namely: Rice seed certification information systems, E-Commerce of Rice Seeds, Rice Type Determination Applications, Irrigation Control Applications, Paddy Pest Resolution Applications, Rice Growth Monitoring Applications, Personnel Information Systems, Payroll Information System, Procurement Information System, Financial Information System. Keywords: Information Systems, Information Systems Strategic Planning, Anita Cassidy Method
Identification of Website-Based Product Sales Frequency Patterns using Apriori Algorithms and Eclat Algorithms at Rio Food in Bekasi Pramuhesti, Salwa Nabiila; Herlawati, Herlawati; Lestari, Tyastuti Sri
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 11 No. 1 (2023): March 2023
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v11i1.5941

Abstract

Sales reports that are not managed automatically may hinder businesses from accurately determining their progress in the short or long term. With increasing community needs for a product, business owners have an opportunity to market their products to a larger audience. The abundance of data highlights the need for information to produce patterns that can be used as a reference for making decisions in buying products on the website. Data mining algorithms can provide support for analysis, which can help avoid inaccurate business progress reports. In this study, the Apriori and Eclat algorithms were applied to analyze frequent itemsets in association rule mining. The dataset used in this study consists of 20 transaction data from frozen food sales. The results showed that the combination of Nugget and Chicken Sausage itemsets were the most frequent, with higher support, confidence, and lift ratio values than the others. These results can be used as product recommendations that are most in demand by customers.
Sentiment Analysis of On-Demand Ride-Hailing Systems using Support Vector Machine and Naïve Bayes Wiguna, Bhagaskara Farhan; Herlawati, Herlawati; Yusuf, Ajif Yunizar Pratama
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 11 No. 2 (2023): September 2023
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v11i2.7384

Abstract

Gojek is one of Indonesia's most popular online transportation, founded in 2010. The Gojek application has been downloaded one hundred forty-two million times with more than two million drivers and four hundred thousand partners in food delivery services. Due to the increasing use of the Gojek application and the importance of knowing user views about the services provided by the application. In this research, the sentiment analysis is using Support Vector Machine and the Naïve Bayes method to classify positive sentiment and negative sentiment. The target label focus on positive and negative labels to aims avoid the bias that exists in neutrally labeled reviews on the Gojek Application. The research process includes data collection, pre-processing the data, weighting with Term Frequency-Invers Document Frequency, Support Vector Machine, and Naïve Bayes training by dividing the data into 90% training data and 10% testing data and then evaluating the results using a confusion matrix. The results of testing using the Support Vector Machine algorithm resulted in 90% accuracy, 94% recall, 91% precision, and 94% f1-score, therefore the Naïve Bayes algorithm produces 77% accuracy, 96% recall, 77% precision, and 85% f1-score.
Learning Tools for Artificial Intelligence Implementation Herlawati, Herlawati
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 12 No. 1 (2024): March 2024
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v12i1.9476

Abstract

According to the rules of the Indonesian National Qualifications Framework (KKNI), undergraduate students fall into levels 5 and 6. Here, graduates are required to have the ability to apply existing knowledge according to the needs of the job. However, laboratory facilities that provide such competencies are very difficult to provide, especially for private campuses that rely on funding from students. This research tries to anticipate the gap between students' abilities and industry demands by providing laboratory facilities that do not require large costs. One of the courses demanded for students to master is Artificial Intelligence (AI), which has now spread to various fields. However, the curriculum currently applied usually focuses only on methods commonly used in the field of AI, while implementation in corporate fields requires direct application in the form of applications. Research results prove that several online applications can be used as substitutes for laboratories, including Google Colab, Play with Docker, Streamlit, and Teachable Machine. Compared to providing servers, computers containing development applications, using computers or laptops connected to the internet, students can easily implement the AI knowledge they have learned. For group work, applications for Continuous Integration/Continuous Delivery can be utilized, for example with Github, Gitlab, and similar ones.
Analyzing Land Suitability for Housing in Bekasi Regency: Managing Farmland Conversion During Urban Growth Herlawati, Herlawati; Handayanto, Rahmadya Trias
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 12 No. 2 (2024): September 2024
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v12i2.9968

Abstract

Bekasi Regency is a buffer area for Jakarta and is part of the Jakarta Metropolitan Region (JMR). Along with Karawang, this region is a major rice producer, but it is currently experiencing significant land conversion from agriculture to residential and industrial uses. Preventing this conversion is very challenging due to the high population growth in the area. To address this issue, this study aims to conduct a suitability analysis to identify areas that are unsuitable for agricultural land but still suitable for residential purposes. The factors considered in the suitability analysis include slope, distance to roads, distance to residential areas, distance to facilities and infrastructure, and distance to rivers and irrigation systems. The results of the study identify areas that are unsuitable for agriculture, allowing local governments to focus on these areas as potential sites for new residential developments. The location is situated in the southern part of Bekasi Regency, specifically in the Cikarang area and its surroundings.
Metode Naïve Bayes dan Support Vector Machine untuk Mengolah Sentimen Ulasan dan Komentar di Platform Digital Herlawati; Srisulistiowati, Dwi Budi; Agustin, Syafira Cessa; Syafina, Prilia Hashifah; Rachmatin, Nida; Setiawati, Siti
Journal of Students‘ Research in Computer Science Vol. 5 No. 2 (2024): November 2024
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/dby15h32

Abstract

This study analyzes sentiment from user Reviews of the FLO app, Taman Mini Indonesia Indah (TMII), and public comments on infidelity cases on Instagram, using Naïve Bayes and Support Vector Machine (SVM) algorithms. FLO, an app that helps users track reproductive health, was analyzed based on 1,393 Reviews on Google Play Store. Of these, 796 Reviews expressed positive sentiment, while 597 were negative. Although both Naïve Bayes and SVM achieved an accuracy of 74%, SVM performed better in recall (74%) and precision (71%). For TMII Reviews, the analysis involved 1,616 Google Reviews, with 1,263 showing negative sentiment, indicating complaints about facilities and services, and 353 expressing positive sentiment. SVM outperformed Naïve Bayes, achieving an accuracy of 85% and an f1-score of 87%, compared to Naïve Bayes’ 82% accuracy and 83% f1-score. Additionally, the analysis of 1,200 public comments on Instagram accounts @lambe_turah and @awreceh.id revealed 918 negative comments and 282 positive ones. SVM once again demonstrated superior performance with an accuracy of 91%, precision of 87%, recall of 96%, and an f1-score of 92%, surpassing Naïve Bayes, which achieved an accuracy of 86%. These findings confirm that SVM is more effective for sentiment classification across various digital Platforms, including social issues and service evaluations. The results can be applied to develop public opinion analysis systems that support strategic decision-making and enhance service quality based on user feedback.
Fine-Tuning Large Language Model (LLM) for Chatbot with Additional Data Sources Herlawati, Herlawati; Handayanto, Rahmadya Trias
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 13 No. 1 (2025): Maret 2025
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v13i1.10832

Abstract

Currently, Large Language Models (LLMs) are gaining popularity in implementation and research, with numerous open-source models available for use. One notable example is the AI-powered chat application, which leverages pre-trained LLMs to provide accurate and relevant information to users. By utilizing fine-tuning technology, this model can be tailored to specific student registration data, making it easier for prospective students to access the necessary information. Research findings indicate that this model achieves high accuracy in providing answers based on the inputted information. One of its advantages is its ability to generate training data through a Llama-based chat application, resulting in a more interactive and engaging user experience.
Analisis Pengaruh Video Advertising Pada Platfrom Instagram Terhadap Minat Beli Busana Muslim Melalui Brand Awareness Sebagai Variabel Intervening Herlawati, Herlawati; Fahrika, Andi Ika; Shadriyah , Shadriyah
IKRAITH-EKONOMIKA Vol. 8 No. 1 (2025): IKRAITH-EKONOMIKA Vol 8 No 1 Maret 2025
Publisher : Universitas Persada Indonesia YAI

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Abstract

Penelitian ini bertujuan untuk menganalisis pengaruh video advertising pada platform Instagram terhadap minat beli busana muslim, dengan brand awareness sebagai variabel intervening. Pendekatan yang digunakan dalam penelitian ini adalah pendekatan kuantitatif dengan metode survei, melalui penyebaran kuesioner kepada 100 responden di lingkungan Kampus Institut Agama Islam Negeri (IAIN) Bone. Teknik analisis data yang digunakan adalah Structural Equation Modeling (SEM) dengan bantuan perangkat lunak SmartPLS 4. Analisis ini bertujuan untuk menguji hubungan antara variabel independen, yaitu video advertising, terhadap variabel dependen, yaitu minat beli, serta melihat peran brand awareness sebagai variabel mediasi dalam hubungan tersebut. Pendekatan ini memungkinkan pemahaman yang lebih komprehensif mengenai pengaruh tidak langsung video advertising terhadap minat beli busana muslim. Hasil penelitian menunjukkan bahwa (1) Video advertising berpengaruh langsung dan signifikan terhadap brand awareness. (2)Video advertising tidak berpengaruh langsung secara signifikan terhadap minat beli. (3) Brand awareness berpengaruh langsung dan signifikan terhadap minat beli. (4) Video advertising berpengaruh secara tidak langsung terhadap minat beli busana muslim melalui brand awareness, dan pengaruh tersebut terbukti signifikan. Nilai R-square untuk variabel brand awareness sebesar 0,602 dan untuk variabel minat beli sebesar 0,821, yang menunjukkan bahwa model memiliki kemampuan prediktif yang baik.
Co-Authors A.A. Ketut Agung Cahyawan W Abd Rohman Abdul Kholis Achmad Wira Wiguna Adam Adam Adam Fajariansyah Adi Muhajirin Adi Supriyatna admin admin Aera Santiana Agus Hidayat Agustin, Syafira Cessa Ajie Prasetya Ajif Yunizar Pratama Yusuf AlHakim, Abdu Malik Andy Achmad Hendharsetiawan Anggaini, Meri Anisa Feby Yana Anita Setyowati Srie Gunarti Anita Setyowati Srie Gunarti Anita Setyowati Srie Gunarti Anita Setyowati Srie Gunarti Anton Anton Ardiansyah, Muhamad Arrasyid, Rizky Maulana Asmoro Bangun Priambodo Atika , Prima Dina Ayu Afidarisa Rahma Bangga Tua Siregar Bayu Andriansyah Ben Rahman Beno Aditya Sanusi Beno Aditya Sanusi Benrahman Bhagaskara Farhan Wiguna Binu Nuryadi Budi Santoso Bunga Pratiwi Cahyaaty, Tata Arya Christhover , Robbie Dadan Irwan Dani Dani Daniel Jhon Rosinton Hutauruk Desi Puspasari Diah Putri Ramadhani Dicki Rizki Amarullah Didik Setiyadi Dinda Mutiara Hanum Dwi Budi Santoso Dwi Budi Srisulistiowati Eka Puspita Sari Eka Suryani Pratiwi Ekawati, Inna Endang Retnoningsih Erene Gernaria Sihombing, Erene Gernaria Ervan Dwi Kurniawan Fachrullyanta Adi Saputra Fadilah, Naufal Arif Fahrika, Andi Ika Faisal Adi Saputra Fandiansyah, Rafly Fata Nidaul Khasanah Feni Meilan Tasiba Firyal Rosiana Dita Frieyadie Galih Apriansha Pradana Gedhe Hilman Wakhid Gilby Lionska Wenas Gymnastiar, Muhammad Handry Hartino Haris, Syamsul Alam Harviansyah, Muhammad Haryono Haryono Haryono Hendharsetiawan , Andy Achmad Hendharsetiawan, Andy Achmad Heri Prabowo Hero Suhartono Hero Suhartono, Hero Hutauruk , Daniel Jhon Rosinton Icah Fitri Yani Idaul Hasanah Ikhsan Dwikurniawan Ikhsan Dwikurniawan Ira Wardani Irham Cahya Nugraha Irwan Raharja Ivan Nur Firdaus Izdihar, Zalfa Jaja Jaja JAJA, JAJA Joko Dwi Hartanto Juandika Shevani Julaiwa, Siti Hawa Karnita Afnisari, Karnita Krisendo Setiawan Kukuh Dwi Prasetyo Kurniawan, Ervan Dwi Kustanto , Prio Ladyana Suciani Syafitri Lestari, Tyastuti Sri Lubis, Riski Aditya Magdalena, Caroline Julyana Maimunah Maimunah Maimunah Maimunah Maimunah Maimunah, Maimunah Malikus Sumadyo Mardi Yudhi Putra Mayora Lolly Ishimora Merza Dheo Prakoso Muhamad Ardiansyah Muhammad Harviansyah Muhammad Muharrom Muhammad Riky Sudrajat Muhammad Zidan Al Faiq Nabila , Marsyanda Salsa Ningrum, Mirza Cahya Nita Merlina Nita Merlina, Nita Nitin Kumar Tripathi Noer Hikmah Novaldi Nur Pratama Novianto, Krisna Nunung Hidayatun Nur Amanda Pratiwi Nurchayati Nurchayati Nurcholis Nurcholis Oriza Sativa Dinauni Silaen Pahrizal, Pahrizal Popy Purnamasari Wahid Suyitno Pradana , Galih Apriansha Pramuhesti, Salwa Nabiila Priatna , Wowon Prihatin, Sandy Satyo Prima Dina Atika Purnama, Putra Aldi Purnomo, Rakhmat Purwanti, Santi Rachmatin, Nida Rafika Sari RAFIKA SARI Rahmadya Trias Handayanto Raihan Nurfaidzi Ramadhan, Sahara Ramadhani, Diah Putri Rasim Rasim Rasim, Rasim Rejeki , Sri Retno Nugroho Whidhiasih Retno Sari Riska Utami Dewi Rismayana, Raka Rizki Aulianita, Rizki Robbie Christhover Robertus Suraji Rosliana, Siti Rusdiansyah Rusdiansyah Salwa Nabiila Pramuhesti Samsiana , Seta Sandy Satyo Prihatin Santoso , Muhammad Reinaldy Sanusi, Beno Aditya Saputra , Faisal Adi Saputra, Fachrullyanta Adi Sari , Rafika SATRIYAS ILYAS Septi Eka Hardyana Septia, Dwi Yoga Seta Samsiana Seta Samsiana Seta Samsiana Seta Samsiana Seta Samsiana Setiawan, Andy Achmad Hendhar Setyowati Srie Gunarti, Anita Shadriyah , Shadriyah Silaen, Oriza Sativa Dinauni Siti Masripah, Siti Siti Rosliana SITI SETIAWATI Sohee Minsun Kim Solikin Solikin Solikin Solikin Sri Rejeki Sri Sureni Sugeng Murdowo Sugiyatno , Sugiyatno Sugiyatno Sugiyatno Sugiyatno Sugiyatno Sunandar Sunandar Syadhaffa Gedriyansah Syafina, Prilia Hashifah Syahbaniar Rofiah Syahfitri, Intan Cahya Tambun, Jerisman Jhon Wesli Tia Monisya Afriyanti Trisumeikra, I Komang Arya Tumbur Togu Tyastuti Sri Lestari Tyastuti Sri Lestari Umi Salamah Wicaksono, Naufal Eka Wida Prima Mustika Wiguna, Bhagaskara Farhan Wijaya, Indra Yana, Anisa Feby Yessi Rahmawati Yugo Bhekti Utomo Yusuf, Ajif Yunizar Pratama