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All Journal Jurnal Teknologi dan Manajemen Informatika JPAP (Jurnal Penelitian Administrasi Publik) (e-Journal) Sistemasi: Jurnal Sistem Informasi Indonesian Journal of Artificial Intelligence and Data Mining Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Teknologi Sistem Informasi dan Aplikasi EDUMATIC: Jurnal Pendidikan Informatika SPIRIT JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Knowbase : International Journal of Knowledge in Database
Efendi, Kacung
JPAP: Jurnal Penelitian Administrasi Publik
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering

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PELAYANAN SERTIPIKAT HAK ATAS TANAH DI KANTOR PERTANAHAN KABUPATEN TUBAN (STUDI PENINGKATAN KINERJA PELAYANAN SERTIPIKAT HAK ATAS TANAH MELALAUI PROYEK OPERASI NASIONAL AGRARIA (PRONA) DI KANTOR PERTANAHANKABUPATEN TUBAN) Efendi, Kacung
JPAP: Jurnal Penelitian Administrasi Publik Vol 1 No 02 (2015)
Publisher : Universitas 17 Agustus 1945 Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30996/jpap.v1i02.692

Abstract

Prona is an activity organized by the government in the land sector in general and in thefield of land registration in particular, in the form of land pensertipikatan implementedsimultaneously together (bulk) and the settlement of land disputes that are strategic. Thepurpose of this study is to analyze the performance of the service certificate of landrights through the Land Office Prona in Tuban, as well as to analyze the factors that ledto the performance of the service certificate of land rights through the Land OfficeProna in Tuban. The survey results revealed that the implementation of theImplementation of Public Services On Certificate of Land Through the Land OfficeProna in Tuban has appropriate technical guidelines (Juknis) BPN. The ten principles ofservice stipulated in a decree of the Minister of State Apparatus No. 63 / KEP / M.PAN/ 7/2003 on General Guidelines for the Implementation of Public Service. Not optimalperformance of the public service of the Land Office Prona in Tuban due to lack ofhuman resources, lack of support equipment, as well as the lack of socialization to thecommunity about Prona. In implementing the program Prona Tuban District LandOffice are the problems / obstacles both from the physical aspect, the community, staff,and the financial aspect.Keywords: Services, Prona, Rights to Land, Tuban
Association Rule Mining To Enhance Sata Bottle Sales slamet, slamet kacung; Rohmah, Farah Aqmarinar; Edi Prihartono
Knowbase : International Journal of Knowledge in Database Vol. 4 No. 1 (2024): June 2024
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v4i1.8555

Abstract

Sales of sata bottles are growing and increasing, However, the results of these sales transactions have not been maximally utilized by shop owners. In fact, by using data mining techniques, the collection of data can generate new information. Association rule mining can find interaction patterns between one or more items in a very large data set. This algorithm is widely used in transaction data for purchasing product items at the same time by customers. research objectives to improve sales strategy, by collecting sales patterns that help related parties make sales strategy decisions, recommend products to customers, and maintain product availability. The research method using apriori algorithm data mining system that aims to determine consumer purchasing patterns.  The association rule obtained results in 1 product that is often purchased simultaneously, namely Buy Rabbit Bottle, 420ml Clear Bottle, Buy Rabbit Bottle, Glass Straw, and Buy Rabbit Bottle, Nice Glass with a support value of 10% and a confidence of 80% in three frequent itemset and Rabbit Bottle, 420ml Clear Bottle, Rabbit Bottle, Glass Straw, and Nice Glass, 420ml Clear Bottle with a support value of 15% and a confidence of 83% in two frequent itemset.
Sentiment Analysis on Ajaib App Using the SVM Method Minggow, Lingua Franca Septha; Vitianingsih, Anik Vega; Kacung, Slamet; Maukar, Anastasia Lidya; Rusdi, Jack Febrian
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 14 No. 4 (2025): NOVEMBER
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v14i4.2402

Abstract

The rapid growth of investment applications has transformed trading accessibility, yet user dissatisfaction persists, particularly regarding transaction delays, technical issues, and inadequate customer support. This study addresses a research gap in sentiment analysis, specifically in the context of the Ajaib investment application, by employing a Support Vector Machine (SVM) model combined with lexicon-based labelling. The objective is to classify user-generated Google Play reviews into positive, negative, and neutral sentiments, providing actionable insights for service improvement. The research follows a structured methodology comprising data crawling, text pre-processing (cleaning, case folding, tokenization, stopword removal, and stemming), TF-IDF feature extraction, and supervised classification with SVM. Model validation utilises a 3×3 confusion matrix to calculate accuracy, precision, and recall, thereby ensuring a robust performance evaluation. Experimental results demonstrate that the SVM classifier achieves high accuracy in sentiment polarity classification, highlighting its suitability for text-based sentiment analysis in the financial domain. The distinct contribution of this research is its implementation of SVM for sentiment classification for Ajaib, offering a replicable framework for leveraging user feedback to enhance digital investment platforms. These findings contribute to the development of automated sentiment analysis systems that support data-driven decision-making for improving customer satisfaction.
Comparative Analysis of Support Vector Regression and Linear Regression Models to Predict Apple Inc. Share Prices Pangestu, Resza Adistya; Vitianingsih, Anik Vega; Kacung, Slamet; Maukar, Anastasia Lidya; Noertjahyana, Agustinus
Indonesian Journal of Artificial Intelligence and Data Mining Vol 7, No 1 (2024): March 2024
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v7i1.28594

Abstract

Stock price prediction is a complex and important challenge for stock market participants. The difficulty of predicting stock prices is a major problem that requires an approach method in obtaining stock price predictions. This research proposes using machine learning with the Support Vector Regression (SVR) model and linear regression for stock price prediction—the dataset used in the daily Apple Inc historical data from 2018 to 2023. The hyperparameter tuning technique uses the Grid Search method with a value of k = 5, which will be tested on the SVR and Linear Regression methods to get the best prediction model based on the number of cost, epsilon, kernel, and intercept fit parameters. The test results show that the linear regression model with all hyperparameters k = 5 with the average taken performs best with a True intercept fit value. The resulting model can get an excellent error value, namely the RMSE value of 0.931231 and MSE of 0.879372. This finding confirms that the linear regression model in this configuration is a good choice for predicting stock prices.
Deteksi Notifikasi Suspend pada Aplikasi Ojek Online Menggunakan Metode MOORA Wijiono, Aditya Kusuma; Vitianingsih, Anik Vega; Kacung, Slamet; Maukar, Anastasia Lidya; Pamudi, Pamudi
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 7 No. 3 (2024): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v7i3.42159

Abstract

Online motorcycle taxi drivers often face the risk of account suspension due to violations of rules that are not always clear or understood by them. This ignorance can cause drivers to be unaware of actions that can lead to suspension, which can impact their income and reputation. To overcome this problem, this study proposes the use of the Multi-Objective Optimization based on Ratio Analysis (MOORA) method in detecting and providing early notification regarding potential suspension. The MOORA method is used to analyze various parameters related to violations, such as the frequency and type of violations, as well as the number of accumulated violation points. By processing this data, the developed system can predict the possibility of suspension and provide notification to the driver. The results of the application of the MOORA method show that this system is effective in providing accurate notifications and can help drivers avoid actions that have the potential to cause suspension. The application of this system has the potential to reduce the number of suspension cases and increase driver awareness of actions that must be avoided.
MODEL SYSTEM USABILITY SCALE UNTUK EVALUASI KEPUASAN LAYANAN PROGRAM STUDI kacung, slamet; Umam, Khoirul; Sumirat, Lambang Probo
SPIRIT Vol 16, No 1 (2024): SPIRIT
Publisher : LPPM ITB Yadika Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53567/spirit.v16i1.326

Abstract

Model Sus Untuk Evaluasi Kepuasan Layanan Program Studi di Perguruan Tinggi (PT). Penelitian ini bertujuan untuk memberikan kemudahan kepada mahasiswa, tenaga pendidik, dan tenaga kependidikan, serta mitra kerjasama dalam memberikan penilaian kepuasan kepada program studi karena dalam pengisian kusioner dapat melalui sistem yang dapat diakses kapan saja dan dimana saja selama terhubung dengan internet. Jenis penelitian ini menggunakan penelitian kualitatif dengan menggunakan metode System Usability Scale (SUS), penelitian ini digunakan untuk mengukur tingkat kepuasan pengguna sistem informasi menurut sudut pandang subyektif penggunannya. Hasil penelitian menemukan bahwa sistem kepuasan adalah sistem informasi yang digunakan untuk membantu kerja program studi dalam mengetahui kepuasan terhadap layanan yang dierikan. Ditinjau dari penggunanya sistem kepuasan ini belum dilakukan pengukuran kepuasan dari pengguna. hasil analisis sistem menggunakan metode System Usability Scale (SUS) dengan jumlah sampel 13 responden diperoleh nilai rata-rata 85. dengan kriteria penilaian pada Adjective rating adalah Good, dengan Grade Scale nilai A-. Adapun Acceptability Ranges dengan nilai Acceptable, yang artinya sistem tersebut dapat diterima dan digunakan oleh seluruh pengguna. Kata kunci: Sistem Informasi, Kepuasan Layanan, Metode System Usually Scale (SUS)
Sentiment Analysis on Indonesian National Football Team Naturalization using KNN and SVM Adharani, Salza Kartika; Kacung, Slamet; Vitianingsih, Anik Vega
Jurnal Pendidikan Informatika (EDUMATIC) Vol 9 No 1 (2025): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v9i1.29653

Abstract

The naturalization of football players in Indonesia is largely viewed positively, with supporters highlighting its benefits for team performance, international competitiveness, and player development. While PSSI endorses naturalization to strengthen the national team, Liga Indonesia Baru (PT LIB) imposes limits to maintain fairness. The purpose of this research is to examine public sentiment toward the naturalization of Indonesian football players by analysing discussions on X and YouTube. This research analyses public sentiment toward the naturalization of Indonesian football players using a data and text mining approach based on 3,267 comments from X and YouTube between 2022 and 2024. The research process includes data collection, preprocessing, TFIDF, data labeling, and model training and evaluation. Two machine learning models, KNN and SVM, are implemented for classification, with SVM outperforming KNN in accuracy. Our results show that KNN achieved 76.71% accuracy (precision: 52%, recall: 56%, F1-score: 53%), while SVM RBF outperformed with 86.51% accuracy (precision: 59%, recall: 42%, F1-score: 26%). SMOTE and GridSearch effectively address the class imbalance and optimize model performance. Public sentiment is predominantly positive, highlighting enhanced team performance and global recognition. These insights assist PSSI and policymakers in making informed decisions regarding fairness, discrimination, and the governance of Indonesian football.
Sentiment Analysis of Cyberbullying Detection on Social Networks using the Sentistrenght Method Yunior, Kevin Heryadi; Vitianingsih, Anik Vega; Kacung, Slamet; Lidya Maukar, Anastasia; Dwi Arumsari, Andini
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.4226

Abstract

In today's swiftly changing digital realm, social media has emerged as a pervasive means of communication, yet it has also fostered the rise of cyberbullying, especially among young demographics. This research strives to develop an application that assesses public sentiment on Instagram regarding cyberbullying instances, categorizing sentiments as positive, negative, or neutral. Drawing data from Instagram accounts such as kumparandotcom, merdekadotcom, and okezonedotcom, the approach combines lexicon-based text labeling and sentiment analysis employing Sentistrength. Findings demonstrate the method's effectiveness, achieving accuracy, precision, and recall rates exceeding 85% while offering precise visualization of predictions. This study contributes to combatting cyberbullying, aiming to improve victims' mental well-being by providing clearer insights into social sentiment. The dataset comprises 4500 comments collected through web crawling, categorized into positive (735 entries), negative (2478 entries), and neutral (1288 entries) sentiments. The evaluation highlights the commendable performance of Sentistrength, achieving the highest accuracy at 93.85%.
Sistem Pendukung Keputusan Seleksi Pemilihan Pemain Tim Futsal Menggunakan Metode ROC dan ARAS Yusuf, Adrian Edoardo; Santoso, Budi; Kacung, Slamet
Journal of Information System Research (JOSH) Vol 5 No 4 (2024): Juli 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i4.5457

Abstract

Futsal's popularity remains undiminished, captivating communities, including school environments like SMK Unitomo Surabaya. In this school, building a strong futsal team is the cornerstone of achieving success. However, manual player selection processes often encounter obstacles, such as inefficiency and potential subjectivity. Often, coaches do not record selection results, leading them to evaluate selections subjectively.Therefore, this research presents a solution in the form of a Decision Support System (DSS) to assist coaches in identifying potential core futsal players. This DSS integrates two cutting-edge methods: Rank Order Centroid (ROC) and Additive Ratio Assessment (ARAS). The ROC method plays a role in data weighting, assigning measurable values to each selection criterion. On the other hand, ARAS plays a role in determining the best alternative by comparing the overall value of each alternative with the optimal value of the entire series. Research results demonstrate that this DSS can generate rankings of potential core futsal players with an accuracy level of 0.8753324. This indicates that this DSS has great potential to assist coaches in selecting the right players and increasing the team's chances of winning.
PERANCANGAN SISTEM INFORMASI ANALIS BREAK EVEN POINT DAN STOK PADA BUDIDAYA AYAM POTONG BERBASIS WEB Yudi Kristyawan; Slamet Kacung; Afif, Khoiril
Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Vol 12 No 2 (2024): TEKNOIF OKTOBER 2024
Publisher : ITP Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21063/jtif.2024.V12.2.111-119

Abstract

Although broiler chicken farming offers many benefits, there are also risks of losses, especially when production costs are not accurately recorded, leading to inaccurate per-unit pricing that can harm farmers. To assist farmers in accurately determining the Break Even Point (BEP) price for each chicken, a web-based cost and stock management information system for broiler farming has been developed. To provide a clear and sequential software lifecycle approach, this system was built using the waterfall method, which includes the stages of requirements analysis, design specifications, coding, testing, and maintenance. Each stage produces measurable outcomes before proceeding to the next. The development results indicate that the system successfully records the total production costs, including detailed costs for feed, medicine, operational expenses, and chicken stock. By using the formula BEP = total production cost/number of live chickens, the system achieves accurate pricing for broiler chickens. Based on these findings, future research is suggested to improve the user interface for greater appeal, optimize system accessibility on mobile devices, and integrate this system with other systems.
Co-Authors Adharani, Salza Kartika Afif, Khoiril Agustinus Noertjahyana Anastasia Lidya Maukar Anik Vega Vitianingsih Arumsari, Andini Dwi Budi Santoso Edi Prihartono Fauzi, Chamdan Fitri Ana Wati, Seftin Kesuma Wardanie, Debleng Puja Khoirul Umam Lambang Probo Sumirat, Lambang Probo Lidya Maukar, Anastasia Minggow, Lingua Franca Septha Nabil, Muh Pamudi Pamudi, Pamudi Pangestu, Resza Adistya Rohmah, Farah Aqmarinar Rusdi, Jack Febrian Sutejo, Davip Wijiono, Aditya Kusuma Yudha Adhi Jaya, Villa Indra Yudi Kristyawan Yunior, Kevin Heryadi Yusuf, Adrian Edoardo