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All Journal Dinamik Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Pendidikan Teknologi dan Kejuruan Bulletin of Electrical Engineering and Informatics Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) PROCEEDING IC-ITECHS 2014 SMATIKA E-Dimas: Jurnal Pengabdian kepada Masyarakat Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal CoreIT Indonesian Journal of Artificial Intelligence and Data Mining JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Teknoinfo Technomedia Journal KOMPUTIKA - Jurnal Sistem Komputer Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Jurnal Tekno Kompak Building of Informatics, Technology and Science Indonesian Journal of Electrical Engineering and Computer Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Teknik Informatika (JUTIF) JTIKOM: Jurnal Teknik dan Sistem Komputer Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Ilmiah Infrastruktur Teknologi Informasi Jurnal Teknologi dan Sistem Informasi Journal Social Science And Technology For Community Service Jurnal Teknologi Pendidikan : Jurnal Penelitian dan Pengembangan Pembelajaran Bulletin of Computer Science Research Journal of Informatics Management and Information Technology KLIK: Kajian Ilmiah Informatika dan Komputer AKM: Aksi Kepada Masyarakat Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat) Jurnal Ilmiah Sistem Informasi Akuntansi (JIMASIA) Journal of Engineering and Information Technology for Community Service Jurnal Ilmiah Edutic : Pendidikan dan Informatika Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Pengabdian Masyarakat Bangsa Bulletin of Informatics and Data Science Jurnal Ilmiah Computer Science Journal of Information Technology, Software Engineering and Computer Science Management of Information System Journal JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Smatika Jurnal : STIKI Informatika Jurnal Dharma Nusantara: Jurnal Ilmiah Pemberdayaan dan Pengabdian kepada Masyarakat
Heni Sulistiani
Universitas Teknokrat Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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Evaluation of Salesperson Performance in the Sales Allowance Decision Support System Using the MARCOS and PIPRECIA Methods Hadad, Sitna Hajar; R Metha, Abhishek; Setiawansyah, Setiawansyah; Sulistiani, Heni
Journal of Computer System and Informatics (JoSYC) Vol 5 No 2 (2024): February 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i2.4863

Abstract

Optimal salesperson performance is the main key to a company's success in achieving sales targets and business growth. A reliable salesperson is not only able to sell products or services, but also has the ability to build strong relationships with customers. The purpose of this study is to assess the performance of salesperson in providing sales allowances based on performance results carried out by applying a combination of MARCOS and PIPRECIA methods, so as to produce a recommendation for the final assessment of salesperson performance that will assist the company in providing sales benefits to salespersons. The combination of Pairwise Relative Criteria Importance Assessment (PIPRECIA) and Measurement of Alternatives and Ranking According to Compromise Solution (MARCOS) forms a powerful holistic approach to decision making. PRCIA facilitates the identification and assessment of the relative weights of each decision criterion, providing a solid foundation for assigning value to the relative importance between criteria. The results of the salesperson performance evaluation ranking above show the final results for rank 1 with a value of 4.3446 obtained by Rini, rank 2 with a value of 3.5369 obtained by Murniasih, rank 3 with a value of 3.1807 obtained by Hana Ferbi.
SENTIMENT ANALYSIS OF PUBLIC OPINION ON THE RIGHT OF INQUIRY IN INDONESIA IN 2024 USING THE SUPPORT VECTOR MACHINE (SVM) METHOD Sebastian, Dicky Fernanda; Sulistiani, Heni; Isnain, Auliya Rahman
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.1968

Abstract

Research on the right of inquiry refers to public responses on twitter social media related to the 2024 elections. The right of inquiry is a right used in investigations. There are a lot of public opinions about the right of inquiry that are discussed on twitter social media that convey their various opinions or criticisms of government policies towards the 2024 elections. Based on Law No. 17/2014, the right of inquiry of the House of Representatives is regulated in Article 20A of the 1945 Constitution, which regulates the right of inquiry of the House of Representatives. Sentiment analysis is used in this research to determine the accuracy value of public opinion which is categorized into two, namely positive and negative sentiment. In this study, the SVM method is used to identify and find the results of public opinions or responses regarding the issue of the right of inquiry in Indonesia in 2024 which is being widely under the twitter social media platform, so it is necessary to analyze the sentiment. By using the support vector machine (SVM) algorithm and word weighting using TF-IDF (term frequency-inverse document frequency). Data collection using Google Collaboratory tools with the python programming language. The data used were 2,179 tweets with the keywords "inquiry right", "DPR inquiry right", "election inquiry right". The results obtained from the SVM process with an accuracy value of 77%, negative precision value 77%, positive precision value 77%, negative recall value 57%, positive recall value 89%, positive f1-score value 66%, negative f1-score value 82%. The data that has been tested and processed has an adequate accuracy value for SVM algorithm classification using confusion matrix calculation. The results of the research conducted have been effective with the SVM method.
Implementasi Sensor GY-302 BH1750 untuk Penyesuaian Intensitas Cahaya pada Tanaman Selada dan Sawi Hidroponik: Implementation of the GY-302 BH1750 Sensor for Adjusting Light Intensity in Hydroponic Lettuce and Mustard Plants syahril, Muhammad; Sulistiani, Heni
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 5 No. 4 (2025): MALCOM October 2025
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v5i4.2281

Abstract

Penelitian ini mengimplementasikan sistem pengendalian intensitas cahaya otomatis untuk tanaman hidroponik selada dan sawi menggunakan sensor GY-302 BH1750, mikrokontroler ESP32, dan driver BTS7960. Sistem dirancang untuk secara otomatis mengatur intensitas cahaya sesuai kebutuhan spesifik masing-masing tanaman melalui mekanisme kontrol PWM. Pengujian dilakukan selama 8 jam dengan interval pencatatan per jam untuk dua mode tanaman berbeda. Hasil menunjukkan sistem berhasil mempertahankan intensitas cahaya pada rentang di bawah 3000 lux untuk tanaman sawi dan 4850-7890 lux untuk tanaman selada dengan akurasi tinggi dan stabilitas yang konsisten. Sistem ini terbukti mampu meningkatkan efisiensi energi hingga 40% dibandingkan sistem pencahayaan konvensional melalui penyesuaian intensitas yang presisi. Implementasi push button sebagai selector mode tanaman bekerja optimal dengan respon transisi yang cepat tanpa gangguan operasional. Temuan penelitian mengindikasikan bahwa sistem ini dapat menjadi solusi efektif untuk optimasi pertumbuhan tanaman hidroponik dengan konsumsi energi yang minimal
Penerapan Metode Pembobotan LOPCOW dan Grey Relational Analysis Dalam Penentuan Pemasok Toserba Terbaik Izka, Ade Adyatna; Sulistiani, Heni
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.v5i4.5537

Abstract

Selecting the best supplier is a crucial aspect in the supply chain that has a significant impact on operational efficiency and final product quality. The main problem in this study is that there is no model in the selection of the best supplier that is carried out, but the company always assesses the performance of suppliers to see the performance of suppliers periodically and ensure that the agreed standards are still met and re-evaluate if necessary. This study combines the advantages of LOPCOW in objectively weighting criteria based on logarithmic percentage changes in data, with the strength of GRA in handling data complexity and uncertainty in multi-criteria evaluation. This combination improves the accuracy and reliability of decisions taken, as it combines the advantages of objectivity in weighting with strong analytical capabilities in alternative evaluations. The result is a more holistic, objective, and data-driven decision-making process, which is especially beneficial in complex and uncertain situations. The results of the ranking of the best convenience store suppliers show that Supplier AB is the first best with a value of 0.1722, Supplier JB is the second best with a value of 0.12, and MA Supplier is the third best with a value of 0.0848. The results of this study are recommendations for convenience stores in assessing the performance of existing suppliers.
Analisis Sentimen Publik terhadap ‘Save Raja Ampat’ di Media Sosial Menggunakan Model IndoBERT Eko Putro, Dimas; Juarsa, Doris; Putra Hermana, BP; Bagastian, Bagastian; Sulistiani, Heni
Bulletin of Computer Science Research Vol. 5 No. 5 (2025): August 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i5.621

Abstract

The "Save Raja Ampat" campaign has emerged as a significant environmental issue that has garnered widespread public attention on social media platforms, particularly TikTok and YouTube. Videos tagged with #SaveRajaAmpat have sparked various public responses, ranging from full support to criticism of natural resource exploitation. This phenomenon highlights the importance of understanding public sentiment as an indicator of the campaign's effectiveness. This study aims to analyze public sentiment toward the campaign using a language modeling approach based on artificial intelligence, namely IndoBERT. The data were obtained from user comments on TikTok videos promoting the “Save Raja Ampat” campaign, totaling 10,000 comments. The analysis process involved several stages, including data preprocessing, sentiment labeling (positive, negative, neutral), and the training and evaluation of the IndoBERT model. Preliminary results indicate that the majority of public sentiment toward the campaign is positive, with the model achieving an accuracy rate of 71% in sentiment classification. This study contributes to understanding public perception of environmental issues and demonstrates the effectiveness of using the IndoBERT model in the context of social media.
Klasifikasi Tingkat Risiko Gempa di Indonesia Menggunakan Pola Spasial dan Temporal Berbasis Decision Tree Prasetio, Mugi; Sulistiani, Heni; Inonu, Onassis Yusuf; Magda, Kardita; Santosa, Budi
Bulletin of Computer Science Research Vol. 5 No. 5 (2025): August 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i5.624

Abstract

Indonesia is an area that is very vulnerable to earthquakes due to its location in the meeting zone of active tectonic plates. This study aims to classify the level of earthquake risk based on spatial and temporal patterns using the Decision Tree method as a solution in predicting potential earthquake hazards. The data used is earthquake data in Indonesia from 2015 to 2023 obtained from public datasets, including location information (latitude and longitude), event time (year and month), and earthquake magnitude. Earthquakes are categorized into three risk classes: Low (M < 4.0), Medium (4.0 ? M < 6.0), and High (M ? 6.0). The Decision Tree model was successfully built with an average accuracy of 88% on the test data. The results show that earthquakes mostly occur in active subduction zones such as the Sunda Subduction Zone (Sumatra and Java), Banda Arc (Nusa Tenggara, Maluku, Seram), Sulawesi, and Papua. Temporal analysis also shows fluctuations in the number of earthquakes by year and season, with increased activity in certain months. The spatial visualization reinforces the finding that the eastern region of Indonesia is more seismically active than the western region. This research proves that machine learning approaches can be used to support earthquake disaster mitigation through historical data-based risk identification.
Segmentasi Produk Fashion Berdasarkan Harga, Ukuran, dan Merek Menggunakan K-Means di Rapidminer Sanjaya, Ival; Nitami Evita Inonu; Muhammad Fahmi Fudholi; Adelia Pratiwi; Heni Sulistiani
Journal of Informatics Management and Information Technology Vol. 5 No. 3 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v5i3.651

Abstract

Tight competition and product diversity are the hallmarks of the fashion industry, especially in terms of price variation, size, and brand. To help the process of making more accurate business decisions, product segmentation is needed to identify the characteristics of each group. This study utilizes the K-Means Clustering algorithm to group fashion products based on these attributes. The implementation is carried out using the RapidMiner platform, starting with the data normalization stage and the transformation of categorical attributes into numeric form. The optimal number of clusters is determined through the elbow method approach, which shows a significant decrease in the average distance between data in the cluster. The clustering results show the formation of product groups with different characteristics, which can be utilized in stock planning and marketing strategies. This study confirms that the K-Means algorithm is effective in analyzing the distribution of fashion products based on the main attributes they have.
Optimizing the best student selection: hybrid K-Means approach and entropy-grey relational analysis Sulistiani, Heni; Setiawansyah, Setiawansyah; Palupiningsih, Pritasari; Ferico Octaviansyah Pasaribu, Ahmad; Andika, Rio; Hamdan Sobirin, Muhammad
Bulletin of Electrical Engineering and Informatics Vol 14, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i2.8715

Abstract

The selection of the best students is an important process in recognizing students' achievements and dedication in various fields. Through careful and fair selection, students who stand out in both academic and non-academic terms can be identified and assigned. The purpose of the research on the use of hybrid entropy-grey relational analysis (GRA) and K-Means clustering in the selection of the best students is to develop a more objective, accurate, and comprehensive assessment system. The silhouette score results show that 2 clusters have a value of 0.5733, so in this study 2 clusters are used with the best cluster at cluster 0. Data from cluster 0 will be used in determining the best students using hybrid entropy-GRA. The results of the best student ranking using the hybrid entropy-GRA method, for the first best student with a final score of 0.25 were obtained by Mareta Amelia. The hybrid approach of K-Means and entropy-GRA offers a powerful tool to improve decision-making in the student selection process. The hybrid approach of K-Means grouping and entropy-GRA presents a powerful solution, improving the decision-making process and ensuring that high-achieving students are accurately recognized and rewarded.
Penerapan Metode Forward Chaining Pada Sistem Pakar Diagnosa Penyakit Ayam Ternak Ahmad Januar Amriyansah; Heni Sulistiani; Riska Amalia
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 14 No 01 (2024): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM UBHINUS MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v14i01.1001

Abstract

One of the most serious problems faced by chicken farmers is chicken disease. Chicken diseases can be diagnosed by identifying the symptoms that appear and also consulting with an expert. However, this method requires a long time and is quite expensive. Therefore, this research aims to implement the forward chaining method in an expert system to help chicken farmers in diagnosing chicken diseases online. This expert system was developed using the PHP programming language and MySQL database. This expert system also provides treatment guidelines that are in accordance with the diagnosed disease. The expert system was tested using 33 symptoms and 10 common chicken diseases. The test results show that this expert system can diagnose chicken diseases with high accuracy and provide diagnosis results directly through a web browser. This expert system can also improve users' understanding of website creation and chicken diseases.
Implementasi Elliptic Curve Digital Signature Algorithm Untuk Smart Gerobak Sorong Dalam Monitoring Pakan Ternak Alvi Suhartanto; Heni Sulistiani; Selamet Samsugi; Reflan Nuari; Izudin Ismail
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 14 No 01 (2024): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM UBHINUS MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v14i01.1231

Abstract

The Internet of Things (IoT) implementation in the livestock sector includes the use of sensors, software and internet-based platforms to monitor, manage and optimize in real-time. This research is intended to solve problems at PT. Indo Prima Beef noted that the use of animal feed is still based on estimates, resulting in the calculation of the selling price of cattle being inaccurate and potentially detrimental. Manual recording which is prone to errors and less efficient causes uncertainty in feed management and costs. Therefore, this research develops an IoT-based tool that is integrated in a wheelbarrow. This tool is capable of reading the results of weighing animal feed and storing the data in real-time in a database connected to web monitoring. Apart from that, the monitoring application can display recap results of cow feed weights, there are also features that support optimal use of the Smart Gerobak Sorong. The method used in this research is applying the Elliptic Curve Digital Signature Algorithm as a safeguard for data communication between IoT and the database. Based on the test results on a cow's feed weight of 10.6 kg, a difference value of 0.11 kg was obtained. This means that the average error value is 0.01%. So, it can be concluded that the loadcell sensor can read mass data for weighing cattle feed with the same load. With this tool, PT. Indo Prima Beef can increase the efficiency of feed use, optimize business income, and provide innovative and effective solutions in overall animal feed management.
Co-Authors Ade Dwi Putra Ade Dwi Putra Adelia Pratiwi Admi Syarif Ady Chandra Agung Pria Laksono Agung Saputra Agus Irawan Agus Irawan Agustina, Intan Ahmad Ari Aldino Ahmad Fawaiq Suwanan Ahmad Januar Amriyansah Aidil Akbar Akbar, Muhammad Fadil Alfarizi, Ferdian Alfikri, Valbian Alita, Debby Alvi Suhartanto Alvi Suhartanto Alvi Suhartanto Alvinan Virgilia Andi Nurkholis Andika, Rio Andre, Muhammad Fabio Ani Sesanti Antoni, Kevin Rizki Anwar, Adi Khairul Anwar, Rian Aprian Nuriansah Ari Sulistiyawati Arief Aryudi Syidik Arif Munandar Arshad, Muhammad Waqas Arsi Hajizah Auliya R. Isnain Bagastian, Bagastian Bagus Miftaq Hurohman Bambang Dwi Setyarto Benhouzer N.P Pasaribu Budi Santosa Budi Santosa Chanafy, Muhammad Cici Dian Paramita Damayanti Damayanti Damayanti Damayanti Damayanti, Damayanti Darwanto, Imam Dedi Darwis Dedi Darwis Dewantoro, Fajar Dimas, Novario Donaya Pasha Donaya Pasha Eka Lisna Rahmadani Eko Bagus Fahrizqi Eko Putro, Dimas Elin Gusbriana Elvano Delisa Mega Erliyan Redy Susanto Esy Ervina Yanti Evi Dwi Wahyuni Fahreza Aditya Aryatama Falssava, Jossa Neka Fatmawati Isnaini Fatriana, Nina Ferico Octaviansyah Pasaribu, Ahmad Fikri Hamidy Gaib Wiwaha, Gigant Geri Marizki Greessheilla Phylosta P.B Gunawan, Rakhmat Dedi Hamdan Sobirin, Muhammad Hati, Clifansi Remi Siwi hendri eka pratama Hendrik Saputra Heru Setiawan I Gede Heri Susanto Ikbal Yasin Ikbal Yasin Ilham Muhammad Ghoffar Imam Ahmad Imam Ahmad Inonu, Onassis Yusuf Ismail, Izudin Ismail, Izzudin Isnain, Auliya Rahman Istiana, Winda Iwan Purwanto Izka, Ade Adyatna Izudin Ismail Juarsa, Doris Junaidi Junaidi Khairun Nisa Khoirunnisa, Yosi Koswara, Wawan Kurnia Muludi M. Sholahuddin Al-Ayyubi Magda, Kardita Maheswari, Diva Afirlia Masnia Rahayu Maulida Waya Inayah Mauludi, Ilham Moenir Megawaty, Dyah Ayu Mehta, Abhishek Meutia Kartika Arisandi Miswanto Miswanto Muhammad Fahmi Fudholi Muhammad Hamdan Sobirin Muhammad Syahril Muhaqiqin muhaqiqin naufal, wandi Neneng Neneng Nirwana Hendrastuty Nitami Evita Inonu Nosa, Sania Media Nova Evrilia Nunyai, Reiza Fahlevi Oktami, Yuga Palupiningsih, Pritasari Parjito Parjito Pasha, Donaya PENDI, PENDI Pinangkis, Alif Danang Prananta, Gery Prasetio, Mugi Prastowo, Kukuh Adi Pratama, Farhan Rizki Pratama, Miko Septa Priandika, Adhie Thyo Priskilia Lovika Prita Dellia Putra Hermana, BP Putri, Nanda Aulia Qadhli Jafar Adrian Qadli Jafar Adrian R Metha, Abhishek Rahayu, Masnia Rahmadany, Loisha Adellia Ramadhan, Surya Reflan Nuari Rendy Ramadhan Retno Triana Reza Kumala Dewi Rido Febriansyah Rika Mersita Rika Mersita Riska Amalia Rohaniah Rohaniah Rojat, Muhamad Randyka Ryan Randy Suryono S. Samsugi Sandi, Yeris Ari Sangha, Zahra Kharisma Sania Media Nosa Sanjaya, Ival Sari, Priskila Lovika Sebastian, Dicky Fernanda Setiawan, Randi Setiawansyah Setiawansyah Setyani, Tria Shynta Octriana Siska Amelia, Siska Siska Febriani Sitna Hajar Hadad Styawati Styawati Suaidah Suaidah Sufiatul Maryana Sufiatul Maryana Sugianto, Rudi Susanti Susanti Syakuru, Nazwa Tauhid, Naufal Tazul Tazul Antoni Umami, Nila Niswatun Untoro Adji Very Hendra Saputra Very Hendra Saputra Waqas Arshad, Muhammad Warsito Warsito Wawan Koeswara Wayan Kresna Yogi Swara yasin, ikbal Yasinta Ismi Yasinta Ismi HS Yeris Ari Sandi Yosi Khoirunnisa Yulia Indriani Yuliani, Asri Yunita Yunita Yunita Yunita Yuri Rahmanto Yusra Fernando Zaenal Abidin Zahra Kharisma Sangha Zofaisal Hamid, Pratama