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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Media Infotama Jurnal Informatika Jurnal Pseudocode International Journal of Artificial Intelligence Research Jurnal Ilmiah Matrik JOURNAL OF SCIENCE AND SOCIAL RESEARCH JSAI (Journal Scientific and Applied Informatics) Community Development Journal: Jurnal Pengabdian Masyarakat MEANS (Media Informasi Analisa dan Sistem) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) GATOTKACA Journal (Teknik Sipil, Informatika, Mesin dan Arsitektur) Djtechno: Jurnal Teknologi Informasi KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Pengabdian Masyarakat IPTEK Jurnal Multidisiplin Dehasen (MUDE) Jurnal Indonesia Raya Jurnal Media Computer Science Jurnal Dehasen Mengabdi Jurnal Komputer Indonesia VISA: Journal of Vision and Ideas Jurnal Komputer Akademika Journal of Engineering and Technology Innovation Jurnal Komputer, Informasi dan Teknologi
Herlina Latipa Sari
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PERBANDINGAN ALGORITMA K-MEANS DAN K-MEDOID DALAM PENGELOMPOKAN DATA PASIEN BERDASARKAN REKAM MEDIS DI PUSKESMAS M. THAHA BENGKULU SELATAN Adetri Suprianto; Herlina Latipa Sari; Ricky Zulfiandry
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 6, No 3 (2023): October 2023
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v6i3.1445

Abstract

Puskesmas M.Thaha Bengkulu Selatan merupakan salah satu pusat kesehatan masyarakat yang terdapat di Bengkulu Selatan. Selama ini pengelolaan data rekam medis masih dilakukan secara manual dengan mengisi form rekam medis yang telah disediakan dari Puskesmas. Dikarenakan pengelolaan data yang masih manual, membuat pihak puskesmas kesulitan dalam memilih materi yang tepat untuk penyuluhan suatu penyakit ke masyarakat. Selain itu data-data yang ada di Puskesmas tersebut disusun dalam bentuk arsip, sehingga ketika membutuhkan suatu informasi dari data tersebut, dibutuhkan waktu yang cukup lama dikarenakan harus memilah satu persatu arsip yang telah disimpan. Pengelompokan data penduduk lanjut usia pada Metode K-Means dan Metode K-Medoids dibagi menjadi 2 kelompok yaitu Cluster C1 dan Cluster C2. Aplikasi pengelompokan data pasien berdasarkan rekam medis pasien di Puskesmas M. Thaha Bengkulu Selatan dapat digunakan untuk mengetahui penyakit mana yang masuk ke dalam kelompok dengan intensitas tinggi atau rendah berdasarkan rekam medis pasien dan dapat membantu pihak puskesmas dalam memilih materi untuk penyuluhan ke masyarakat khususnya tentang penyakit. Hasil analisis perbandingan antara Metode K-Means dan K-Medoids, diperoleh bahwa perbedaan hasil pengelompokan, iterasi dan waktu proses terjadi tergantung nilai centroid awal yang digunakan pada masing-masing metode. Berdasarkan hasil pengujian yang telah dilakukan, aplikasi pengelompokan data pasien berdasarkan rekam medis pasien di Puskesmas M. Thaha Bengkulu Selatan berhasil dilakukan, dan dapat memberikan informasi berdasarkan 2 kelompok yaitu Cluster C1 dan Cluster C2, serta fungsional dari aplikasi telah berjalan sesuai dengan yang diharapkan.
PENERAPAN METODE K-MEDOIDS DALAM CLUSTERING BARANG BERDASARKAN PENJUALAN BARANG DI TOKO AMANAH PLAFON Sulastari, Ezy; Sari, Herlina Latipa; Alinse, Rizka Tri
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 7, No 4 (2024): November 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v7i4.2183

Abstract

Penelitian ini bertujuan untuk mengelompokkan barang menggunakan metode K-Medoids berdasarkan hasil penjualan pada Toko Amanah Plafon. Pengelompokan barang yang efektif dapat membantu Toko Amanah Plafon dalam mengidentifikasi pola penjualan, mengoptimalkan manajemen stok, serta merencanakan strategi pemasaran yang lebih efektif. Metode K-Medoids digunakan untuk membagi barang-barang yang dijual oleh Toko Amanah Plafon menjadi beberapa kelompok berdasarkan kesamaan karakteristik. Metode K- Medoids menggunakan pusat kluster rata-rata sebagai representasi kluster, sedangkan K-Medoids menggunakan medoid, yaitu sampel data aktual yang mewakili kluster tersebut data penjualan Toko Amanah Plafon digunakan sebagai input dalam penelitian ini. Data ini mencakup informasi tentang barang- barang yang dijual dan jumlah penjualan yang terkait. Melalui analisis clustering, barang-barang tersebut akan dikelompokkan ke dalam kluster berdasarkan kesamaan pola penjualan. Dengan menggunakan metode K-Medoids, diharapkan penelitian ini dapat memberikan kontribusi dalam pengelompokan barang yang lebih efektif dan membantu pihak Toko Amanah Plafon dalam meningkatkan efisiensi operasional serta pengambilan Keputusan yang lebih baik berdasarkan hasil penjualan
Application of the Weighted Product (WP) Method in the Decision Support System for Determining the Best Employee Case Study of Pt Alno Air Ikan Estate Yanto, Reno Hendra; Sari , Herlina Latipa; Sudarsono , Aji
Jurnal Komputer Vol 1 No 1 (2022): Juli-Desember
Publisher : CV. Generasi Insan Rafflesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70963/jk.v1i1.9

Abstract

PT. Alno Air Ikan Estate is a company engaged in the oil palm and rubber plantations located in Mukomuko Regency, Bengkulu Province. PT Alno Air Ikan Estate is still using conventional methods to determine the best employees so it requires a decision support system that can correct weaknesses. One of the Decision Support System methods is Weighted Product (WP). This method is the method used in the simplest ranking of values ​​by using multiplication to relate rating attributes where the rating must first be raised to the weight of the attribute in question. Application Application of the weighted product (WP) method in a decision support system to determine the best employee, can be used to determine the best employee based on criteria, namely attendance value, years of service, attitude, and supporting elements. Based on the research results of the 15 samples used in the application of the weighted product (WP) method in the decision support system for determining the best employee, the best employee is Joko Purwanto with a value of 0.09. This application is made using the Visual Basic Net programming language with SQL server database. The author's suggestion is that this new system should be used as a basis for improving the old system at PT. Alno Air Fish Estate which is still manual.
Application of Fuzzy C-Means Algorithm in Grouping Population Status in Nanjungan Village Ardiansyah, Sohenra; Sari , Herlina Latipa; Sartika , Devi
Jurnal Komputer Vol 1 No 1 (2022): Juli-Desember
Publisher : CV. Generasi Insan Rafflesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70963/jk.v1i1.10

Abstract

Nanjungan Village is one of the villages in Semidang Alas District, Seluma Regency, Bengkulu Province. Every year, the Nanjungan Village Office collects population data within the scope of Nanjungan Alas Village in order to find out the underprivileged population in the village. However, the processing of population data is still done manually by surveying each resident and providing an assessment. The application of the Fuzzy C-Means algorithm in grouping population status in Nanjungan Village can help manage population data and can also help provide recommendations in the form of information on the results of grouping population status data which is divided into 2 groups, namely the less fortunate and the less fortunate. Based on the results of the tests that have been carried out by applying the Fuzzy C-Means Algorithm through observational data in 2021, totaling 618 residents in Nanjungan Village, 5% of the population is taken so that the data is processed as many as 31 residents, the result is that 51.6 % entered into Cluster C1 (Disabled) and 48.4% entered into Cluster C2 (Poor)
Implementation Of Weighted Product Method In Cadre Selection At Sawah Lebar Community Health Center Bengkulu Anggraini, Reren; Sari, Herlina Latipa; Sudarsono, Aji
Jurnal Media Computer Science Vol 4 No 2 (2025): Juli
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v4i2.8459

Abstract

Sawah Lebar Health Center Bengkulu faces challenges in selecting health cadres who have the right qualifications and abilities to support health programs in the community. Selecting the right cadres is an important factor in improving the quality of health services at the basic level. One method that can be used to assist in this selection process is the Weighted Product (WP) method. This method is used to perform objective calculations and assessments based on predetermined criteria, such as education level, work experience, communication skills, and commitment to health programs.The purpose of this study was to implement the Weighted Product method in selecting cadres at Sawah Lebar Health Center Bengkulu and to evaluate the most relevant criteria in selecting the right cadres. In addition, this study aims to test the effectiveness of the system built using the WP method in providing optimal cadre recommendations.The method used in this study is to collect data on cadre candidates, then assess each candidate based on the weight and criteria that have been determined. The results of the system test show that the use of the WP method can produce objective cadre selection, reduce subjectivity in decision making, and increase transparency in the selection process. In the system testing, this system successfully provided results that were in accordance with the expectations and priorities of the Health Center in selecting cadres.In conclusion, the application of the Weighted Product method can improve the accuracy and objectivity in selecting cadres at the Sawah Lebar Bengkulu Health Center. The system that was built has also proven effective in providing recommendations for cadres that are in accordance with the established criteria, so that it can support the success of health programs in the region.
Association Rule Mining System in Analyzing The Use Pattern of Drugs by Using Apriori Herlina Latipa Sari; Ila Yati Beti
International Journal of Artificial Intelligence Research Vol 6, No 2 (2022): Desember 2022
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v6i2.1411

Abstract

Data mining is a process to support decision making in finding information patterns in the data. In this study, Association Rule Mining will be implemented as one of the data mining techniques to analyze data and assist data of scientists in compiling raw data, formulating it and recognizing various patterns through a priori algorithms. The method used in this study is the Cross Industry Standard Process for Data Mining (CRISP-DM) Method by analyzing drug use patterns in health centers. The results of the study shows that by using the apriori algorithm, it found patterns and rules of widely used drugs that will provide recommendations in supporting decision making by health centers to submit drug procurement so that they can improve the quality of health services and minimize the risk of shortages or excess drug supplies and help health centers in optimizing drug inventory management.  The results of the analysis using the apriori algorithm on the combination pattern of 2 itemsets produced 2 association rules for drug use, they are "If using Amoxicillin caplets 500 mg, then you will use paracetamol" with a confidence value of 80% and "If using Dexamethasone tablets 0.5 mg, then you will use Ascorbic Acid (Vit C) tablets 50 mg" with a confidence value of 100%.
Analisis dan Penerapan Algoritma Naïve Bayes untuk Klasifikasi Penyakit Gingivitis Fadhillah, Muhammad; Sari, Herlina Latipa; Elfianty, Lena
MEANS (Media Informasi Analisa dan Sistem) Volume 8 Nomor 2
Publisher : LPPM UNIKA Santo Thomas Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54367/means.v8i2.3264

Abstract

The aim of this research is to implement the Naïve Bayes algorithm for gingivitis classification at Dental Polyclinic, UPTD Pasar Ikan Health Center Bengkulu. The diagnosis of gingivitis is one of the diagnoses with severe conditions that are often complained at Dental Polyclinic, UPTD Pasar Ikan Health Center Bengkulu. However, the problem is that the services are still very limited because doctors are only on duty for 2 days a week. Therefore, a method is needed that is able to classify the risk level of various gingivitis diagnoses that occur at UPTD Pasar Ikan Health Center Bengkulu so that it can be immediately treated with appropriate action using Naïve Bayes method. From the results of tests carried out by Naïve Bayes method, it can be used as a solution for using this system. In its implementation, Naïve Bayes method can classify types of gingivitis at UPTD Pasar Ikan Health Center Bengkulu
Application Of Pcq (Per Connection Queue) In Limiting Bandwidth With The Simple Queue Method At Smkn 1 Seluma Yosef Anggara; Sari , Herlina Latipa; Suryana, Eko
Jurnal Komputer Indonesia Vol. 4 No. 1 (2025): Juni
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jki.v4i1.816

Abstract

The internet network at SMK Negeri 1 Seluma often experiences disruptions when used simultaneously by many users, causing a decline in signal quality and connection difficulties. This study aims to implement bandwidth management so that 30 Mbps internet access can be distributed evenly to three local networks, namely the Administration Room (15 Mbps), the Teacher's Room (10 Mbps), and the Laboratory (5 Mbps). The method used is the PPDIOO approach (Plan, Prepare, Design, Implement, Operate, Optimize) with Per Connection Queue (PCQ) configuration using Simple Queue on the Mikrotik router. Testing was conducted via speedtest before and after PCQ implementation in each room. The results show that bandwidth, which was previously not distributed proportionally, can now be distributed more fairly to each user. For example, in the TU room after PCQ implementation, each of the three clients received relatively equal bandwidth. The implementation of PCQ with Simple Queue proved effective in limiting and dividing bandwidth among users in a balanced manner and improving the overall stability of the school network.
Penerapan Regresi Linear dalam Perkiraan Harga Beras di Kota Bengkulu Azhar Dyo Pramono; Herlina Latipa Sari; Ila Yati Beti
VISA: Journal of Vision and Ideas Vol. 4 No. 2 (2024): VISA: Journal of Vision and Ideas (In Press)
Publisher : IAI Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/visa.v4i2.3662

Abstract

The price of rice tends to fluctuate or change, therefore it is necessary to predict the price in the next period as an effort to maintain the stability of the average price of rice in the community. In Bengkulu City, there are 6 types of rice, namely IR 64 Lampung Local Rice (Medium), IR 64 Bengkulu Local Rice (Medium), Manggis Manis Rice (Premium), Kembang Kol Rice (Premium), Termurah Rice (medium), Bulog/Dolog rice. The implementation of linear regression in rice price forecasting in Bengkulu City can help provide an overview of the estimated price of rice in the next 1 year from January to December based on the results of processing time series data on previous rice prices through Linear Regression Method and can help people to minimize losses and maximize profits, especially for the business and economic sectors. Based on the test results of rice price data from 2021 to 2023, the average results of rice price forecasting on 6 types of rice in 2024 are IR 64 Lampung Local Rice (Medium) with a prediction of IDR 12,202, IR 64 Bengkulu Local Rice (Medium) with a prediction of IDR 12. 094,-, Manggis Manis Rice (Premium) with a prediction of Rp 14,876,-, Kembang Kol Rice (Premium) with a prediction of Rp 15,032,-, Termurah Rice (medium) with a prediction of Rp 11,437,-, Bulog/ Dolog rice with a prediction of Rp 10,900,-.
PENERAPAN METODE K-MEANS CLUSTERING DALAM PENGELOMPOKAN DATA PENJUALAN BARANG DI TOKO USAHA BINGKAI 2 BENGKULU Gustianto, Angga; Sari, Herlina Latipa; Kalsum, Toibah Umi
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 4 (2025): November 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i4.4813

Abstract

Abstract: Toko Usaha Logam 2 Bengkulu is a business selling frames, calligraphy, mirrors, and similar products that still manages transactions manually. This condition complicates the process of recording, sales analysis, and inventory management. This study applies the K-Means Clustering method to group sales data based on inventory quantity and sales volume. The data sample used is transactions during September 2025. Grouping is carried out into three clusters, namely: very popular items, medium-popular items, and not popular items. The results show that there are 6 items included in the very popular category (17.1%), 23 items are in the medium-popular category (65.7%), and 6 items are in the not popular category (17.1%). The application of the K-Means method has been proven to be able to provide information on sales patterns that can assist decision-making in stock management and sales strategies.Keywords: K-Means Clustering Method, Sales Data, Toko Usaha Frame 2 Bengkulu Abstrak: Toko Usaha Bingkai 2 Bengkulu merupakan usaha penjualan bingkai, kaligrafi, cermin, dan produk sejenis yang masih mengelola transaksi secara manual. Kondisi ini menyulitkan proses pencatatan, analisis penjualan, dan manajemen persediaan. Penelitian ini menerapkan metode K-Means Clustering untuk mengelompokkan data penjualan barang berdasarkan jumlah persediaan dan jumlah penjualan. Sampel data yang digunakan adalah transaksi selama bulan September 2025. Pengelompokan dilakukan ke dalam tiga cluster, yaitu: barang sangat laris, laris sedang, dan tidak laris. Hasil penelitian menunjukkan bahwa terdapat 6 barang termasuk kategori sangat laris (17,1%), 23 barang masuk kategori laris sedang (65,7%), dan 6 barang berada pada kategori tidak laris (17,1%). Penerapan metode K-Means terbukti mampu menyediakan informasi pola penjualan yang dapat membantu pengambilan keputusan dalam pengelolaan stok dan strategi penjualan.Kata kunci: K-Means Clustering Method, Sales Data, Toko Usaha Bingkai 2 Bengkulu
Co-Authors Aan Herwansah Adetri Suprianto Agil Setiawan Agri Ayu Dewani Aji Sudarsono Alinse, Rizka Tri Andalah, Haluan Saputra Andre Wedianto Angga Gustianto Anggraini, Reren Anisa Mardhyath Anton Saputra Aprilia Dwi Gumay Ardiansyah, Sohenra Areni Areni Areni, Areni Arius Satoni Kurniawansyah Aryopi Arsipan Asnawati Asnawati Aspriyono , Hari Astika Sari Atang Khotami Azhar Dyo Pramono B. Herawan Hayadi Benri Melpa Metisen Bima Dwi Cahya Bobi Irawan David Tri Julian Devi Sartika Devina Ninosari Dewi Suranti Dimas Aulia Trianggana Edi Kusuma Negara Edo Alwis Eko Suryana Eko Suryana Elfianty , Lena Ezy Sulastari Fakhri Ardiansyah Farizal Sinambela Febrianto Febrianto Felic Valentino Fenggi Wiranto Ferdynan Mashaq Feri Ramadiansyah Fredricka, Jhoanne Gustardi, Rion Gustianto, Angga Haluan Saputra Andalah Handika, Elsi Hari Aspriyono Hari Aspriyono Harjoni Saputra Haryadi, B Herawan Hendri Alamsyah Herizal Syafputra Hermawansyah Hermawansyah Hidayatullah Sholihin Ila Yati Beti Ila Yati Beti Ilham Rivaldo Pratama Indra Utama Intan Diba Aulia Sari Jumadi, Juju Kanedi, Indra Kanedi Khairil Khairil Lena Elfianty Lena Elfianty Leni Natalia Zulita Lisa Trisna Amelia Liza Yulianti Mardiansa Mardiansa Maryaningsih Maryaningsih Mashaq, Ferdynan Moh. Syahrul Adlom Muhammad Anugrah Muhammad Fadhil Z, Rusdi Noor Rosa (p:43-50) Muhammad Hafist Khalaf Nugroho Ponco Riyanto Prahasti Prahasti , Prahasti Prahasti Prahasti Prahasti, Prahasti Pramadana, Yoga Prara Sindia Citra Tessa Pratama, Ilham Rivaldo Rahmat Kurniawan Ramadiansyah, Feri Ricky Zulfiandry Ricky Zulfiandry Riko Mandala Putra Rina Julita Rion Gustardi Riska Riska Rizka Tri Alinse Rizka Tri Alinse Sallaby, Achmad Fikri Samsilul Azhar Samsuri Ridwan sapri sapri Sapri Sapri Saputra, Harjoni Sartika , Devi sono, Aji Sudar Sudarsono , Aji Sulastari, Ezy Suranti, Dewi Tessa, Prara Sindia Citra Toibah Umi Kalsum Toibah Umi Kalsum Venny Novita Sari Wahyu Al-Amar Wahyu Ishak Marzuki Widia Sari Wiranto, Fenggi Yanolanda Suzantri H Yanto, Reno Hendra Yosef Anggara Yupianti - Yupianti, Yupianti