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All Journal ComEngApp : Computer Engineering and Applications Journal Jurnal Online Mahasiswa (JOM) Bidang Ilmu Sosial dan Ilmu Politik Jurnal CoreIT INOVTEK Polbeng - Seri Informatika Building of Informatics, Technology and Science JTIM : Jurnal Teknologi Informasi dan Multimedia JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Information System Journal (INFOS) Jurnal Computer Science and Information Technology (CoSciTech) Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Bulletin of Information Technology (BIT) Malcom: Indonesian Journal of Machine Learning and Computer Science Indonesian Journal of Innovation Multidisipliner Research Scientific Journal of Informatics INOVTEK Polbeng - Seri Informatika
Fitri Insani
Bogor Agricultural University
Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences Other

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UPAYA INDONESIA MEMBEBASKAN TENAGA KERJA INDONESIA TERPIDANA HUKUMAN MATI DI ARAB SAUDI (2011-2013) Insani, Fitri; Jamaan, Ahmad
Jurnal Online Mahasiswa (JOM) Bidang Ilmu Sosial dan Ilmu Politik Vol 2, No 1: WISUDA FEBRUARI 2015
Publisher : Fakultas Ilmu Sosial dan Ilmu Politik Universitas Riau

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Abstract

This research describes about effort of Indonesia to acquitted Indonesia labours who get death penalty in Saudi Arabia’s (2011-2013). There are some Indonesian labours that have been accused of committing a crime that drags them become a convict of the death penalty by a court of Saudi Arabia’s. There are three kind of the death penalty in Saudi Arabia’s, they are: Qishas, Rajam and Ta’zir. As for the allegations imposed on Indonesian labours that under sentence of death in Saudi Arabia’s are torture, murder, perform of magic and adultery.This research used the theory of diplomacy. As for the kind of diplomacy that used are bilateral diplomacy. Bilateral diplomacy is diplomacy carried out by between two countries. This research used nation-state analysis.This study applies qualitative research method with library. The data sources are from books, journal, and the internet.Finnaly, Indonesian government’s actions in providing protection for Indonesian labours who became convicted of the death penalty in 2011-2013 is considered to be the maximum. As for the efforts that has been made are: do moratorium policy, bilateral diplomacy, forming a special task force, appoint of retainer lawyer and assist in paying (diyat) to the families of victims. Those efforts can help the Indonesian labours who convicted of death penalty and get a lighter punishment like a forgiveness from the victim’s family or pay a fine.Keywords: Bilateral Diplomacy, Death Penalty, Effort, Indonesian Labours
KONSTRUKSI MAKNA “TAKKO BINOTO” BAGI PELAKU DI DESA MENAMING KECAMATAN RAMBAH KABUPATEN ROKAN HULU Insani, Fitri; Yohana, Nova
Jurnal Online Mahasiswa (JOM) Bidang Ilmu Sosial dan Ilmu Politik Vol. 6: Edisi II Juli - Desember 2019
Publisher : Fakultas Ilmu Sosial dan Ilmu Politik Universitas Riau

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Abstract

This research is motivated by the phenomenon of Takko binoto which has long been a fairly complex problem in which many male and female couples in realizing their desire to carry out a marriage contract by way of binoto takko. Because they felt that there was a conflict from parents about the relationship they had endured, Takko Binoto was chosen as a way out. Takko Binoto happened because it was influenced by economic aspects and low levels of education. The purpose of this research is to find out the motives behind the couple doing Takko Binoto, understanding the meaning of Takoto Binoto and knowing the communication experience for Takko Binoto actors in Menaming village, Rambah District, Rokan Hulu Regency.This study uses qualitative research methods with a phenomenological approach. Data collection techniques consist of in-depth interviews, observation and documentation. Data analysis techniques consist of data reduction, data presentation and drawing conclusions. The data validity checking technique uses triangulation. The gathering of informants in this study used the Snowball Technique with the number of informants as many as 5 pairs of Takoto Binoto actors.The results of this study show the first few motives of takoto binoto actors in the village menaming are divided into two motives because (because motive) and motives of hope (in order to motive). As for the motives because for Takoto binoto actors are economic factors, mutual love, free promiscuity and low education. Then in order to motive Takko Binoto's perpetrators are motives to provide a deterrent effect, happy motives for the world and the hereafter and motives to ease the burden on the family's economy. Second, the meaning of Takko Binoto for actors in the village of Menaming is the meaning of Takoto Binoto as the destiny of God, Takko Binoto as a result of past actions, and Takko Binoto as the last choice to be taken. Third, the Takko Binoto perpetrators' communication experience consists of pleasant (positive) communication experiences and unpleasant communication experiences. a pleasant (positive) communication experience for Takko Binoto's perpetrators, namely getting a life partner to feel extraordinary love from her husband. Then the unpleasant (negative) communication experience for Takko Binoto actors is getting negative comments, being ostracized from the family and the environment, and family conflicts. Keywords: Construction Meaning, Takko Binoto, Motives
Pembentukan Model Regresi Linier Menggunakan Algoritma Genetika untuk Prediksi Parameter Indeks Standar Pencemar Udara(ISPU) Insani, Fitri; Darlianti, Sri Indah
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 5, No 2 (2019): Desember 2019
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (568.836 KB) | DOI: 10.24014/coreit.v5i2.9157

Abstract

Prediksi merupakan upaya untuk mengetahui suatu peristiwa di masa yang akan datang. Pada kasus prediksi data yang dipelajari merupakan data historis, agar data tersebut dapat mengasilkan informasi berupa hasil prediksi maka digunakan suatu model yaitu regresi linier, dalam proses pembentukan model regresi linier digunakan pendekatan kecerdasan buatan algoritma genetika. Algoritma genetika digunakan untuk mendapatkan nilai koefisien terbaik pada persamaan regresi linier. Penelitian ini menggunakan data parameter Indeks Standar Pencemar Udara(ISPU), terdapat lima parameter ISPU meliputi Sulfur dioksida (SO2), Partikulat (PM10), Karbondioksida (CO), Ozon (O3), dan Nitrogen dioksida (NO2) sehingga dibangun lima model prediksi. Berdasarkan hasil pengujian menggunakan data harian bulan Januari 2016 sampai dengan Desember 2016, algoritma genetika mampu menentukan nilai koefisien yang digunakan pada model regresi linier dalam memprediksi parameter ISPU dengan kesalahan prediksi untuk parameter SO2 yaitu 2,33958%, kesalahan prediksi parameter PM10 6,623923%, kesalahan prediksi parameter CO 2,62279%, kesalahan prediksi parameter O3 6,34495%, dan kesalahan prediksi parameter NO2 2,927575%
Implementasi Algoritma K-Means dalam Menentukan Clustering pada Penilaian Kepuasan Pelanggan di Badan Pelatihan Kesehatan Pekanbaru Fahrozi, Aqshol Al; Insani, Fitri; Budianita, Elvia; Afrianty, Iis
Indonesian Journal of Innovation Multidisipliner Research Vol. 1 No. 4 (2023): December
Publisher : Institute of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/ijim.v1i4.53

Abstract

This research discusses the implementation of the K-Means algorithm in determining clustering in customer satisfaction assessments at the Pekanbaru Health Training Agency. Customer satisfaction is the level of a person's feelings to perceive the comparison between the consumer's impression of the level of product and service performance and the customer's or buyer's expectations. The aim of this research is to see the level of customer satisfaction with the Pekanbaru Health Training Agency (Bapalkes) services using K-means clustering and how high the level of customer satisfaction is using the K-means Clustering method. In this research, the data used is Health Training Center customer data from 2019 and 2023. Data was collected through questionnaires distributed via Google form. Creating a rule model for the collected data using the k-means algorithm and rapidminer software. From the research results obtained using the K-Means algorithm in clustering customer data, it can provide customer segmentation results that are in line with expectations, so that the Pekanbaru Health Training Agency can easily understand the characteristics of its customers based on their clusters and their satisfaction. Then, using the elbow and Davies Bouldin methods, we also provide a solution for selecting the right number of clusters so that performance is more optimal and produces more accurate customer segmentation results. From the calculations of the k-means algorithm, it was obtained that the response value was very dominant at 259 who expressed satisfaction and 44 people who expressed dissatisfaction from 303 customers, so that the k-means algorithm used sensitivity and specificity tests, 86% expressed satisfaction and 14% expressed dissatisfaction with services provided by the Pekanbaru Health Training Agency.
Implementasi Metode Learning Vector Quantization (LVQ) Untuk Klasifikasi Keluarga Beresiko Stunting Aziz, Abdul; Insani, Fitri; Jasril, Jasril; Syafria, Fadhilah
Building of Informatics, Technology and Science (BITS) Vol 5 No 1 (2023): June 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i1.3478

Abstract

Stunting is a condition where a child's height is too short compared to children of the same age. This condition affects the health of toddlers in the short and long term, such as suboptimal body posture in adulthood, decreased reproductive health, and decreased learning capacity, resulting in suboptimal performance in school. One of the causes of stunting is a lack of nutrition, basic health facilities, and poor parenting practices. However, the current data collection and classification of families at risk of stunting still use Microsoft Excel, which is ineffective in processing large data. Therefore, the LVQ method, which is an improvement of the Vector Quantization method, is used to accelerate the classification process. In this study, 5 parameters were tested, and the optimal result was achieved by using 7 input neurons, Chebychev distance as the distance measure, a learning rate of 0.1, 7 epochs, and 30% of training data. With these parameters, an accuracy of 99.38% was obtained. Based on these results, the LVQ method can help improve accuracy in classifying families at risk of stunting
Penerapan Deep Learning Menggunakan Gated Recurrent Unit Untuk Memprediksi Harga Minyak Mentah Dunia Saputra, Nugroho Wahyu; Insani, Fitri; Agustian, Surya; Sanjaya, Suwanto
Building of Informatics, Technology and Science (BITS) Vol 5 No 1 (2023): June 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i1.3552

Abstract

Crude oil is a much-needed energy for the whole world. Each country is inseparable from the use of crude oil for use in various sectors, such as transportation, so that the price of world crude oil is the most important variable for the world. Fluctuations in oil prices will cause various problems, such as inflation, changes in market prices, and others. Therefore, the prediction of world crude oil prices is very important as a consideration for decision making. This study implements deep learning using the Gated Recurrent unit model. The data used is the price of Brent crude oil with a total of 5834 data, starting from January 4, 2000 to December 19, 2022. The parameters used are the number of GRU units, batch size, and lookback. The best model produced in this study is the GRU model with hyperparameters consisting of 30 lookbacks, 50 GRU units, and 256 batch sizes with the lowest MAPE value among the other models, which is 2.25%. The MAPE value states that predictions using the GRU model are said to be very good at predicting world crude oil prices
Analisis Pola Asosiasi Data Transaksi Penjualan Minuman Menggunakan Algoritma FP-Growth dan Eclat Najmi, Risna Lailatun; Irsyad, Muhammad; Insani, Fitri; Nazir, Alwis; ., Pizaini
Building of Informatics, Technology and Science (BITS) Vol 5 No 1 (2023): June 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i1.3592

Abstract

Every day transaction activities between companies and consumers continue to be carried out. This makes transaction data more and more and accumulate. This transaction data can be processed into more useful information using technology. Data mining is a technology that can work on a collection of transaction data into information that can be taken by companies as decision makers. The association rule method is used as a method to see the relationship between items in a transaction data. To analyze transaction data, researchers used the FP-Growth and Eclat algorithms. There are three stages of association in this study which are distinguished from the confidence value. The results in the first stage have a minimum confidence value of 0.4, the FP-Growth algorithm produces 41 association pattern rules, while the Eclat algorithm produces 32 association pattern rules. Then in the second stage the minimum trust value is 0.5, the FP-Growth algorithm produces 40 association pattern rules, for the Eclat algorithm it produces 32 association pattern rules. In the third stage, the minimum trust value is 0.6, the FP-Growth algorithm generates 32 association pattern rules, while the Eclat algorithm generates 30 association pattern rules. The results of the association pattern rules show that the Eclat algorithm is more efficient in determining the association pattern rules than the Fp-Growth algorithm
Sistem Klasifikasi Penyakit Jantung Menggunakan Teknik Pendekatan SMOTE Pada Algoritma Modified K-Nearest Neighbor Novitasari, Fitria; Haerani, Elin; Nazir, Alwis; Jasril, Jasril; Insani, Fitri
Building of Informatics, Technology and Science (BITS) Vol 5 No 1 (2023): June 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i1.3610

Abstract

The heart is a vital organ that plays a crucial role in pumping oxygenated blood and nutrients throughout the body. Heart disease refers to damage to the heart that can occur in various forms, caused by infections or congenital abnormalities. The World Health Organization (WHO) reports nearly 17.9 million deaths each year due to heart disease. In Indonesia, the prevalence of heart disease is around 1.5%, meaning that in 2018, approximately 15 out of 1,000 people, or nearly 2,784,060 individuals, were affected by this disease, according to the Basic Health Research data (Riskesdas) 2018. Many people have limited knowledge about heart health, leading to a lack of awareness of their heart conditions. This can be attributed to a lack of understanding regarding the importance of medical checkups related to heart health. Modified K-Nearest Neighbors (MKNN) is one of the data mining methods applied for classifying the risk of heart disease. The research utilized data obtained from the UCI dataset repository, which consists of 918 records with 12 attributes. To balance the imbalanced dataset with minority classes, the Synthetic Minority Over-sampling Technique (SMOTE) approach was used to generate new synthetic samples from the minority class. The objective of developing a web-based system for heart disease classification is to assist the public in assessing their risk of heart disease as early as possible, enabling them to take preventive actions sooner. The accuracy results of the MKNN algorithm with a 90:10 ratio are 80.37%, while with the MKNN+SMOTE approach, the accuracy increased to 84.00%. The use of the SMOTE approach improved the accuracy of low-performing data.
Penerapan Langchain Retriever dengan Model Chat Openai dalam Pengembangan Sistem Chatbot Hadis Berbasis Telegram Herwanza, Niken Aisyah Maharani; Harahap, Nazruddin Safaat; Yanto, Febi; Insani, Fitri
JTIM : Jurnal Teknologi Informasi dan Multimedia Vol 6 No 1 (2024): May
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v6i1.514

Abstract

In Islamic studies, the Hadiths of Prophet Muhammad (SAW) hold significant value as guides for behavior and faith. However, access to understanding Hadiths often presents challenges, espe-cially for those who are not Hadith experts. The digitalization of Hadiths is still limited, making it time-consuming to find answers by sifting through the vast amount of available information. This research aims to create an efficient chatbot that provides answers related to Hadiths, including the original sources, quickly. The proposed solution is a technology-based approach through the development of a Hadith chatbot on Telegram, integrated with the LangChain Retriever and the GPT-4-1106-preview chat model from OpenAI. Using LangChain Retriever helps the chatbot find accurate answers by matching user questions with relevant Hadith databases, enhancing the ac-curacy of the chatbot's responses. The GPT-4-1106-preview chat model enables the chatbot to generate natural and context-appropriate responses, improving user interaction. The Rapid Ap-plication Development (RAD) method is applied in system development, through stages of Re-quirement Planning, User Design, Construction, and Cut-Over, including data analysis of Hadiths from the Nine Imam Hadith Books, totaling 62,169 Hadiths. The chatbot's performance evaluation uses the Scoring Evaluator framework with an average evaluation score of 0.97 and quality answer evaluation testing by five Hadith experts with an accuracy percentage of 90%. The Scoring Eval-uator test results indicate that the responses are highly accurate and aligned with Hadith refer-ences, and the quality answer evaluation test on a Likert scale shows respondents strongly agree with the system's answers. This research contributes to laypersons wanting to learn Hadiths by utilizing the chatbot as an interactive and innovative learning medium. Further research can expand the focus to complex interpretations of Musykil al-Hadith and asbab al-wurud to address deeper questions about Hadith interpretation.
Diagnosis Dini Penyakit Gagal Ginjal Dengan Metode Dempster Fakhira, Adzra; Insani, Fitri; Irsyad, Muhammad; Vitriani, Yelfi; Kurnia, Fitra
Jurnal Inovtek Polbeng Seri Informatika Vol 8, No 2 (2023)
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/isi.v8i2.3728

Abstract

Terlambatmendeteksipenyakitgagalginjalakanberakibatseriuskarenadiagnosisbiasanya terjadiketika masalah ginjal sudah mencapai tingkat parah. Seperti yang telah terjadi di Indonesia pada tahun 2022 lalu, terdapat 324 kasus terkonfirmasi dan 195 diantaranya meninggal dunia. Hal yang mempengaruhiketerlambatankesadaranpenderitaadalahpengetahuanyangkurangterhadapbahayapenyakit gagal ginjal. Penyakit gagal ginjal dapat disebabkan oleh dehidrasi, penyakit kronis seperti hypertensi dan diabetes, serta kekurangan banyak darah akibat  cedera atau operasi. Penggunaan teknologi dapat terwujud melalui pembuatan sistem pakardengan metode Dempster Shafer guna mendiagnosis penyakit gagal ginjal.Dalam sistem pakardiagnosis dini penyakit gagal ginjal ini penggunadiperintahkan agar mengisi data diri singkatdan gejala-gejala yang dialami. Selanjutnya sistem akan mengkombinasi gejala yang telahdipilih dengan metode Dempster Shafer menggunakan teori kepercayaan pakar sehingga mendapatkan hasil diagnosis berupa persentase pengguna mengidap penyakit gagal ginjal akut atau kronis, dan solusi untuk tindakan pengguna berikutnya. Penelitian ini telah menghasilkan sistem yang mampu mendiagnosis penyakit gagal ginjal dan dapat diterima dengan baik oleh pengguna
Co-Authors ., Pizaini Abdul Aziz Afriyanti, Liza Agustian, Surya Ahmad Fauzan Al Fiqri, M. Faiz Ananda, Rahmadan Alam Ardan Aqilah, M Alfandri Damayanti, Elok Darlianti, Sri Indah Elin Haerani Elvia Budianita Fadhilah Syafria Fahrozi, Aqshol Al Fakhira, Adzra Febi Yanto, Febi Fitria Novitasari Hasibuan, Aldiansyah Pramudia Herwanza, Niken Aisyah Maharani Iis Afrianty Iwan Iskandar Jasril Jasril Jasril Jasril Kurnia Rahman, Fikri kurnia, fitra Lestari Handayani Mai Candra, Reski Miftah Farid Muhammad Abdillah Muhammad Affandes, Muhammad Muhammad Fikry Muhammad Irsyad Muhammad Ravil Mulyadi, Syahrul Najmi, Risna Lailatun Nazir, Alwis Nazruddin Safaat H Nova Yohana Novi Yanti Okfalisa Okfalisa Oktavia, Lola Rahmad Abdillah Ruri Hartika Zain Saputra, Nugroho Wahyu Setiawan, Adil Subhi, Yazid Abdullah Suwanto Sanjaya Tri Prastio Nugroho Utari, Roid Fitrah Vernando, Julio Vitriani, Yelfi Yusra Zahri, Firman